Regulation of miRNA expression during Sorafenib treatment in hepatocellular carcinoma. Development of a new therapeutic approach

Regulación de la expresión de miRNAs durante el tratamiento con Sorafenib en el carcinoma hepatocelular. Desarrollo de una nueva estrategia terapéutica Laboratorio de Cirugía Oncológica, Trasplante de Órganos y Terapia Celular. Instituto de Biomedicina de Sevilla (IBiS). Hospital Universitario “Virgen del Rocío” Programa de Doctorado en Biología Molecular, Biomedicina e Investigación Clínica. Departamento de Cirugía. Universidad de Sevilla Patricia de la Cruz Ojeda Tutor y Director: Jordi Muntané Relat Co-director: Juan Manuel Falcón Pérez Sevilla, 2023 Regulation of miRNA expression during Sorafenib treatment in hepatocellular carcinoma. Development of a new therapeutic approach Laboratory of Oncological Surgery, Organ Transplantation and Cell Therapy. Institute of Biomedicine of Seville (IBiS). Hospital University “Virgen del Rocío” PhD Programme in Molecular Biology, Biomedicine and Clinical Research. Department of Medical Physiology and Biophysics. University of Seville Patricia de la Cruz Ojeda PhD Supervisor: Jordi Muntané Relat PhD Co-Supervisor: Juan Manuel Falcón Pérez Seville, 2023 Dr. Jordi Muntané Relat, Co-Investigador Responsable del grupo de Cirugía Oncológica, Terapia Celular y Trasplante de Órganos del Investigador en el Instituto de Biomedicina de Sevilla (IBiS), y Profesor Titular del Departamento de Fisiología Médica y Biofísica de la Universidad de Sevilla, en calidad de tutor y director de la Tesis Doctoral de Patricia de la Cruz Ojeda, Dr. Juan Manuel Falcón Pérez, Investigador Responsable del grupo de Exosomas (Exosomes Lab) y jefe de la plataforma de Metabolómica del CIC bioGUNE, en calidad de co-tutor de la Tesis Doctoral de Patricia de la Cruz Ojeda, CERTIFICAN Que, Dña. Patricia de la Cruz Ojeda, Graduada en Biotecnología por la Universidad Pablo de Olavide, ha realizado bajo su dirección el trabajo titulado “Regulación de la expresión de miRNAs durante el tratamiento con Sorafenib en el carcinoma hepatocelular. Desarrollo de una nueva estrategia terapéutica” (“Regulation of miRNA expression during Sorafenib treatment in hepatocellular carcinoma. Development of a new therapeutic approach”), y autorizan su presentación como Tesis Doctoral para la obtención del grado de Doctor por la Universidad de Sevilla. Y para que así conste a todos los efectos oportunos, firman el presente certificado en Sevilla, en 2023. Tutor y Director Co-Tutor Dr. Jordi Muntané Relat Dr. Juan Manuel Falcón Pérez La Doctoranda Dña. Patricia de la Cruz Ojeda DE LA CRUZ OJEDA PATRICIA - 45336926Q Firmado digitalmente por DE LA CRUZ OJEDA PATRICIA - 45336926Q Fecha: 2023.01.27 01:26:48 +01'00' FALCON PEREZ JUAN MANUEL - 28489568C Digitally signed by FALCON PEREZ JUAN MANUEL - 28489568C Date: 2023.01.27 11:04:28 +01'00' MUNTANE RELAT JORDI - 39331869Y Firmado digitalmente por MUNTANE RELAT JORDI - 39331869Y Nombre de reconocimiento (DN): c=ES, serialNumber=IDCES-39331869Y, givenName=JORDI, sn=MUNTANE RELAT, cn=MUNTANE RELAT JORDI - 39331869Y Fecha: 2023.01.27 11:11:03 +01'00' A mis padres AGRADECIMIENTOS Doctoral Thesis Patricia de la Cruz Ojeda 8 Doctoral Thesis Patricia de la Cruz Ojeda 9 INDEX NORMATIVA/REGULATIONS ................................................................... 17 Apoyos Institucionales ................................................................................ 17 Mención Internacional ................................................................................. 23 SUMMARY ....................................................................................................... 27 ABREVIATIONS .............................................................................................. 33 FIGURE INDEX ................................................................................................ 41 TABLE INDEX .................................................................................................. 57 1. INTRODUCTION .................................................................................. 65 1.1 Hepatocellular Carcinoma (HCC) ................................................... 65 1.1.1 Incidence, epidemiology and natural history of HCC ............ 65 1.1.2 Staging, treatment allocation and prognosis of HCC .............. 68 1.2 Molecular mechanisms of Sorafenib in liver cancer ..................... 72 1.3 Genetic landscape of HCC ................................................................ 74 1.3.1 Genetic predisposition to HCC ................................................... 74 1.3.2 Mechanisms of malignant transformation in HCC.................. 74 1.4 Liquid biopsy ...................................................................................... 75 1.4.1 Circulating tumor cells (CTCs) ................................................... 76 1.4.2 miRNAs .......................................................................................... 82 1.4.3 Extracellular vesicles .................................................................... 93 1.5 Development of new alternative therapeutic approaches: nanovectorization of miRNAs ............................................................................. 107 1.5.1 β-Cyclodextrins (CDs) ................................................................ 108 2. HYPOTHESIS AND OBJECTIVES .................................................... 113 2.1 Hypothesis ........................................................................................ 113 2.2 Objectives .......................................................................................... 114 3. MATHERIALS, METHODS AND PATIENTS ................................ 117 3.1 Type of study .................................................................................... 117 3.1 Cell culture ........................................................................................ 117 3.1.1 Primary hepatocytes isolation and cell culture ...................... 117 3.1.2 Cell treatments ............................................................................ 118 3.2 Patients .............................................................................................. 119 Doctoral Thesis Patricia de la Cruz Ojeda 10 3.3 miRNA array and bioinformatic analysis .................................... 120 3.3.1 miRNA profiling ......................................................................... 120 3.3.2 Data analysis ................................................................................ 120 3.3.3 Bioinformatic analysis ................................................................ 121 3.4 Measurement of miRNA expression ............................................. 121 3.4.1 RNA extraction ............................................................................ 121 3.4.2 Reverse transcription and qPCR ............................................... 122 3.5 Transient transfections with miRNA mimics and inhibitors .... 123 3.6 Cell proliferation assay ................................................................... 125 3.7 Preparation of cell lysate ................................................................. 125 3.8 Protein quantification ...................................................................... 126 3.9 Cell death assay ................................................................................ 126 3.10 Cell migration assay ..................................................................... 127 3.11 Cell invasion assay ....................................................................... 127 3.12 Isolation of extracellular vesicles ............................................... 127 3.12.1 EVs depletion from FBS ............................................................. 127 3.12.2 Experimental procedure ............................................................ 128 3.13 EVs size analysis based on Brownian motion of particles ..... 129 3.13.1 Dynamic Light Scattering .......................................................... 129 3.13.2 Nanoparticle Tracking Analysis ............................................... 130 3.13.3 Cryo-Electron Microscopy (cryo-EM) ...................................... 130 3.14 Assessment of protein expression by Western Blot ................ 130 3.15 mRNA Sequencing ....................................................................... 132 3.15.1 RNA quality and quantity assessments .................................. 134 3.15.2 Library Generation ..................................................................... 134 3.15.3 Library amplification with dual indices .................................. 135 3.15.4 Library quantity and quality assessments .............................. 136 3.15.5 Library pooling and dilution..................................................... 136 3.15.6 mRNA sequencing data analysis .............................................. 136 3.16 Circulating Epithelial Cell enrichment ...................................... 137 3.17 Circulating Epithelial Cell enumeration ................................... 138 3.17.1 Technique efficiency evaluation ............................................... 140 Doctoral Thesis Patricia de la Cruz Ojeda 11 3.18 Assessment of cell proliferation and death in CECs ............... 140 3.18.1 CTCs cell culture ......................................................................... 140 3.18.2 Flow cytometry ........................................................................... 140 3.19 Assessment of effectiveness of CDplexes functionalized with miRNA mimics ....................................................................................................... 142 3.19.1 Preparation of CDplexes ............................................................ 142 3.19.2 Characterization of CDplexes by DLS ..................................... 146 3.19.3 Transfection of SNU499 cells with CDplexes ......................... 146 3.20 Statistical analysis ......................................................................... 147 4. RESULTS ............................................................................................... 151 4.1 Objective 1. Prospective study of the secretion profile of EVs and CECs in patients of HCC at intermediate and advanced stages, and their relationship with clinical outcome. ..................................................................... 151 4.1.1 High CECs counts correlated with HCC ................................. 151 4.1.2 CECs counts showed a tendency to decrease with malignant phenotype 155 4.1.3 Evaluation of the impact of CECs levels in the prognosis of HCC patients treated with TACE .................................................................... 163 4.1.4 Evaluation of the impact of CECs levels in the prognosis of HCC patients treated with Sorafenib .............................................................. 168 4.1.5 Evaluation of the impact of CECs levels in the prognosis of HCC patients treated with Lenvatinib ............................................................ 170 4.2 Objective 2. Anti-proliferative and pro-apoptotic response of CECs under pharmacological pressure (Doxorubicin, Sorafenib, Regorafenib, Lenvatinib, Cabozantinib). ................................................................................... 172 4.3 Objective 3. Isolation and characterization of EVs (large, small and very small EVs) secreted by HCC cells in vitro after treatment (Sorafenib, Regorafenib, Lenvatinib, Cabozantinib), and its relationship with cell death, cell proliferation, migration and invasion. ......................................................... 176 4.3.1 Sorafenib exerted anti-tumoral properties in liver cancer cells 176 4.3.2 Sorafenib attenuated EVs secretion .......................................... 177 4.3.3 Anti-tumoral signaling induced by other tyrosine kinase inhibitors (Regorafenib, Lenvatinib, Cabozantinib). ..................................... 181 4.3.4 Differential EVs secretion patterns induced by Regorafenib, Lenvatinib and Cabozantinib ........................................................................... 182 Doctoral Thesis Patricia de la Cruz Ojeda 12 4.4 Objective 4. Determination of circulating miRNA profile before and 1 month after Sorafenib treatment in HCC patients at advanced stages (objective 1), compared to miRNAs in EVs (objective 2), and in vitro data. Functional impact of miRNAs in cell proliferation, cell death, migration and invasion, and regulation of mRNAs involved in tumor processes. ............... 186 4.4.1 Analysis of miRNA expression in primary human hepatocytes and liver cancer cells .......................................................................................... 186 4.4.2 Functional analysis with miRNA mimics and inhibitors revealed pro- and anti-tumoral miRNAs........................................................ 190 4.4.3 Sorafenib altered the secretion of miRNAs ............................. 194 4.4.4 Transcriptomic impact of miRNAs on the anti-tumoral properties of Sorafenib ...................................................................................... 198 4.4.5 Circulating levels of miR-200c-3p, miR-222-5p and miR-512-3p constituted a miRNA signature of Sorafenib response in patients with advanced HCC .................................................................................................... 220 4.4.6 Analysis of common pathways regulated by miR-200c-3p, miR-222-5p and miR-512-3p ............................................................................. 227 4.4.7 Assessment of miR-200c-3p, miR-222-5p and miR-512-3p expression in patient derived EVs ................................................................... 229 4.5 Objective 5. Development of new therapeutic strategies based of cyclodextrin nanovectors functionalized with miRNA mimics (Objective 4). 231 4.5.1 Physical characterization of AMC6 and ADM70 cyclodextrin nanovectors 231 4.5.2 Internalization of nanovectors by endosomal pathways ...... 234 4.5.3 Transfection efficiency of cyclodextrin nanovectors ............. 236 5. DISCUSSION ........................................................................................ 241 5.1 The usage of CECs as diagnostic and prognostic biomarkers of HCC 241 5.2 Differential anti-tumor properties of Sorafenib and other TKIs (Regorafenib, Lenvatinib, Cabozantinib) ........................................................... 242 5.3 The role of EVs during Sorafenib response in HCC ................... 244 5.3.1 Sorafenib altered the secretion of EVs ..................................... 244 5.4 miRNAs as biomarkers of Sorafenib response in HCC .............. 245 5.4.1 miRNA profile related to hepatocarcinogenesis .................... 245 Doctoral Thesis Patricia de la Cruz Ojeda 13 5.4.2 miRNA profile of HepG2 cells treated with Sorafenib and their prognostic role in HCC ............................................................................ 248 5.5 Delivery of miR-200c-3p mimics in cyclodextrin nanovectors .. 258 6. CONCLUSIONS .................................................................................. 263 7. BIBLIOGRAPHY .................................................................................. 267 SCIENTIFIC CONTRIBUTIONS ................................................................. 299 Publications ................................................................................................. 299 Participation in congresses and seminars ............................................... 305 APPENDICES ................................................................................................. 313 Doctoral Thesis Patricia de la Cruz Ojeda 14 Doctoral Thesis Patricia de la Cruz Ojeda 15 NORMATIVA/REGULATIONS Doctoral Thesis Patricia de la Cruz Ojeda 16 Doctoral Thesis Patricia de la Cruz Ojeda 17 NORMATIVA/REGULATIONS Apoyos Institucionales El presente trabajo ha sido desarrollado en el Instituto de Biomedicina de Sevilla (IBiS), centro de carácter mixto por pertenecer institucionalmente a la Universidad de Sevilla, Hospital Universitario Virgen del Rocío, Junta de Andalucía y Consejo Superior de Investigaciones Científicas (CSIC), en el laboratorio 209, grupo de Cirugía Oncológica, Terapia Celular y Trasplante de Órganos del Investigador en el Instituto de Biomedicina de Sevilla (IBiS), siendo el Prof. Dr. Francisco Javier Padillo Ruiz su Investigador Responsable y el Dr. Jordi Muntané el Co-Investigador Responsable. El soporte económico para el desarrollo de los diferentes objetivos de esta Tesis Doctoral proviene principalmente de las siguientes fuentes: ‐ Beca del Programa de Formación del Profesorado Universitario (FPU) del Ministerio de Universidades, con referencia FPU17/00026. ‐ Beca de Movilidad del Grupo Español de Innovación e Investigación en Vesículas Extracelulares (GEIVEX) en convocatoria de 2020 para la realización de una estancia corta de 1 mes de duración en el Laboratorio del Dr. Juan Manuel Falcón Pérez ‐ Beca de Movilidad de Estancias Breves y Traslados FPU en convocatoria de 2019-2020, con referencia EST19/01091, para la realización de una estancia de 3 meses de duración en el laboratorio del Prof. Dr. Bernhard Brüne y el Dr. Tobias Schmid. ‐ Proyecto PI16/00090, titulado “Marcadores genéticos, transcriptómicos y proteómicos relacionados con la evolución del hepatocarcinoma, co-morbilidades y respuesta a los tratamientos”, financiado por el Instituto de Salud Carlos III. Se incluye informe favorable del comité ético (muestras humanas). ‐ Proyecto PI-0216-2020, titulado “Identificación del papel de miRNA y lncRNA en las células tumorales circulantes en la progresión y respuesta al tratamiento en pacientes con carcinoma hepatocelular en Doctoral Thesis Patricia de la Cruz Ojeda 24 Doctoral Thesis Patricia de la Cruz Ojeda 25 SUMMARY Doctoral Thesis Patricia de la Cruz Ojeda 26 Doctoral Thesis Patricia de la Cruz Ojeda 27 SUMMARY Hepatocellular carcinoma (HCC) is one of the most frequent neoplasia and one of the major causes of cancer-related death worldwide. It usually arises upon chronic liver damage in cirrhotic livers. Several with different incidence increase the risk of HCC development, including hepatitis B and C virus infection, nonalcoholic liver disease (NAFLD) and alcohol abuse, among others. In the last years, there has been a shift in epidemiology from viral hepatitis to NAFLD and alcoholic liver disease (ALD). Treatment and patient prognosis are stablished according to the Barcelona Clinic Liver Cancer Staging System (BCLC). While early stages might receive curative treatments, intermediate and advanced stages of the disease rely on palliative treatments. The standard of care for intermediate patients at BCLC-B stages is transartherial chemoembolization (TACE), that consists in the embolization of the arteries that irrigate the tumor and the delivery of doxorubicin eluting beads. The landscape of treatments for advanced stages (BCLC-C) and patients at BCLC-B with untreatable progressive disease has profoundly changed. Nowadays, the combined treatment of Atezolizumab + Bevacizumab is the first line treatment. For patients in whom immunotherapy is not feasible, the tyrosine kinase inhibitors (TKIs) Sorafenib or Lenvatinib are still suitable therapeutic options. Regorafenib might be used upon Sorafenib progression in Sorafenib tolerant patients, and Cabozantinib has shown to be similar to Regorafenib. Given the limited efficacy of Sorafenib and other tyrosine kinase inhibitors (TKIs) in the clinical setting, new biomarkers of patient prognosis are urgently needed. In particular, liquid biopsy such as circulating tumor cells (CTCs), miRNAs, and extracellular vesicles (EVs). Therefore, the current thesis focuses on the impact of CTCs, EVs and miRNAs in the prognosis of patients with HCC at intermediate or advanced stages treated with TACE, Sorafenib or Lenvatinib. Circulating epithelial cells (CECs) were used as surrogate biomarkers or CTCs. Results were expressed as the percentage of cytokeratin positive cells in total enriched nucleated cells. Herein we demonstrated that CECs might be potential diagnostic liquid biopsy biomarkers of HCC, as CECs ≥ 5.21 (%) and Doctoral Thesis Patricia de la Cruz Ojeda 28 clustered CECs ≥ 0.285 (%) correlated with HCC. High counts of CECs were related to worse prognosis in HCC patients treated with TACE. Baseline counts of CECs ≥ 15.315 (%) were related to increased risk of death in BCLC-A and BCLC-B patients treated with TACE. In BCLC-B stages, baseline levels of CECs (%), clusters ≥ 0.48 (%) and clustered CECs ≥ 1.395 (%) were associated with higher risk of progression. In more advanced tumor stages, time-dependent values of CECs after 1 month of Sorafenib treatment were related to increased risk of progression in BCLC-B and BCLC-C patients. CECs displayed differential proliferative and apoptotic features in response to Sorafenib, Regorafenib, Lenvatinib, Cabozantinib and Doxorubicin treatment ex vivo, supporting personalized medicine approaches. In liver cancer cells, Sorafenib exerted anti-tumoral properties in HepG2 cells by downregulating proliferation, migration and invasiveness, and upregulating apoptosis and autophagy. Sorafenib was the TKI with the most anti-tumoral effect, compared to Lenvatinib, Regorafenib or Cabozantinib. Sorafenib altered the expression of 11 miRNAs. At 6 hours it induced the downregulation of miR-551a, and upregulation of miR-122-5p, miR-200c-3p and miR-505-5p. At 24 hours of Sorafenib treatment, miR-148b-3p, miR-194-5p, miR- 222-5p and miR-512-3p were downregulated, and miR-27a-3p, miR-193b-3p and miR-375 were upregulated. From these, miR-27a-3p and miR-200c-3p exerted clear anti-tumoral properties, while miR-122-5p, miR-148b-3p, miR-194-5p, miR- 505-5p and miR-512-3p displayed unequivocal pro-tumoral functions. miR-551a, miR-193b-3p and miR-222-5p showed both anti- and pro-tumorigenic properties. miR-375 did not show any effect. Transcriptomic profiles suggested that miRNAs regulate Sorafenib response by controlling apoptosis, proliferation, damage response, oxidation-reduction processes, mitochondria, cell cycle, and metabolism, among others. The anti-tumoral effect of Sorafenib was related to increased release of apoptotic bodies and decreased secretion of exosomes. Regorafenib and Cabozantinib also induced the secretion of apoptotic bodies, but to a lesser extent than Sorafenib. Lenvatinib induced the release of exosomes. In particular, Doctoral Thesis Patricia de la Cruz Ojeda 29 Sorafenib induced the secretion of miR-122-5p, miR-200c-3p, miR-27a-3p, miR- 148b-3p, miR-193b-3p, miR-194-5p and miR-375 in the exosomal fraction. The usage of this miRNA signature was tested as circulating biomarkers of HCC in two independent cohorts of patients with advanced HCC treated with Sorafenib. Baseline levels of miR-200c-3p were related to increased survival, whereas time-dependent values of miR-222-5p and miR-512-3p at 1 month of Sorafenib treatment were related to bad prognosis. These miRNAs were related to cell dedifferentiation and aggressiveness. Thanks to the development of these new liquid biomarkers and given the limited effectiveness of Sorafenib treatment in patients, we developed a new therapeutic strategy for the delivery of anti-tumoral miR-200c-3p to tumor cells. We were able to encapsulate miR-200c-3p mimics in β-cyclodextrins AMC6 and ADM70. AMC6 CDplexes delivering 15 nM of miRNA mimics were incorporated to liver cancer cells by endocytic mechanisms to efficiently increase miR-200c-3p levels. In summary, this project found liquid biopsy biomarkers of therapy response in HCC. CTCs were explored as diagnostic and prognostic markers in intermediate and advanced HCC patients treated with TACE and Sorafenib. Also, the secretion of a specific EVs pattern was related to Sorafenib effectiveness. Circulating levels of miR-200c-3p, miR-222-5p and miR-512-3p were related to Sorafenib response in patients with advanced HCC. Lastly, β-cyclodextrins nanovectors were constructed to efficiently deliver the anti-tumoral miR-200c-3p to liver cancer cells. Doctoral Thesis Patricia de la Cruz Ojeda 30 Doctoral Thesis Patricia de la Cruz Ojeda 31 ABBREVIATIONS Doctoral Thesis Patricia de la Cruz Ojeda 32 Doctoral Thesis Patricia de la Cruz Ojeda 33 ABREVIATIONS AGO2 ArGOnaute-2 ABCB1 ATP Binding Cassette Subfamily B Member 1 ABCG2 ATP-binding cassette subfamily G member 2 ABs Apoptotic Bodies ACOX1 Acyl-CoA oxidase 1 ACSL4 Acyl-CoA Synthetase Long chain family member 4 AFP α‐FetoProtein Akt, PKB Protein Kinase B ALD Alcoholic Liver Disease ALP Alkaline Phosphatase ALT Alanine Aminotransferase AMPK 5' AMP-activated Protein Kinase ANGPT2 Angiopoietin 2 ANOVA Analysis Of VAriance ANT2 Adenine Nucleotide Translocase 2 ANXA2 Annexin A2 APC Adenomatous Polyposis Coli AR Androgen Receptor ARF ADP-Ribosylation Factor AST Aspartate Aminotransaminase ATG Autophagy Related BCLC Barcelona Clinic Liver Cancer BrdU BromodeoxyUridine BSA Bovine Serum Albumin BTG3 BTG anti-proliferation factor 3 CAFs Cancer-Associated Fibroblasts CD CycloDextrin CEC Circulating Epithelial Cell CHOP C/EBP Homologous Protein CI Confidence Interval circRNA Circular RNA CLCF1 Cardiotrophin-Like Cytokine Factor 1 Doctoral Thesis Patricia de la Cruz Ojeda 40 Doctoral Thesis Patricia de la Cruz Ojeda 41 FIGURE INDEX Figure 1. World map showing incidence and epidemiological trends of HCC. 2020 Worldwide Age-standardized HCC Incidence Rates, both sexes, all ages. Figure adapted from [1]. ............................................................................................. 65 Figure 2. BCLC staging system. Very early stages (BCLC-0) and early stages (BCLC-A) undergo ablation, liver resection or transplantation curative treatments. If not feasible, patients should migrate to TACE. Patients with multinodular tumors but preserved liver function should undergo TACE. Whenever this is not possible, treatment strategies must migrate to systemic therapy. Advanced stages are characterized by the presence of portal invasion and/or extrahepatic metastasis. Systemic therapies include immunotherapy, tyrosine kinase inhibitors and clinical trials. For patients with end stage liver disease and Performance Status (PS) 3-4, best supportive care should be provided. ....................................................................................................................... 72 Figure 3. General mechanisms of CTC dissemination in peripheral blood. Cancer cells from primary tumors that undergo EMT are able intravasate into the bloodstream, turning into CTCs. CTCs might display epithelial, EMT of mesenchymal phenotype. Cells might undergo cell death upon loss of adhesion (anoikis). In order to survive, CTCs might associate with blood cells (neutrophils, platelets, macrophages or myeloid cells), or cancer-associated fibroblast. Reverse MET is required for distant growth and metastasis. .............................................. 78 Figure 4. miRNA biogenesis and mechanisms of action. miRNAs are transcribed in the nucleus mostly by the RNA polymerase II into pri-miRNAs. These precursors are cleaved by DROSHA to form loop pre-miRNAs, that are transported to the cytoplasm. Cleavage by DICER forms a miRNA duplex, whose guide strand is incorporated in the RISC complex to mediate regulation of mRNA translation by targeting 3’UTR. Non-canonical mechanisms involve targeting 5’UTR or ORF, as well as transport back into the nucleus to regulate gene expression. .................................................................................................................... 84 Doctoral Thesis Patricia de la Cruz Ojeda 42 Figure 5. Impact of cellular miRNAs involved in Sorafenib resistance in hallmarks of cancers. Adapted from [115,116]. ...................................................... 85 Figure 6. Extracellular vesicles (EVs) classification according to their origin into apoptotic bodies (50-5000 nm), microvesicles (100-1000 nm) and exosomes (30-150 nm). Apoptotic bodies originate from membrane blebs in apoptotic cells after cell shrinkage. Therefore, they might contain functional organelles and cell debris, RNA, DNA or even chromatin. Microvesicles originate from membrane budding. During these EVs biogenesis several membrane curvature inducers participate, as lipids and calcium-related enzymes, including contraction of the actomyosin ring. The endosomal sorting complex required for transport (ESCRT) participates in vesicle fission. They include RNA, lipids, proteins, tetraspanins and biomarkers of the cell of origin. Exosomes originate from intraluminal vesicles (ILVs) that accumulates in endosomes forming multivesicular bodies (MVBs) that later fuse with the membrane to release the vesicles. Cargo sorting might happen in an ESCRT-dependent or independent pathway. Exosomes carry RNA, lipids, proteins and are highly enriched in tetraspanins, more than microvesicles. ............................................................................................................... 94 Figure 7. Structures of CDs. (A). Structures of α-, β- and δ-CD (left), 3D view of βCD (upper-right) and schematic representation of CD basket-shape architecture (lower right), with indication of the height, and average internal and external diameters for the three commercially available representatives. (B). Molecular structure of paCDs ADM70 and AMC6. ................................................................ 110 Figure 8. Liquid biopsy profile assessed in this PhD project. Circulating tumor cells (CTCs), circulating miRNAs, extracellular vesicles (EVs) and EVs derived miRNAs might be useful for determining patient prognosis, tumor progression and recurrence, as well as they could serve as tools for treatment choice in the clinical setting. ............................................................................................................ 113 Figure 9. Diagram showing protocol of EV isolation by differential centrifugation. ........................................................................................................... 129 Doctoral Thesis Patricia de la Cruz Ojeda 43 Figure 10. Library preparation and sequencing workflow following QuantSeq 3’mRNA-Seq Library Prep Kit forward (FWD) with dual indices set B1 from Lexogen and Illumina protocols. ........................................................................... 133 Figure 11. (A) Representative images of CECs immunofluorescence and (B) Negative control of immunomagnetic beads. CD45+ blood cells were nucleated cells (blue) with positive red fluorescence (arrowhead). Individual CECs were defined as colocalization of one nucleus (blue) and cytokeratin-green fluorescence (green) (arrow). Clustered CECs were recognized as grouped CECs (dotted arrow). ........................................................................................................... 139 Figure 12. Diagram showing gating strategy of CECs samples labelled with proliferation, apoptosis, epithelial and blood cell markers. CECs were identified as singlets positive for cytokeratin and negative for CD45 markers. This population was further used for proliferation and death assessments. ... 142 Figure 13. Synthesis of paCDs ADM70 and AMC6. .......................................... 144 Figure 14. Proliferation status (A) and apoptosis levels (B) in CECs at baseline (before treatments) in healthy subjects and HCC patients at intermediate (BCLC-B) and advanced stages (BCLC-C). Ki67 was used as a marker of proliferation, and caspase-3 activation was representative of apoptotic cell death. Fluorescence values were normalized to the number of events detected by flow cytometry. *p ≤ 0.05 between healthy subjects and HCC patients. Multiple comparison test statistics are expressed with lower case a–b. Groups with different letter indicate statistical differences p ≤ 0.05. ........................................ 173 Figure 15. Proliferation status in CECs induced by Sorafenib, Regorafenib, Lenvatinib, Cabozantinib or Doxorubicin treatment in all subjects included in the study (A) and separated by disease condition (B). Fluorescence values were normalized to the number of events detected by flow cytometry, and to control CECs. *p ≤0.05, **p ≤0.01, and ****p ≤ 0.0001 between control and treatment. Multiple comparison test statistics are expressed with lower case a–b. Groups with different letter indicate statistical differences p ≤ 0.05. ............................... 174 Doctoral Thesis Patricia de la Cruz Ojeda 44 Figure 16. Apoptosis levels in CECs induced by Sorafenib, Regorafenib, Lenvatinib, Cabozantinib or Doxorubicin treatment in all subjects included in the study (A) and separated by disease condition (B). Fluorescence values were normalized to the number of events detected by flow cytometry, and to control CECs. **p ≤0.01, and ***p ≤ 0.0001 between control and treatment. Multiple comparison test statistics are expressed with lower case a–d Groups with different letter indicate statistical differences p ≤ 0.05. ........................................ 175 Figure 17. Anti-tumoral signaling induced by Sorafenib in HepG2 cells. Cell proliferation measured by BrdU incorporation (A), caspase-3/7 activation (B), cell migration (C) and invasion (D) were detected at 24 hours of treatment. Autophagy induction was assessed at 6 hours of Sorafenib treatment by LC3-II/I conversion (E). *p ≤0.05, and ***p ≤ 0.001, and ****p ≤ 0.0001 between control and Sorafenib. Multiple comparison test statistics are expressed with lower case a–b. Groups with different letter indicate statistical differences p ≤ 0.05. ................. 177 Figure 18. Dynamic light scattering (DLS) measurements of extracellular vesicles (EVs) obtained at 24 hours of Sorafenib treatment. Large (grey), small (orange) and very small (green) EVs from control (A) and Sorafenib (B) treated cells were characterized. ........................................................................................... 178 Figure 19. Characterization of EVs by size and protein expression. Size was measured by Nanoparticle Tracking Analysis (NTA) in large (A), small (B) and very small (C) EVs obtained at 6 and 24 hours of treatment. Expression of EVs markers and cellular contaminants in EVs and cell lysates obtained at 24 hours after Sorafenib treatment. Total lane protein content was used as the loading control (D). .................................................................................................................. 179 Figure 20. Characterization of EVs by cryo-EM. Representative images of small and very small EVs derived from HepG2 cells treated with Sorafenib at 6 and 24 hours (A). Size (B) and number (C) were quantified. *p ≤0.05, and ****p ≤ 0.0001 between control 6 hours and other conditions tested. Multiple comparison test statistics are expressed with lower case a–i. Groups with different letter indicate statistical differences p ≤ 0.05. .................................................................................. 180 Doctoral Thesis Patricia de la Cruz Ojeda 45 Figure 21. Anti-tumoral signaling induced by Sorafenib, Regorafenib, Lenvatinib and Cabozantinib in HepG2 cells. Cell proliferation measured by BrdU incorporation (A), and caspase-3/7 activation (B) were detected at 24 hours of treatment. ****p ≤ 0.0001 between control and treatments. Multiple comparison test statistics are expressed with lower case a–e. Groups with different letter indicate statistical differences p ≤ 0.05. ................................................................... 181 Figure 22. Dynamic light scattering (DLS) measurements of extracellular vesicles (EVs) obtained at 24 hours of TKI treatment. Large (grey), small (orange) and very small (green) EVs from Regorafenib (A), Lenvatinib (B), and Cabozantinib (C) treated cells were characterized. .............................................. 182 Figure 23. Characterization of EVs by size. Size was measured by Nanoparticle Tracking Analysis (NTA) in large (left panel), small (central panel) and very small (right panel) EVs obtained at 24 hours of Regorafenib (A), Lenvatinib (B) and Cabozantinib (C) treatment. ..................................................................................... 183 Figure 24. Characterization of EVs protein expression. Expression of EVs markers and cellular contaminants in EVs and cell lysates obtained at 24 hours after TKI treatment. Total lane protein content was used as the loading control (A). ............................................................................................................................... 184 Figure 25. Characterization of EVs by cryo-EM. Representative images of small and very small EVs derived from HepG2 cells treated with Sorafenib, Regorafenib, Lenvatinib and Cabozantinib (A). Size (B) and number (C) were quantified. **p ≤ 0.01, and ****p ≤ 0.0001 between control (small EVs) and other conditions studied. Multiple comparison test statistics are expressed with lower case a–e. Groups with different letter indicate statistical differences p ≤ 0.05. . 185 Figure 26. Heatmap showing hierarchical clustering of miRNA expression profiles in human primary hepatocytes and HepG2 cells treated with Sorafenib. ................................................................................................................... 186 Figure 27. miRNA expression profile of HepG2 cells, compared to primary human hepatocytes. (A) Volcano plot showing differential expression analysis. (B) Fold-change and corrected p-value statistics data of differentially expressed Doctoral Thesis Patricia de la Cruz Ojeda 46 miRNAs. (C) Gene regulatory network (GRN) showing target prediction. (D) Top-10 most significant Kyoto encyclopedia of genes and genomes (KEGG) pathway terms resulting from target prediction. Upregulated miRNAs are highlighted in red, whereas downregulated miRNAs are highlighted in green. ...................................................................................................................................... 187 Figure 28. miRNA expression profile of primary human hepatocytes treated with Sorafenib (24 hours). (A) Volcano plot showing differential expression analysis. (B) Fold-change and corrected p-value statistics data of differentially expressed miRNAs. (C) Gene regulatory network (GRN) showing target prediction. (D) Top-10 most significant Kyoto encyclopedia of genes and genomes (KEGG) pathway terms resulting from target prediction. Upregulated miRNAs are highlighted in red, whereas downregulated miRNAs are highlighted in green. ................................................................................................. 188 Figure 29. miRNA expression profile of HepG2 cells treated with Sorafenib (6 hours). (A) Volcano plot showing differential expression analysis. (B) Foldchange and corrected p-value statistics data of differentially expressed miRNAs. (C) Gene regulatory network (GRN) showing target prediction. (D) Top-10 most significant Kyoto encyclopedia of genes and genomes (KEGG) pathway terms resulting from target prediction. Upregulated miRNAs are highlighted in red, whereas downregulated miRNAs are highlighted in green. .............................. 189 Figure 30. miRNA expression profile of HepG2 cells treated with Sorafenib (24 hours). (A) Volcano plot showing differential expression analysis. (B) Foldchange and corrected p-value statistics data of differentially expressed miRNAs. (C) Gene regulatory network (GRN) showing target prediction. (D) Top-10 most significant Kyoto encyclopedia of genes and genomes (KEGG) pathway terms resulting from target prediction. Upregulated miRNAs are highlighted in red, whereas downregulated miRNAs are highlighted in green. .............................. 190 Figure 31. Validation of miRNA expression. Expression of down (A) and upregulated miRNAs (B) in Sorafenib treated HepG2 cells. Effectiveness of mimics (C) and anti-sense oligonucleotides (D) in downregulated or upregulated Doctoral Thesis Patricia de la Cruz Ojeda 47 miRNAs, respectively. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 between the control and miRNA tested. Multiple comparison test statistics are expressed with lower case a–d. Groups with different letter indicate statistical differences p ≤ 0.05. ........................................................................................................................... 191 Figure 32. Functional impact of miRNAs in proliferation (A, B) and cell death (C, D), using miRNA mimics (A and C) and anti-sense oligonucleotides (B and D) according to down or upregulation of miRNA by Sorafenib in HepG2 cells. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 between the transfection control and mimic or inhibitor tested. Multiple comparison test statistics are expressed with lower case a–c. Groups with different letter indicate statistical differences p ≤ 0.05. .................................................................................................... 192 Figure 33. Functional impact of miRNAs in cell migration (A, B) and invasion (C, D), using miRNA mimics (A and C) and anti-sense oligonucleotides (B and D) according to down or upregulation of miRNA by Sorafenib in HepG2 cells. Invasion was tested for the miRNA mimics and inhibitors that showed the upregulation of cell migration with p-value < 0.01, or those that downregulated cell migration more than 5%. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 between the transfection control and mimic or inhibitor tested. Multiple comparison test statistics are expressed with lower case a–e. Groups with different letter indicate statistical differences p ≤ 0.05. ........................................ 193 Figure 34. Bulk secretion of miRNAs into the extracellular space. (A) Ratio of miRNA expression between cell culture medium and cellular content at 6 and 24 hours. (B) Sorafenib induced expression of miRNAs in extracellular space at 6 hours, compared to control (C) Sorafenib induced expression of miRNAs in extracellular space at 24 hours, compared to control. **p ≤ 0.01, and ****p ≤ 0.0001 between the miRNA expression in the control and Sorafenib derived cell culture media. Multiple comparison test statistics are expressed with lower case a–c. Groups with different letter indicate statistical differences p ≤ 0.05. ................. 195 Figure 35. miRNA expression profile in large, small and very small EVs. miRNAs were evaluated at 6 (A) and 24 hours (B) after Sorafenib treatment. **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001 between the miRNA expression in the Doctoral Thesis Patricia de la Cruz Ojeda 48 control and Sorafenib derived EVs. Multiple comparison test statistics are expressed with lower case a–e. Groups with different letter indicate statistical differences p ≤ 0.05. .................................................................................................... 196 Figure 36. miRNA expression profile in large, small and very small EVs compared to cellular levels at 6 hours. miRNA expression was tested in control (A) and Sorafenib (B) conditions. **p ≤ 0.01, and ****p≤ 0.0001. Multiple comparison test statistics are expressed with lower case a–f. Groups with different letter indicate statistical differences p ≤ 0.05. ........................................ 196 Figure 37. miRNA expression profile in large, small and very small EVs compared to cellular levels at 24 hours. miRNA expression was tested in control (A) and Sorafenib (B) conditions. ns, non-significant; *p ≤0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001. Multiple comparison test statistics are expressed with lower case a–h. Groups with different letter indicate statistical differences p ≤ 0.05. .............................................................................................................................. 197 Figure 38. RNA-sequencing data of miR-122-5p downregulation in HepG2 cells showed increased plasma membrane related signaling. (A) Venn diagrams showing the mRNAs regulated upon miR-122-5p inhibition (I-miR- 122-5p) compared to the transfection control (TC). (B) Heatmap of genes regulated by miR-122-5p. (C) Fold-enrichment values of the top five most significantly enriched GO BP, MF, CC, and KEGG pathways. (D) Diagram showing the clustering of STRING analysis (non-significant). Experiments were carried out as three independent replicates. For I-miR-122-5p one replicate was excluded. ..................................................................................................................... 199 Figure 39. RNA-sequencing data of miR-200c-3p downregulation in HepG2 cells showed increased damage response mechanisms. (A) Venn diagrams showing the mRNAs regulated upon miR-200c-3p inhibition (I-miR-200c-3p) compared to the transfection control (TC). (B) Heatmap of genes regulated by miR-200c-3p. (C) Fold-enrichment values of the top five most significantly enriched GO BP, MF, CC, and KEGG pathways. (D) Top 10 significant hallmarks GSEA upregulated after I-miR-200c-3p. Plots were provided for the three most Doctoral Thesis Patricia de la Cruz Ojeda 49 enriched terms. (E) Diagram showing the clustering of STRING analysis. (F) Fold-enrichment values of the top two most significantly enriched terms in either the GO BP, MF, CC, or KEGG pathways in each STRING cluster. Experiments were carried out as three independent replicates. ................................................ 201 Figure 40. RNA-sequencing data of miR-505-5p downregulation in HepG2 cells showed increased ER response mechanisms. (A) Venn diagrams showing the mRNAs regulated upon miR-505-5p inhibition (I-miR-505-5p) compared to the transfection control (TC). (B) Heatmap of genes regulated by miR-505-5p. (C) Fold-enrichment values of the top five most significantly enriched GO BP, MF, CC, and KEGG pathways. (D) GSEA hallmark (non-significant) upregulated after I-miR-505-5p. Plots were provided for the three most enriched terms. (E) Diagram showing the clustering of STRING analysis. (F) Fold-enrichment values of the top two most significantly enriched terms in either the GO BP, MF, CC, or KEGG pathways in each STRING cluster. Experiments were carried out as three independent replicates. ............................................................................................. 203 Figure 41. RNA-sequencing data of miR-551a upregulation in HepG2 cells showed decreased development related signaling. (A) Venn diagrams showing the mRNAs regulated upon miR-551a mimics (M-miR-551a) compared to the transfection control (TC). (B) Heatmap of genes regulated by miR-551a. (C) Foldenrichment values of the top five most significantly enriched GO BP, MF, CC, and KEGG pathways. (D) Diagram showing the clustering of STRING analysis. (E) Fold-enrichment values of the top two most significantly enriched terms in either the GO BP, MF, CC, or KEGG pathways in each STRING cluster. Experiments were carried out as two independent replicates. ........................... 205 Figure 42. RNA-sequencing data of miR-27a-3p downregulation in HepG2 cells showed increased cell growth mechanisms. (A) Venn diagrams showing the mRNAs regulated upon miR-27a-3p inhibition (I-miR-27a-3p) compared to the transfection control (TC). (B) Heatmap of genes regulated by miR-27a-3p. (C) Fold-enrichment values of the top five most significantly enriched GO BP, MF, CC, and KEGG pathways. (D) Top 10 significant hallmarks GSEA upregulated after I-miR-27a-3p. Plots were provided for the three most enriched terms. (E) Doctoral Thesis Patricia de la Cruz Ojeda 56 Doctoral Thesis Patricia de la Cruz Ojeda 57 TABLE INDEX Table 1. Summary of literature review of techniques for isolation and enrichment of CTCs in peripheral blood. .............................................................. 79 Table 2. EVs isolation techniques based on density, size, ionization and affinity properties. A brief description of each method is provided. ............... 101 Table 3. miRNA expression during Sorafenib resistance and mechanisms involved in cells and EVs. miRNA targets are indicated within brackets. ... 104 Table 4. List of treatments used in this study, including formulation, reference and dosage. ................................................................................................................. 119 Table 5. List of primers used in miRNA PCR assays, including reference number and usage of the oligonucleotides for PCR analysis. ......................... 123 Table 6. List of mimics and inhibitors used in this study, including reference number and concentration used in functional studies...................................... 124 Table 7. List of antibodies used for Western Blot in this study. Isotypes, clones, as well as reference numbers and suppliers are indicated in the table. ............ 131 Table 8. Antibodies used in flow cytometric analysis of proliferative and apoptotic properties of CECs. Table includes information about lasers and filter configuration for each marker. ................................................................................ 141 Table 9. Calculations for the preparation of CDplexes using different N/P ratios. ........................................................................................................................... 145 Table 10. Comparison of demographic, epidemiologic and CECs counts data of healthy subjects (n=22) and total HCC patients (n=136) at baseline. Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution and as percentage (%, n) for categorical variables. Significant results (p<0.05) are shown in bold. Alanine aminotransferase, ALT; Aspartate aminotransferase, AST; Alkaline phosphatase, ALP; α-fetoprotein, AFP; Circulating epithelial cells, CECs; p-value, p. *cytokeratin+/nucleated cells. .. 152 Table 11. ROC analysis of baseline CECs, clusters and clustered CECs for HCC (yes). Significant results (p<0.05) are shown in bold. Area under the curve, AUC; Doctoral Thesis Patricia de la Cruz Ojeda 58 Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 153 Table 12. Risk evaluation of baseline CECs levels at baseline in presenting HCC (n=158). Data were analyzed using logistic regression models (Odds Ratio, OR) with 95% Confidence Intervals (CI). Significant results (p<0.05) are shown in bold. Circulating epithelial cells, CECs; p-value, p. *cytokeratin+/nucleated cells. ...................................................................................................................................... 154 Table 13. Comparison of baseline demographic, epidemiologic and CECs counts data of HCC patients according to BCLC stage. Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution and as percentage (%, n) for categorical variables. Significant results (p<0.05) are shown in bold. Alanine aminotransferase, ALT; Aspartate aminotransferase, AST; Alkaline phosphatase, ALP; α-fetoprotein, AFP; Circulating epithelial cells, CECs; Hepatitis C virus, HCV; Interferon, IFN; Non-alcoholic fatty liver disease, NAFLD; Performance status; PS; p-value, p; Transartherial chemoembolization, TACE. *cytokeratin+/nucleated cells. .................................................................... 155 Table 14. ROC analysis of baseline CECs, clusters and clustered CECs according to BCLC stage (n=136). Significant results (p<0.05) are shown in bold. Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ...................................... 159 Table 15. Risk evaluation of baseline CECs levels at baseline according to BCLC stage (n=136). Data were analyzed using logistic regression models (Odds Ratio, OR) with 95% Confidence Intervals (CI). Significant results (p<0.05) are shown in bold. Circulating epithelial cells, CECs; p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 159 Table 16. ROC analysis of baseline CECs, clusters and clustered CECs according to exitus (yes) and progression (yes) (n=136). Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 160 Doctoral Thesis Patricia de la Cruz Ojeda 59 Table 17. Baseline individual CECs, clusters and clustered CECs levels in naïve and previously treated patients (n=136). Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution. p-value, p *cytokeratin+/nucleated cells. ................................................................................. 161 Table 18. Comparison of CECs counts data of HCC patients treated with TACE, Sorafenib and Lenvatinib. Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution. Significant results (p<0.05) are shown in bold. Circulating epithelial cells, CECs; p-value, p; Transartherial chemoembolization, TACE. *cytokeratin+/nucleated cells. ............................... 162 Table 19. ROC analysis of baseline CECs, clusters and clustered CECs according to exitus (yes) and progression (yes) in HCC patients treated with TACE (n=73). Significant results (p<0.05) are shown in bold. Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ............................................................................. 163 Table 20. Individual CECs, clusters and clustered CECs levels before and 1 month after TACE (n=46). Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution. p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 164 Table 21. Risk evaluation of CECs levels at baseline in death and disease progression in HCC patients treated with TACE (n=73). Data were analyzed using Cox regression models (Hazard Ratio, HR) with 95% Confidence Intervals (CI). HR models were adjusted to prognostic factors Child-Pugh and BCLC stages. Significant results (p<0.05) are shown in bold. Circulating epithelial cells, CECs; ns, non-significant; p-value, p. *cytokeratin+/nucleated cells. ............... 164 Table 22. ROC analysis of baseline CECs, clusters and clustered CECs according to exitus (yes) and progression (yes) in BCLC-A patients treated with TACE (n=37). Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ................. 165 Table 23. Individual CECs, clusters and clustered CECs levels before and 1 month after TACE in BCLC-A patients (n=24). Data are expressed as median Doctoral Thesis Patricia de la Cruz Ojeda 60 [25th; 75th] for quantitative variables with non-normal distribution. p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 166 Table 24. ROC analysis of baseline CECs, clusters and clustered CECs according to exitus (yes) and progression (yes) in BCLC-B patients treated with TACE (n=36). Significant results (p<0.05) are shown in bold. Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ............................................................................. 166 Table 25. Individual CECs, clusters and clustered CECs levels before and 1 month after TACE in BCLC-B patients (n=22). Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution. p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 167 Table 26. Risk evaluation of CECs levels at baseline in death and disease progression in BCLC-B HCC patients treated with TACE (n=36). Data were analyzed using Cox regression models (Hazard Ratio, HR) with 95% Confidence Intervals (CI). HR models were adjusted to prognostic factor Child-Pugh stage. Significant results (p<0.05) are shown in bold. Circulating epithelial cells, CECs; ns, non-significant; p-value, p. *cytokeratin+/nucleated cells. ........................... 168 Table 27. ROC analysis of baseline CECs, clusters and clustered CECs according to exitus (yes) and progression (yes) in HCC patients treated with Sorafenib (n=34). Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ................. 169 Table 28. Individual CECs, clusters and clustered CECs levels before and 1 month after Sorafenib treatment (n=27). Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution. Significant results (p<0.05) are shown in bold. p-value, p. *cytokeratin+/nucleated cells. ............. 169 Table 29. Risk evaluation of time-dependent CECs levels in death and disease progression in HCC patients treated with Sorafenib (n=27). Data were analyzed using Cox regression models (Hazard Ratio, HR) with 95% Confidence Intervals (CI). HR models were adjusted to prognostic factors Child-Pugh, Performance Status (PS) and BCLC stages. Significant results (p<0.05) are shown in bold. Doctoral Thesis Patricia de la Cruz Ojeda 61 Circulating epithelial cells, CECs; ns, non-significant; p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 170 Table 30. ROC analysis of baseline CECs, clusters and clustered CECs according to exitus (yes) and progression (yes) in HCC patients treated with Lenvatinib (n=18). Area under the curve, AUC; Circulating epithelial cells, CECs, Confidence intervals, CI; p-value, p. *cytokeratin+/nucleated cells. ..... 170 Table 31. Individual CECs, clusters and clustered CECs levels before and 1 month after Lenvatinib treatment (n=14). Data are expressed as median [25th; 75th] for quantitative variables with non-normal distribution. p-value, p. *cytokeratin+/nucleated cells. ................................................................................. 171 Table 32. Summary of functional analysis with mimics and inhibitors and their impact on cell proliferation, apoptosis, migration and invasiveness............. 194 Table 33. Comparison of demographic and epidemiologic data of the study cohort (n=36), and the validation cohort (n=81). Alanine aminotransferase, ALT; Aspartate aminotransferase, AST; Alkaline phosphatase, ALP; α-fetoprotein, AFP; Gamma-glutamyl transferase, GGT. ............................................................. 220 Table 34. Risk evaluation of miRNA levels at baseline in disease progression (at 30 and 60 days) and death according to BCLC stage in the study cohort (n=36; BCLC-B n=9; BCLC-C n=27). Hazard Ratio models were adjusted to prognostic factors Child-Pugh and Performance Status (PS) stages. Hazard Ratio, HR; Confidence Intervals, CI; baseline miRNA value, miR; ns, non-significant; pvalue, p. ....................................................................................................................... 222 Table 35. Risk evaluation of miRNA time-dependent values upon Sorafenib treatment in disease progression (at 30 and 60 days) and death according to BCLC stage in the study cohort (n=36; BCLC-B n=9; BCLC-C n=27). Hazard Ratio models were adjusted to prognostic factors Child-Pugh and Performance Status (PS) stages. Hazard Ratio, HR; Confidence Intervals, CI; time-dependent miRNA value, miR; ns, non-significant; p-value, p. ............................................. 222 Table 36. Risk evaluation of miRNA levels at baseline in disease progression (at 30 and 60 days) and death according to BCLC stage in the validation cohort Doctoral Thesis Patricia de la Cruz Ojeda 62 (n=81; BCLC-B n=34; BCLC-C n=47). Hazard Ratio models were adjusted to prognostic factors Child-Pugh and Performance Status (PS) stages. Hazard Ratio, HR; Confidence Intervals, CI; baseline miRNA value, miR; p-value, p. ............ 223 Table 37. Risk evaluation of miRNA time-dependent values upon Sorafenib treatment in disease progression (at 30 and 60 days) and death according to BCLC stage in the validation cohort (n=81; BCLC-B n=34; BCLC-C n=47). Hazard Ratio models were adjusted to prognostic factors Child-Pugh and Performance Status (PS) stages. Hazard Ratio, HR; Confidence Intervals, CI; time-dependent miRNA value, miR; ns, non-significant; p-value, p. ................ 225 Doctoral Thesis Patricia de la Cruz Ojeda 63 1. 2. INTRODUCTION Doctoral Thesis Patricia de la Cruz Ojeda 64 Doctoral Thesis Patricia de la Cruz Ojeda 65 1. INTRODUCTION 1.1 Hepatocellular Carcinoma (HCC) 1.1.1 Incidence, epidemiology and natural history of HCC Liver cancer constitutes the sixth most common neoplasia, with 905,677 new cases per year. Incidence has been growing during the last twenty years, showing an estimated annual increase percentage of 1.61% in Spain (males) or up to 4.18% in the USA (males). Worldwide incidence is heterogenous, showing East Asia and Africa the highest incidence rates, followed by Europe and North America (Figure 1). Liver cancer is present in major proportion in male than females, accounting for 14.1% and 5.2% incidence worldwide, respectively. HCC was responsible for the death of 3,882 of males (7.5%) and 1,673 females (2.1%) in 2020 in Spain, and represents the third leading cause of cancer-related death worldwide (830,180 patients, 8.7%) [1]. Therefore, liver cancer represents an international health concern. Figure 1. World map showing incidence and epidemiological trends of HCC. 2020 Worldwide Age-standardized HCC Incidence Rates, both sexes, all ages. Figure adapted from [1]. HCC is the most frequent primary liver cancer, followed by cholangiocarcinoma. It usually arises upon chronic liver damage leading to Doctoral Thesis Patricia de la Cruz Ojeda 72 Figure 2. BCLC staging system. Very early stages (BCLC-0) and early stages (BCLC-A) undergo ablation, liver resection or transplantation curative treatments. If not feasible, patients should migrate to TACE. Patients with multinodular tumors but preserved liver function should undergo TACE. Whenever this is not possible, treatment strategies must migrate to systemic therapy. Advanced stages are characterized by the presence of portal invasion and/or extrahepatic metastasis. Systemic therapies include immunotherapy, tyrosine kinase inhibitors and clinical trials. For patients with end stage liver disease and Performance Status (PS) 3-4, best supportive care should be provided. 1.2 Molecular mechanisms of Sorafenib in liver cancer Sorafenib targets TK Receptors (TKRs) including the VEGF Receptor (VEGFR) 2, VEGFR 3, Platelet‐Derived Growth Factor Receptor‐β (PDGFR‐β), Flt3 and c‐Kit, and components of the Raf/MEK/Extracellular Signal‐Regulated Kinase (ERK) signaling pathway [48]. The mechanism by which Sorafenib induces apoptosis is not fully elucidated, and the effectiveness and adverse events are related to the dose used. The mean trough Sorafenib concentration in patients under Sorafenib monotherapy at the recommended dose (400 mg/12 hours) is Doctoral Thesis Patricia de la Cruz Ojeda 73 4.3 ± 2.5 mg/L in blood [49]. The commonly used dose in in vitro studies ranges 0-10 µM. It has been well stablished that Sorafenib decreases cell proliferation in diverse experimental HCC models blocking the ERK pathway as well as p53 signaling [50,51]. Sorafenib not only targets tyrosine kinases (TKs), but also is able to activate several phosphatases, including SHatterProof 2 (SHP2). Activation of SHP2 leads to reduced Signal Transducer and Activator of Transcription-3 (STAT3) signaling by promoting Tyr705P-STAT3 dephosphorylation. As a consequence, susceptibility to Tumor necrosis factor–Related Apoptosis- Inducing Ligand (TRAIL) induced apoptosis is increased, showing also decreased expression of Mcl-1 [52]. Sorafenib induced cell death relies on early induction of Endoplasmic Reticulum (ER) stress. In particular, Sorafenib at the effective dose of 10 µM induces sustained ER stress, with upregulation of Ser51P‐Eukaryotic Translation Initiation Factor 2α (eIF2α)/eIF2α ratio, C/EBP Homologous Protein (CHOP), IRE1α, and spliced XBP1. This leads to an early pro-survival signaling characterized by autophagy induction and upregulation of tBid, BimEL, Beclin‐ 1, Bcl‐xL and Bcl‐2 protein expression, as well as a transient increase of Akt (Protein Kinase B, PKB), c-Jun N-terminal Kinase (JNK) and Forkhead bOX O (FOXO) signaling, and decreased mammalian Target Of Rapamycin (mTOR) pathway. Sustained ER stress leads to autophagy-to-apoptosis shift mediated by Bim, but not Bax and Bak, with consequent caspase-3 activation [53]. Mitochondrial dysfunction plays a relevant role during the induction of cell death by TKIs. Disruption of the 5' AMP-activated Protein Kinase (AMPK)- Peroxisome Proliferator–Activated Receptor γ Coactivator-1- α (PGC1-α) axis during oxidative and nitrosative damage is partially entailed in this [54]. Related to oxidative and nitrosative damage is nuclear factor E2-related factor 2 (Nrf2), that is frequently associated with treatment resistance. Sorafenib downregulates Nrf2-encoded genes such as thioredoxin-1 in vitro and in vivo experimental HCC models [55]. Together with reduced proliferation and increased cell death, Sorafenib exerts its anti-tumoral properties by decreasing migration and invasion by reducing the expression of matrix metalloproteinases (MMP) [56]. Doctoral Thesis Patricia de la Cruz Ojeda 74 Resistance to Sorafenib treatment is a complex multifactorial process. Several factors such as epigenetic regulation, non-coding RNAs (ncRNAs), autophagy, ferroptosis, membrane transporters, extracellular vesicles, hypoxia, tumor microenvironment, and signaling pathways like Akt-ERK, among other factors, have been shown to be responsible for therapy resistance. Therefore, they constitute targetable markers for therapeutic strategies development [57]. Their connections with ncRNAs will be reviewed later on. 1.3 Genetic landscape of HCC 1.3.1 Genetic predisposition to HCC Syndromes such as hemochromatosis, Wilson disease, cutanea tarda, α1 anti-trypsin deficiency, glycogen storage diseases, among others, can promote adenomatosis that can ultimately lead to HCC in the absence of cirrhosis [58]. On the other hand, numerous studies have identified Single Nucleotide Polymorphisms (SNPs) to be associated with HCC as representative mechanism of multifactorial predisposition to HCC. They are able to modulate liver diseases at different levels, including susceptibility to injury and its progression to cirrhosis, malignant transformation and tumor progression. These SNPs participate in oxidative stress and detoxifying systems, iron metabolism, inflammation, DNA synthesis and repair, cell death and proliferation, and treatment response [59]. For instance, SNPs in Nitric Oxide Synthase type 3 (NOS3), Angiopoietin 2 (ANGPT2), ATP-Binding Cassette subfamily G member 2 (ABCG2), VEGF-A and -C and Solute Carrier Family 15 Member 2 (SLC15A2) have been associated with response to Sorafenib therapy [60-63]. 1.3.2 Mechanisms of malignant transformation in HCC HCC develops in a multi-step process starting from Low-Grade Dysplastic Nodules (LGDN) to High-Grade Dysplastic Nodules (HGDN), evolving to early HCC that might progress to advanced HCC [58]. Carcinogenesis follows sequential steps involving inactivation of tumor suppressors genes, telomerase Doctoral Thesis Patricia de la Cruz Ojeda 75 and oncogene activation, overexpression or sustained activation of cell proliferating signaling, and cell dedifferentiation [64]. HCC tumors are highly heterogenous showing multiple somatic mutations including by-stander and driver genes. As stated above, genomic landscape of HCC involves inactivation of tumor suppressor genes and activation of oncogenes. In particular, telomere maintenance constitutes a crucial process during hepatocarcinogenesis. Telomeres are protective repeat sequences located at the end of the chromosomes, maintained by telomerase. As telomerase is not expressed in human mature livers, chronic liver damage induces telomere shortening, progression of tissue injury and, ultimately, cirrhosis [65]. Contrarily, reactivation of telomerase is widely detected in malignant transformation during hepatocarcinogenesis [66]. The activation of telomerase is present in almost 90% of HCCs. Regarding the WNT/β-catenin pathway, CTNNB1 gene shows activating mutations and, less frequently, inactivating mutations of oncosuppressors such as AXIN1 and Adenomatous Polyposis Coli (APC). Other oncosuppressors such as TP53 or RetinoBlastoma (RB1) altering cell cycle control and cell dedifferentiation are also predominantly encountered in HCC. The resistance to oxidative stress through activation of NFE2L2 (Nrf2) or inactivation of its negative regulator KEAP1 also constitutes a gene signature in HCC. Inactivating mutations of regulators of chromatin structure such as epigenetic modifiers ARID1A or ARID2, or in histone methylation genes impact DNA transcription. Finally, pro-survival PhosphoInositide 3-Kinase (PI3K)/Akt/mTOR and Rat Sarcoma Virus (RAS) pathways tend to be augmented. It should be mentioned that mutations in the RAS gene family are rare in HCC [58,67]. The long period of chronic inflammatory disease that fosters the accumulation of genetic and epigenetic defects is related to the increased heterogeneity of HCC. 1.4 Liquid biopsy The term liquid biopsy refers to the assessment of tumor components released from a solid tumor into biological fluids, such as blood, urine or saliva. Tumor components include Circulating Tumor nucleic acids (ctDNA and Doctoral Thesis Patricia de la Cruz Ojeda 76 RNAs), Circulating Tumor Cells (CTCs) and Extracellular Vesicles (EVs) [68]. Liquid biopsy provides non-invasive techniques for cancer diagnosis, monitoring tumor heterogeneity and treatment response. As a personalized medicine tool, it can be used for cancer screening and prognosis. Nonetheless, this approach has several drawbacks. Most importantly, there is a lack of standardization in isolation and characterization procedures. Also, very sensitive and specific methods are required to avoid loss of material, that is usually present in low quantities, and to avoid false negative or positive results [69]. Given the importance of CTCs, RNAs and EVs in this PhD project, these three items are going to be reviewed here. 1.4.1 Circulating tumor cells (CTCs) 1.4.1.1 The biology of CTCs CTCs are considered to be the major cause of metastases and derive from tumor cells released from the primary tumor that enter the circulation and travel to distant organs to give rise to secondary tumors. Despite the fact that millions of CTCs could be daily released from tumors, only a few number of them will survive and engraft at distant locations [70]. The clearance of CTCs depends on physical stress in the bloodstream, resistance to detachment induced cell death (anoikis), immune surveillance and the lack of growth factors [71]. CTCs can travel as individual cells or in the form of cell clusters. These clusters do not arise from aggregation during circulation but instead they come from oligoclonal cells that shed together from the primary tumor [72]. Clusters are usually associated with poor prognosis because of their higher aggressiveness and increased risk of metastasis [72,73]. The Epithelial-to-Mesenchymal Transition (EMT) is the process by which tumor cells lose their intercellular adhesions and acquire motility and invasive properties. This explains how tumor cells change their phenotype to metastasize throughout the blood or the lymphatic system. This multi-step process involves the downregulation of epithelial proteins such as Epithelial Cellular Adhesion Doctoral Thesis Patricia de la Cruz Ojeda 77 Molecule (EpCAM), E-cadherin, claudin or cytokeratin, and the upregulation of mesenchymal proteins, like N-cadherin, fibronectin or vimentin. Several transcription factors are involved in this process, also serving as biomarkers of EMT. Among them, Snail 1, Snail 2 (Slug), ZEB1, Twist, TCF4, and Forkhead box protein C2 (FOXC2) are of great importance. Other signaling pathways considered to be pro-survival, like Mitogen-Activated Protein Kinase (MAPK), PI3K, Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB) or Wnt/β-catenin might also induce EMT [74]. Snail 1 contributes to transmigration by inducing the expression of MMP1 and MMP2 [75]. Cells that intravasate into the bloodstream are subjected to shear stress that could end up in anoikis. However, CTCs that are able to interact with cells of the blood microenvironment, such as neutrophils, platelets, macrophages, Myeloid-Derived Suppressor Cells (MDSCs), or Cancer-Associated Fibroblasts (CAFs), will evade the immune system and survive [76,77]. As a matter of fact, the presence of clusters of CTCs associated with white blood cells constitutes an independent prognosis factor in HCC, leading to poor disease outcome [78]. The EMT phenotype of CTCs of epithelial origin is characterized by its dynamism, heterogeneity and plasticity. In fact, it can be reversed to the epithelial phenotype during the Mesenchymal-to-Epithelial Transition (MET), which is necessary for extravasation and distant engraftment. Although mechanisms have not been fully elucidated, the MET model seems to be the most plausible theory [79,80]. Therefore, CTCs can be found in different states in the bloodstream: epithelial CTCs, EMT CTCs, mesenchymal CTCs, and/or a combination of them (Figure 3). In lung cancer, the presence of epithelial and EMT CTCs has been related with tumor size, whereas mesenchymal CTCs were related to disease progression and metastasis [81]. These different phenotypes and their clinical significance have been investigated in HCC. The total number of CTCs regardless of phenotype earn the greatest diagnostic value in HCC patients. The increased expression of mesenchymal markers in CTCs appears in advanced stages of HCC, suggesting that changes to more aggressive phenotypes correlate with disease progression [82]. Doctoral Thesis Patricia de la Cruz Ojeda 78 Eventually, CTCs need to extravasate to promote the growth of secondary tumors at distant tissues. This process involves transendothelial migration, which requires cooperation with immune cells to mediate the permeability of the capillary walls. CTCs adhere to the epithelium through adhesion molecules such as integrins or cadherins. For that, cancer cells or bound leukocytes induce the expression of E-selectin in the endothelium [71]. Extravasation does not occur randomly, as CTCs display metastatic tropism. For instance, the heterogeneity of CTCs displaying different receptors or transcription factors, like Twist or Snail 1, contributes to the organotropism of breast cancer [83]. Figure 3. General mechanisms of CTC dissemination in peripheral blood. Cancer cells from primary tumors that undergo EMT are able intravasate into the bloodstream, turning into CTCs. CTCs might display epithelial, EMT of mesenchymal phenotype. Cells might undergo cell death upon loss of adhesion (anoikis). In order to survive, CTCs might associate with blood cells (neutrophils, platelets, macrophages or myeloid cells), or cancer-associated fibroblast. Reverse MET is required for distant growth and metastasis. Doctoral Thesis Patricia de la Cruz Ojeda 79 1.4.1.2 An overview of enrichment techniques of CTCs Procedures for the enrichment and isolation of CTCs must confront their rarity in circulation. CTCs counts depend on their extravasation and intravasation rates, and their average lifetime, under the assumption of constant concentration through the bloodstream. However, it should be noticed that CTCs counts may be underestimated as, for instance, in the tumor vasculature counts could be larger [84]. Physicochemical and biological properties of CTCs are used during isolation techniques to enrich this population. Most of them rely on three steps: capture and enrichment, detection and identification, and release to perform further applications [76]. The following table summarizes several techniques described in the literature for the isolation of CTCs and their main characteristics: Table 1. Summary of literature review of techniques for isolation and enrichment of CTCs in peripheral blood. Property Technique Brief description Reference Size and CD45 absence CTC-iChip Microfluidic hydrodynamic size separation and depletion of white blood cells [85] Size Isolation by Size of Epithelial Tumor cells (ISET) Filtration through polycarbonate TRACK-ETCH-type membranes [86] Flexible Micro spring Array (FMSA) Microfiltration through array device [87] OncoQuick density gradient centrifugation Density centrifugation with new agent [88] RUBYchip™ Microfluidic system that separated CTCs based on their size and deformability [89] Doctoral Thesis Patricia de la Cruz Ojeda 80 RareCyte® Sample separation by density gradient with the AccuCyte® sample preparation system and identification with the CyteFinder instrument [90] Lab-on-a-disc Movement of CTCs under centrifugal forces [91] EpCAM (+EMT) CanPatrol™ Size filtration coupled to mRNAs in situ analysis of EpCAM, cytokeratin, vimentin and Twist, and CD45 [92] EpCAM CellSearch® Immunomagnetic enrichment of epithelial cells with EpCAM antibodies, coupled to immunofluorescent identification of cytokeratin positive cells and CD45 negative cells. [93] MagSweeper Magnetic rod that captures CTCs with paramagnetic beads functionalized with antibodies against EpCAM [94] CTC-Chip Microchips with antibody EpCAM- coated microposts [95] Isoflux™ Immunomagnetic enrichment of epithelial cells with EpCAM antibodies, coupled to immunofluorescent identification of cytokeratin positive cells and CD45 negative cells. [96,97] Electrophoretic mobility ApoStream™ device CTCs display distinct morphologic and electrical conductivity properties that allow for their separation with dielectrophoretic field-flow fractionation technology [98] Doctoral Thesis Patricia de la Cruz Ojeda 81 Method selection should be based on the application needed and available resources. While techniques based on size seem to be highly heterogenous and dependent on high quantities of blood samples, they usually provide viable cells suitable for cell culture. On the other hand, methods based on EpCAM expression and microfluidic system have been developed more recently and provide more homogenous data using automatized procedures. CanPatrol™ provides genetic information of CTCs but relies on sample fixation. Thus, our chose of Isoflux™ was based on the usage of immunomagnetic beads coupled to EpCAM, Epidermal Growth Factor Receptor (EGFR), vimentin, N-cadherin and Twist to enhance CTC enrichment of rare cells, automatization, and obtaining of viable cells. Nonetheless, it should be taken into consideration that cell counting is based on immunofluorescent staining using an epithelial cell marker (cytokeratin + cells) and a non-immune cell marker (CD45 - cells) in the overall enriched cell population. Thus, for the purpose of this thesis we will use the term circulating epithelial cell (CEC), as no further confirmation of the tumor origin was carried out. 1.4.1.3 The clinical significance of CTCs in HCC CTCs might be used as surrogate biomarkers for diagnosis, prognosis, and therapy monitoring in liver cancer. They have been widely correlated with response to liver resection. Pre-operative levels of CTCs and Neutrophil- Lymphocyte Ratio (NLR) correlate with reduced Overall Survival (OS) and clinicopathological characteristics of HCC patients, such as BCLC stage or the number of tumors. However, recurrence risk was not assessed in this study [99]. In bigger cohorts, CTCs might be related to microvascular invasion, and their presence confirm the utility of large resection margins to prevent recurrence [100]. From the molecular point of view, the presence of EMT or mesenchymal markers in CTCs expressing Nanog seems to be fundamental for HCC recurrence after surgery, being correlated with BCLC stage, vascular invasion, tumor size and HBV [101]. CTC counts also determine recurrence after liver transplantation, Doctoral Thesis Patricia de la Cruz Ojeda 88 mimics are able to increase apoptosis in cellular models of HCC [136]. In a similar way, miR-365 downregulation is also related to Rac1 expression, controlling stemness, controlling the Janus Kinase (JAK)/STAT3 pathway [137]. 1.4.2.2.2 Autophagy Autophagy shows a dual role in cancer, being anti-tumoral during early stages and promoting tumor progression later on. In particular, autophagy is induced in Sorafenib resistant cells. In these cells, miR-23b-3p is downregulated that increases the expression of its target Autophagy Related 12 (ATG12) [138]. Mechanistically, lncRNA SNHG16 sponges miR-23b-3p leading to increased ATG12 expression and autophagy [139]. Also, upregulation of miR-25 induces autophagy by targeting F-BoX and WD repeat domain containing 7 protein (FBXW7) to induce therapy resistance [140]. Downregulation of miR-204 upregulates ATG3 and autophagy leading to therapy resistance. miRNA levels are controlled by lncRNA NEAT1, whose expression is increased in HCC [141]. Furthermore, miR-142-3p downregulation is associated with ATG5 and ATG16L1 upregulation in Sorafenib resistant cells [142]. Contrarily, other reporters showed decreased autophagy during Sorafenib resistance. In this sense, Sorafenib-related miR-21 upregulation reduces PTEN that activates Akt signaling and reduces autophagy rates [143]. 1.4.2.2.3 Cell death The regulation of anti-apoptotic and pro-apoptotic Bcl-2 family members is fundamental for the induction of cell death by Sorafenib. miRNAs could also be directly or indirectly involved in this process. miR-221 directly regulates caspase-3 [144]. miR-106b-5p is upregulated in HCC involving reduced expression of cell cycle regulator BTG Anti-Proliferation Factor 3 (BTG3) leading to Sorafenib resistance. Negative regulation of BTG3 positively impacts Bcl-xL [145]. Instead, let-7c and let-7g target Bcl-xL increasing apoptosis [146]. Another example is miR-518d-5p, that regulates mitochondrial functionality and Doctoral Thesis Patricia de la Cruz Ojeda 89 Sorafenib resistance by targeting c-Jun/PUMA signaling [147]. miR-29a maintains stemness properties in liver Initiating Tumor Cells (I-TCs). This miRNA is frequently downregulated in EpCAM+ or CD133+ cells, promoting Sorafenib resistance by increasing the levels of the anti-apoptotic Bcl-2 protein [148]. Mcl-1, another anti-apoptotic protein that prevents cytochrome c release from mitochondria, seems to be upregulated in HBV induced HCC, as a consequence of miR-193b downregulation [149]. In another context, downregulation of the liver specific miR-122 has been related to apoptosis resistance by regulating Serpin B3 after Sorafenib treatment, a negative regulator of JNK and apoptosis. This also favors the expression of stemness markers such as EpCAM or CD133 [150]. Apart from apoptosis, it has been demonstrated that Sorafenib also promotes cell death dependent on iron-induced lipid peroxidation or ferroptosis, that can be interconnected with apoptosis. Upregulation of miR-23a-3p by the transcription factor ETS1 could be inhibiting Sorafenib mediated ferroptosis by diminishing the expression level of Acyl-CoA Synthetase Long chain family member 4 (ACSL4), an enzyme involved in phospholipid biosynthesis [151]. 1.4.2.2.4 Cell cycle Cell cycle arrest is required for successful therapy response. Downregulation of cyclin E1 by miR-10b-3p appears to be relevant for Sorafenibinduced cell death [152]. Cell cycle progression is controlled by downregulation of miR-140-5p, that is sponged by MALAT1, and promotes expression of its target Aurora-A, a mitotic kinase, leading to Sorafenib resistance. In concordance, expression of MALAT1 and Aurora-A are positively correlated in HCC tissues but negatively correlated with miR-140-5p expression [153]. 1.4.2.2.5 EMT EMT process is required for cell migration and invasion during tumor progression. Sorafenib resistant cells display increased miR-125b-5p expression that negatively regulated ataxin-1. Either miR-125b-5p or inhibition of ataxin-1 Doctoral Thesis Patricia de la Cruz Ojeda 90 increase the pro-metastatic phenotype of liver cancer cells by inducing EMT. Indeed, low expression levels of ataxin-1 correlated with shorter OS [154]. Upstream regulation of miRNAs by sponging lncRNAs constitutes an additional level of regulation of gene expression. lncRNA LINC01089 (LIMT) has been identified as a tumor suppressor ncRNA whose downregulation promotes Sorafenib resistance. Mechanistically, LIMT downregulation leads to miR-665 augmentation, which promotes EMT [155]. The pro-tumoral H19 lncRNA positively regulates miR-675 to decrease Sorafenib sensitivity and to increase EMT [156]. From another point of view, cell differentiation status could be also related to Sorafenib treatment. In particular, increased expression of miR-93 promotes CSC like features. In fact, downregulation of this miRNA in tumors constitutes a biomarker of good prognosis [157]. 1.4.2.2.6 Metabolic rewiring Alterations in metabolism are often related to therapy resistance in cancer. Higher rates of aerobic glycolysis partially due to the downregulation of miR- 30a-5p and upregulation of its target Cardiotrophin-Like Cytokine Factor 1 (CLCF1) and mTOR activation are observed in Sorafenib-resistant liver cancer cells. This axis has also been validated in tumor vs non-tumor samples of patients with HCC, showing pro-tumoral functions [158]. Curiously, miR-30a has also been related to autophagy modulation, by targeting Beclin-1. In concordance with the above-mentioned study, downregulation of miR-30a displays protumoral functions by augmenting autophagy [159,160]. Similar to miR-30a-5p, miR-374b downregulation is found in Sorafenib resistant cell lines that indirectly regulates Pyruvate Kinase (PKM2) by targeting the HnRNPA1 ribonucleoprotein that controls PKM2 alternative splicing [161]. Moreover, mitochondrial bioenergetics might be also affected during Sorafenib resistance. As a matter of fact, the Adenine Nucleotide Translocase 2 (ANT2) associates with low expression of miR-137 and high expression of the stem cell markers CD133 and EpCAM, contributing to higher invasive properties [162]. Doctoral Thesis Patricia de la Cruz Ojeda 91 The metabolic reprogramming is necessary for CSC development and maintenance, being miR-122 involved in this process. According to previous studies about the role of miR-122 in different contexts, its downregulation contributes to treatment resistance. In this case, downregulated miR-122 increases the expression of Pyruvate Dehydrogenase Kinase 4 (PDK4), which is indispensable for glycolysis allowing CSC maintenance [163]. 1.4.2.2.7 Oxidative metabolism Resistance to oxidative stress through activation of Nrf2 signaling constitutes a hallmark of liver cancer. In this sense, Nrf2 involves a major cluster in the exome sequencing of HCC [164]. The axis FOXD2‐AS1/miR‐150‐ 5p/TransMEMbrane Protein 9 (TMEM9) is involved in Nrf2 regulation in Sorafenib resistant cells. Whereas lncRNA FOXD2‐AS1 and TMEM9, a lysosomal proton-transporting ATPase, are downregulated during resistance, miR-150-5p is upregulated, and their restoration increases Sorafenib sensitivity by modulating Nrf2 [165]. Sorafenib is primarily metabolized in the liver by oxidation of CYtochrome P450 3A4 (CYP3A4) and glucuronidation by UGD GlucuronosylTransferase 1A9 (UGT1A9). UGT19A is associated with better prognosis and it has been associated with reduced expression of miR-200a-3p and miR-183-5p [166]. Genes from CYP family might be transcriptionally regulated by the Pregnenolone X Receptor (PXR). miR-140-3p is related to higher half-life of Sorafenib and increased sensitivity by targeting PXR, therefore altering its metabolism [167]. 1.4.2.2.8 Hypoxia Hypoxia-related signaling has a great impact in Sorafenib responsiveness in cancer cells. Hypoxia Inducible Factor 1α (HIF-1α) is also able to induce rewiring of cell metabolism impacting different catabolic and anabolic pathways that alter treatment response [168]. Downregulation of miR-16 in resistant cells Doctoral Thesis Patricia de la Cruz Ojeda 92 contributes to stabilization of HIF-1α by 14-3-3η. In fact, high expression levels of 14-3-3η in HCC tissues correlate with poor prognosis [169]. Hypoxia has been highlighted as one of the mechanisms involved in Sorafenib resistance [170]. One plausible mechanism is by controlling the Androgen Receptor (AR), that has shown to be involved in HCC progression. Hypoxia diminishes AR expression and increases stemness regulating SRY-BOX transcription factor 9 (SOX9) [171]. The connections among hypoxia, AR and SOX9 are mediated by miR-520f-3p. In particular, AR regulates the expression of this miRNA to regulate SOX9 mRNA at the post-transcriptional level. As a consequence, high AR expression and upregulation of miR-520f-3p are related to higher survival benefits [171]. Furthermore, miRNA could directly regulate HIF-1α. miR-338-3p targets HIF-1α and, therefore, regulates downstream signaling including MultiDrug Resistance protein 1 (MDR1) or VEGF, controlling Sorafenib sensitivity [172]. 1.4.2.3 Circulating miRNAs as prognostic biomarkers of Sorafenib response in HCC There are no consolidated biomarkers of HCC prognosis or treatment response in patients [26,173]. Several studies have tried to identify miRNA signatures that could help in deciphering patient outcome in HCC using data repositories and omics approaches. For example, miR-326, miR-30d-5p, let-7c-5p, miR-5003-3p, miR-760, and miR-7-5p have been identified as a signature related to immune infiltration [174]. Although these studies provide great information and contribute to the general knowledge, validation experiments with robust statistics are needed in patient cohorts [174-177]. Many other studies have tried to understand mechanisms of carcinogenesis and progression based on the interaction of miRNAs with endogenous lncRNAs or circular RNAs (circRNAs) [178]. Nonetheless, most of them have been carried out in tumor samples, in vitro or in vivo, insisting on the need of validated data in independent cohorts. Few studies in the literature have addressed the expression of miRNAs in liquid biopsy during Sorafenib response. It has been described previously that Doctoral Thesis Patricia de la Cruz Ojeda 93 several miRNAs have been tested in serum or plasma of HCC patients treated with Sorafenib. For instance, low levels of circulating miR-221 might be related to Sorafenib response, as this miRNA controls caspase-3 [144]. Similarly, miR- 518d-5p negatively regulates apoptosis. Therefore, high circulating levels of miR- 518d-5p can be found in HCC patients, and they correlate with reduced Sorafenib response [147]. Related to cell cycle, patients displaying high levels of circulating miR-10b-3p show longer OS [152]. Circulating levels of autophagy-related miR- 23b-3p have been demonstrated to be downregulated in HCC patients compared to healthy controls, which display variable levels during Sorafenib treatment. [179]. In another study, miR-30d has been shown to be upregulated in the serum of patients with good response to Sorafenib [180]. However, these studies do not perform risk analysis, nor validate the results, that could allow to deepen its influence in survival or progression. 1.4.3 Extracellular vesicles EVs are membrane-contained vesicles able to transfer information to recipient cells. They have been traditionally classified into three groups according to their origin, role and composition into Apoptotic Bodies (ABs), MicroVesicles (MVs) or ectosomes, and exosomes (Figure 6). ABs are released from cells in apoptosis generated by plasma blebbing. Also, MVs are derived from the plasma membrane. On the other hand, exosomes generate from intracellular pathways, in which Intraluminal Vesicles (ILVs) are released after fusion of Multivesicular Bodies (MVBs) with the plasma membrane. Because of these different origins, EVs are highly heterogeneous and depend on the cell origin as well as environmental conditions [181]. Doctoral Thesis Patricia de la Cruz Ojeda 94 Figure 6. Extracellular vesicles (EVs) classification according to their origin into apoptotic bodies (50-5000 nm), microvesicles (100-1000 nm) and exosomes (30-150 nm). Apoptotic bodies originate from membrane blebs in apoptotic cells after cell shrinkage. Therefore, they might contain functional organelles and cell debris, RNA, DNA or even chromatin. Microvesicles originate from membrane budding. During these EVs biogenesis several membrane curvature inducers participate, as lipids and calcium-related enzymes, including contraction of the actomyosin ring. The endosomal sorting complex required for transport (ESCRT) participates in vesicle fission. They include RNA, lipids, proteins, tetraspanins and biomarkers of the cell of origin. Exosomes originate from intraluminal vesicles (ILVs) that accumulates in endosomes forming multivesicular bodies (MVBs) that later fuse with the membrane to release the vesicles. Cargo sorting might happen in an ESCRT-dependent or independent pathway. Exosomes carry RNA, lipids, proteins and are highly enriched in tetraspanins, more than microvesicles. 1.4.3.1 Biogenesis and composition of EVs 1.4.3.1.1 Apoptotic bodies (ABs) Apoptosis is a type of programmed cell death characterized by cell shrinkage, cell and nuclear membrane fragmentation, membrane blebbing and formation of ABs, caspase activation, chromatin condensation and DNA fragmentation [182]. ABs are released during membrane disruption after drastic alteration of cellular osmotic equilibrium during cell death. The secretion of ABs Doctoral Thesis Patricia de la Cruz Ojeda 95 constitutes a hallmark of apoptosis. Although they may range in size from 50 nm up to 5000 nm, they usually display large sizes [183] (Figure 6). As blebbing occurs in a random way across the membrane, composition of ABs is frequently diverse. They might harbor lipids, proteins, chromatin, RNA species, as well as viable and/or fragmented organelles, including ER, mitochondria, or Golgi. They also carry phosphatidylserine (PS) on their plasma membrane which it is recognized and phagocyted by macrophages. Not only, ABs could be transferred to other surrounding cells, like parenchymal or neoplastic cells. Although they have been considered as “waste” vesicles, they are able to transfer available material to recipient cells [183,184]. 1.4.3.1.2 Microvesicles (MVs) MVs biogenesis involves budding from the plasma membrane. Therefore, MVs could size in range from 100 nm up to 1000 nm [184] (Figure 6). Mechanisms governing MVs biogenesis have not been fully elucidated and seem to be highly dependent of cell type and context. It seems to rely on lipid composition, cytoskeletal components, Ca+2 levels and some components of the Endosomal Sorting Complexes Required for Transport (ESCRT) machinery. Among Ca+2 - dependent mechanisms, the action of aminophospholipid translocases, scramblases and calpain should be mentioned, as they promote the exposure of PS on the cell membrane, causing membrane curvatures that reassemble actin cytoskeleton and contribute to ceramide distribution to promote vesicle release. This pathway seems to be specific of MVs and has not been identified during exosome biogenesis until now. Later on, the release of MVs by membrane fission should be carried out. One plausible mechanism is the contraction of the actomyosin fibers, in which several small GTP binding proteins have been shown to participate, such as ADP-Ribosylation Factor 6 and 1 (ARF6 and ARF1), or even Cdc42. Moreover, several ESCRT members like TSG101 and the ATPase Vacuolar protein sorting-associated protein 4 (Vps4) could also induce fission and promote EVs release [185]. In HCC cell lines, miR-200a has shown to Doctoral Thesis Patricia de la Cruz Ojeda 96 modulate the biogenesis of exosomal like-MVs. In particular, this miRNA is able to target gelsolin, that regulates the assembly of F-actin filaments. Therefore, the increased release of MVs in cancer could be correlated with lower levels of the anti-tumoral miR-200a [186]. Interestingly, large oncosomes originate from non-apoptotic membrane blebs in ameboid-like tumor cells, and contribute to tumor progression by transferring large amounts of oncogenic material. They share some of the pathways involved in MVs biogenesis, so they could be considered a mixed type of EVs [187,188]. Regarding composition, MVs show high variability depending on isolation procedures. However, they might present protein markers related to their biogenesis, including several tetraspanins, and should be depleted of cellular components. This implies that there are no specific biomarkers that could help to distinguish them from exosomes [184]. The proteome of human circulating microparticles has been explored, showing representation of actin- and myosinrelated proteins, integrins and Major Histocompatibility Complex (MHC), among others [189]. In particular, ARF6 may regulate the inclusion of MHC class I, β1 integrin receptors, Vesicle Associated Protein 3 (VAMP3) and Membrane Type 1 Matrix Metalloproteinase (MT1MMP) [190]. Also, MVs can transport different RNA species with pro-oncogenic potential [191,192], as well as important tumor biomarkers relevant for prognosis, like EGFRvIII in glioblastoma [192]. A study carried out in healthy subjects, cirrhotic patients with HCV and HCC patients has identified VersiCAN core protein (VCAN) to be elevated in cirrhotic patients with a further increase in HCC, compared to healthy controls. The enrichment of ANneXin A2 (ANXA2) in MVs could help to differentiate cirrhosis from HCC. In the HCC patients, MVs proteins have been described to be enriched in complement activation, lipid transport and platelet degranulation [193]. Doctoral Thesis Patricia de la Cruz Ojeda 97 1.4.3.1.3 Exosomes Exosomes are referred to vesicles of endosomal origin or ILVs which typically range in size from 30 to 150 nm (Figure 6). As they constitute the result of the secretory pathway, they can be found in several biological fluids, such as blood (plasma and serum), urine, breast milk, semen or saliva, among others [184]. Biogenesis of exosomes starts with the formation of membrane microdomains where cargos cluster at Multivesicular Endosomes (MVEs). Cargo selection mechanisms could be ESCRT-dependent or -independent. However, vesicle fission into the MVEs always depend on ESCRT-III machinery (Figure 6). Both mechanisms operate during biogenesis of exosomes and preferences regarding one or another greatly vary depending on cargos, maturation stage of the cells, stimuli, or they can even coexist and give rise to heterogenous exosome populations [185]. It is important to highlight that although both processes are considered during exosome generation, the routes of EVs biogenesis depend on cell types and their necessities [194,195]. ESCRT-dependent pathway typically involves cargo sorting by ubiquitination and clathrin coating, although there could be some exceptions like it is the case of MHC. The ESCRT network is constituted by four complexes, together with the ATPase (Vps4) and accessory proteins such as Alix [196]: ‐ ESCRT-0: constituted by Hepatocyte Regulated tyrosine kinase Substrate (HRS) and Signal Transducing Adaptor Molecule (STAM). The Ubiquitin- Interacting Motif (UIM) allows the interaction with ubiquitinated cargos at the endosome membrane. Moreover, the double zinc-finger FYVE domain of HRS anchors ESCRT 0 to the membrane through Phosphatidyl- Inositol-3-Phosphate (PtdIns3P). This, in turn, recruits clathrin domains. ‐ ESCRT-I: it is a heterotrimeric complex composed of Vps23 (TSG101), Vps28, Vps37, and the accessory protein Mvb12. ESCRT-0 and ESCRT-I interact through the UEV domain, which also allows for recruitment of ubiquitin labelled cargoes. Doctoral Thesis Patricia de la Cruz Ojeda 104 maintenance of the Golgi structure and vesicle transport, enhances exosome secretion. HCC derived exosomes exert a pro-tumoral role by inducing angiogenesis and leading to Sorafenib resistance. Specifically, these exosomes transport miR-494-3p to directly target PTEN in recipient cells (Table 3) [217]. Other studies have assessed the relationship between the lncRNAs linc-VLDLR or ROR in Sorafenib responsiveness in cancer cells [218,219]. Table 3. miRNA expression during Sorafenib resistance and mechanisms involved in cells and EVs. miRNA targets are indicated within brackets. miRNA Expression Mechanism Reference let-7c Downregulation MAPK signaling (MAP4K3) [134] let-7c Downregulation Apoptosis (Bcl-xL) [146] let-7g Downregulation Apoptosis (Bcl-xL) [146] miR-7 Downregulation ERK signaling (TYRO3) [133] miR-10b-3p Downregulation Cell cycle (cyclin D) [152] miR-15a Downregulation Protein stabilization (CDC37L1) [220] miR-16 Downregulation Hypoxia (14-3-3η) [169] miR-19a-3p Upregulation PTEN/Akt (PTEN) [123] miR-20b Downregulation Protein stabilization (CDC37L1) [220] miR-21 Upregulation Autophagy (PTEN) [143] miR-221 Upregulation Apoptosis (Caspase-3) [144] miR-22-3p Downregulation NRAS/Raf/MEK/ERK pathway (NRAS) [135] miR-23a-3p Downregulation Ferroptosis (ACSL4) [151] miR-23b-3p Downregulation Autophagy (ATG12) [138] Doctoral Thesis Patricia de la Cruz Ojeda 105 miR-23b-3p Downregulation Not tested [179] miR-23b-3p Downregulation Autophagy (EGR1) [139] miR-25 Upregulation Autophagy (FBXW7) [140] miR-29a Downregulation Stemness (Bcl-2) [148] miR-30a Downregulation Autophagy (Beclin-1) [159,160] miR-30a-5p Downregulation Aerobic glycolysis (CLCF1) [158] miR-92b Upregulation PI3K/Akt signaling (PTEN) [121] miR-93 Upregulation MTMR1 [157] miR-93 Upregulation PTEN/Akt (PTEN) [124] miR-106b-5p Upregulation Cell cycle, anti-apoptotic proteins (BTG3) [145] miR-122 Downregulation Apoptosis resistance (Serpin B3) [150] miR-122 Downregulation ERK signaling (IGF-1R) [132] miR-122 Downregulation Glycolysis (PDK4) [163] miR-124 Downregulation Stemness (caveolin-1) [119] miR-124-3p.1 Downregulation Cell death (Akt, Sirt1) [118] miR-125b-5p Upregulation EMT (ataxin-1) [154] miR-126-3p Upregulation ERK pathway (SPRED1) [128] miR-128-3p Downregulation PTEN/PI3K/Akt (DJ-1) [126] miR-137 Downregulation Mitochondrial bioenergetics (ANT2) [162] miR-138-1-3p Downregulation Wnt/β-catenin signaling (PAK5) [120] miR-140-3p Downregulation Drug metabolism (PXR) [167] Doctoral Thesis Patricia de la Cruz Ojeda 106 miR-140-5p Downregulation Cell cycle (Aurora-A) [153] miR-142-3p Downregulation Autophagy (ATG5, ATG16L1) [142] miR-142-5p Downregulation Cell cycle and proliferation (MELK) [117] miR-150-5p Upregulation Nrf2 signaling (TMEM9) [165] miR-181a* Upregulation MAPK and apoptosis signaling (RASSF1) [221] miR-183-5p Downregulation Sorafenib metabolism (UGT19A) [166] miR-193b Downregulation Apoptosis (Mcl-1) [149] miR-194 Downregulation Small GTPases (Rac1) [136] miR-199a-5p Downregulation MAPK signaling (MAP4K3) [134] miR-200a Downregulation MVs release [186] miR-200a-3p Downregulation Sorafenib metabolism (UGT19A) [166] miR-204 Downregulation Autophagy (ATG3) [141] miR-338-3p Downregulation Hypoxia (Hif-1α) [172] miR-365 Downregulation Small GTPases (Rac1) [137] miR-374b Downregulation Aerobic glycolysis (PKM2) [161] miR-378 Downregulation ERK signaling (VEGFR, PDGFRβ and c‑Raf) [131] miR-4510 Downregulation ERK signaling (Raf) [129] miR-486-3p Downregulation ERK signaling (EGFR, FGFR4) [130] miR-494 Upregulation Cell cycle, mTOR pathway, apoptosis (p27, PTEN, PUMA) [125] miR-494-3p Upregulation PTEN [217] Doctoral Thesis Patricia de la Cruz Ojeda 107 miR-518d-5p Upregulation Mitochondrial function (c-Jun- PUMA) [147] miR-520f-3p Downregulation Hypoxia induced stemness (SOX9) [171] miR-552 Upregulation PI3K/Akt signaling (PTEN) [122] miR-622 Downregulation KRAS/Raf/MEK/ERK pathway (KRAS) [127] miR-665 Upregulation EMT [155] miR-675 Upregulation EMT [156] * Low descriptive study not included in the text 1.5 Development of new alternative therapeutic approaches: nanovectorization of miRNAs Given the limited effectiveness and the development of side effects during Sorafenib treatment in patients, as well as the recent advances in liquid biopsy biomarkers including identification of miRNA signatures, it is worth to design a project focused on the delivery of anti-tumoral miRNAs to tumor cells aiming to constitute a new therapeutic strategy. Delivery of naked mimics of anti-tumoral miRNAs or inhibitors of protumoral miRNAs (in a similar way to small interfering RNAs, siRNAs) should confront several drawbacks such as being inactivated by nucleases, eliminated by renal excretion, induce immune responses or cause off-target effects before reaching cancer cells. Different viral and non-viral strategies are being developed to overcome these disadvantages [222]. Viral systems include retroviruses, lentiviruses, and adenoviruses or adeno-associated viruses with maximal infection efficiency. However, contrary to viral systems, non-viral systems tend to be less toxic, less immunogenic and not limited to the size of the nucleic acid to be incorporated. Non-viral vectors include Lipid NanoParticles (LNPs), polymeric nanoparticles (NPs) and inorganic NPs [223]. The tendency is to use Doctoral Thesis Patricia de la Cruz Ojeda 108 organic materials, preferentially of natural origin and biodegradability properties. Even, as explained in previous lines, biomimetic vector such as exosomes constitute valuable delivery systems [222]. Protection of RNA species from nucleases can be achieved using several encapsulation approaches [224]: ‐ Electrostatic adsorption to the surface of the NPs: the nucleic acid adheres to the surface of pre-formed cationic NPs to form lipoplexes or polyplexes. Cationic lipids like DOTAP or DOTMA are frequently used as the major components in combination with DOPC, DOPE, DSPC or cholesterol (lipoplexes). Other cationic polymers that form dendrimers could also for polyplexes with RNAs, like PEI, PLL, poly-arginine or PAMAM. ‐ Electrostatic interaction-based layer-by-layer: encapsulation of RNAs in multi-layered NPs by sequential electrostatic interactions. Hybrid polymer-lipid or inorganic-organic polymeric NPs could be used, including materials such as PLGA, PEI, poly-L-Arg or gold. ‐ Core-shell encapsulation: RNA is located in the core of the NP, typically of LNPs. Stable Nucleic-Acid Lipid Particles (SNALPs) consist of cationic– zwitterionic lipids that encompass the RNA. Other types of micelles such as PolyIonic Complex (PIC) consist of several polymers with different charges offer strong self-assembly abilities. ‐ Non-electrostatic interactions: complementary base pairing-based systems with linker nucleic acid sequences, hydrogen bonds forces and coordination bonds, usually with cross-linking materials 1.5.1 β-Cyclodextrins (CDs) Focusing on cationic polymers, CycloDextrin (CD) is a biocompatible cyclic oligosaccharide that is able to encapsulate nucleic acids, as well as their hydroxyl groups might be modified to increase its functionality. The presence of positive charges in the structure of CD allows self-assembly with nucleic acids into stable structures by means of electrostatic interactions [225]. CDs are Doctoral Thesis Patricia de la Cruz Ojeda 109 composed by α-(1→4)-linked glucose units that feature a unique toroidal truncated-cone shape, in which glucose hydroxyls orient to the outer space flanking the upper and lower rims, while the less polar protons point to the inner cavity (Figure 7A). This rigid 3D structure defines a hydrophilic shell and a moderately hydrophobic hollow cavity whose dimensions depend on the number of constitutive glucose units. The hexamer (α-CD), heptamer (β-CD) and octamer (δ-CD), composed by 6, 7 and 8 glucose units, respectively, are the most representative and readily available CD family members [226]. These features together with the fact that CDs are non-toxic to humans, makes CDs an attractive material to develop new miRNA-based NPs in HCC. In fact, β-CDs have already been used in several clinical trials (NCT03153657, NCT01747135, NCT02418676, etc). CDs form NPs with multihead or multi-tail “Janus” architectures, thereby constituting polycationic amphiphilic CDs (paCDs). They interact electrostatically with nucleic acids, including plasmids or siRNAs in order to encapsulate them into bilayers (CDplexes), giving rise to different morphologies such as spherical, rod- or worm-like superstructures. Several formulations have been shown to protect nucleic acids from nuclease treatment and to allow transfections both in vitro and in vivo, thus supporting the ability of CDplexes of delivering intact nucleic acids to recipient cells in an effective manner [227]. Several CDs derivatives have been used in this PhD for constructing paCDplexes, including ACM6 and ADM70 (Figure 7B). Both of them display a basket-shaped CD core with different protonable groups, being 28 for ACM6 and 14 for ADM70. They have shown high transfection efficiencies, equal or even higher that traditional transfection systems like PEI or Lipofectamine. Mechanisms of internalization of CDplexes have been explored, suggesting that this may occur by endocytosis, preferentially by macropinocytosis [228-230]. The effectiveness of CDplexes for in vivo delivery of mimetics will be shortly undertaken. Doctoral Thesis Patricia de la Cruz Ojeda 110 Figure 7. Structures of CDs. (A). Structures of α-, β- and δ-CD (left), 3D view of βCD (upper-right) and schematic representation of CD basket-shape architecture (lower right), with indication of the height, and average internal and external diameters for the three commercially available representatives. (B). Molecular structure of paCDs ADM70 and AMC6. Doctoral Thesis Patricia de la Cruz Ojeda 111 HYPOTHESIS AND OBJECTIVES Doctoral Thesis Patricia de la Cruz Ojeda 112 Doctoral Thesis Patricia de la Cruz Ojeda 113 2. HYPOTHESIS AND OBJECTIVES 2.1 Hypothesis The identification of liquid biopsy biomarkers such as CTCs, miRNAs and EVs will provide relevant information about tumor heterogeneity and dynamism by increasing mutational burden, co-morbidities and therapeutic pressure. The identification of miRNA signature in easy-to-obtain samples will allow its implementation in clinical decision-making algorithms in patients at advanced stages of HCC. This profile will be useful for the prediction of patient prognosis, tumor recurrence and treatment individualization for patients with HCC (Figure 8). In addition, the development of a safety vector including miRNA mimetic related to the effectiveness of TKI and reducing its side effect would an interesting approach to be in vivo tested. Figure 8. Liquid biopsy profile assessed in this PhD project. Circulating tumor cells (CTCs), circulating miRNAs, extracellular vesicles (EVs) and EVs derived miRNAs might be useful for determining patient prognosis, tumor progression and recurrence, as well as they could serve as tools for treatment choice in the clinical setting. Doctoral Thesis Patricia de la Cruz Ojeda 120 of patients from BCLC was used as the validation cohort (n=81) (March 2008-July 2011, median follow-up of 11.4 months) (Table 33). Our study protocol followed the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the local ethical committee (1189-N-20). 3.3 miRNA array and bioinformatic analysis 3.3.1 miRNA profiling miRNAs were profiled by quantitative real-time polymerase reaction (qRT-PCR) using the TaqMan® OpenArray® Human miRNA Panel (Ref. 4470187, Life Technologies, Carlsbad, USA) and accessory kits (Applied Biosystems). Isolated miRNAs were reverse transcribed into cDNA using the TaqMan MicroRNA Reverse Transcription Kit (Ref. 4366596, Life Technologies) and Megaplex RT Primers Human in a set of predefined pools A and B (Ref. 4444750, Life Technologies). cDNA was preamplified with Megaplex PreAmp Primers of gene-specific Human Pools A and B (Ref. 4391128, Life Technologies). The preamplified product was diluted 40 folds and mixed 1:1 v/v with the TaqMan OpenArray Real-Time PCR Master Mix (Ref. 4462159, Life Technologies). Aliquots of the mixture were dispensed on a microfluidic OpenArray 384-well sample plate (Ref. 4406947, Life Technologies). TaqMan OpenArray Human MicroRNA Panels were loaded with the OpenArray AccuFill System. PCR reactions were carried out with QuantStudio™ 12 K Flex OpenArray® Platform (QS12KFlex, Thermo Fisher, Waltham, USA) following the manufacturer’s instructions. These experiments were carried out in collaboration with Dra. Raquel Gómez from “Servicio de Apoyo a la Investigación Biomédica” at the Institute of Biomedicine of Seville. 3.3.2 Data analysis Thermo Fisher Cloud Relative Quantification software was used to analyze PCR data. Expression levels were calculated using the relative threshold cycle (Crt) method. This assay aimed to obtain a total of 758 Crt values for each Doctoral Thesis Patricia de la Cruz Ojeda 121 sample, including 754 unique miRNAs, one negative control (ath-miR159a) and three endogenous positive controls (RNU48, RNU44 and U6). Crt values were normalized using the global mean strategy. Therefore, ∆Crt values were calculated as Crt miRNA-Crt global mean. To analyze microarray data, we included stringent quality control criteria: Crt values < 28, Amplification Score > 1.15, Cq Confidence > 0.8, Cq Standard Deviation < 0.25, and detectable expression in all samples. miRNAs that did not fulfil these criteria were excluded from the analysis. Relative miRNA expression levels between control and experimental groups were calculated by using the ∆∆Crt method and exported for further analysis [234]. Fold change values were calculated as 2-∆∆Crt. Differentially expressed miRNAs showing ≥ 2.0-fold change or < 0.5-fold with a p-value < 0.05 were used for further analysis. Heatmaps were constructed using R Studio with ComplexHeatmap, viridis and dplyr packages 3.3.3 Bioinformatic analysis Target prediction was done using free online tools TargetScan and miRDB databases. To ensure that target prediction was not random, for TargetScan prediction, only highly conserved predicted targets with a cumulative weighted context score < -0.4 were selected. For miRDB targets, score was set at 80 points. Enrichment analysis of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool [235] allowed us to investigate the biological function of miRNA targets. Gene Regulatory Networks (GRNs) were constructed using Cytoscape software. 3.4 Measurement of miRNA expression 3.4.1 RNA extraction Total RNA from cells, conditioned media and EVs was extracted using the miRNeasy kit (Ref. 217004, Qiagen, Hilden, Germany). Lysis was performed with Doctoral Thesis Patricia de la Cruz Ojeda 122 Qiazol and RNA fractions were bound to RNeasy Mini spin column, washed and eluted in RNase-free water. Cellular RNA was then quantified using NanoDrop™ One/OneC Microvolume UV-Vis Spectrophotometer (ThermoFisher Scientific). Circulating miRNAs were extracted from 200 µL of plasma using the miRNeasy Serum/Plasma Kit (Ref. 217184, Qiagen). To assess quality of RNA extraction from plasma samples, conditioned media and EVs, three spike-in controls were added at the beginning of the extraction (Ref. 339390, Qiagen) (2 fmol UniSp2, 0.02 fmol UniSp4, 0.00002 fmol UniSp5). 3.4.2 Reverse transcription and qPCR Differentially expressed miRNAs were analyzed by qRT-PCR using miRCURY LNA™ miRNA PCR System (Qiagen). Mature miRNAs were retrotranscribed using the miRCURY LNA RT Kit (Ref. 339340, Qiagen), which allows universal cDNA synthesis through the addition of a poly(A) tail to miRNA templates. For miRNA measurements from cell lysates, 25 ng of eluted RNA was used as the starting material, whereas 7 µL of eluates were used for cDNA synthesis in the case of conditioned media and EVs. In the study involving miRNA measurement in patients, 1.12 µL of RNA eluates were used for cDNA synthesis. qRT-PCRs were carried out with miRCURY LNA™ miRNA PCR Assays (Qiagen) in ViiA™ 7 Real‐Time PCR System (Applied Biosystems, Thermo Fisher Scientific). Ct values were analyzed using the ∆∆Ct method and Fold-Change values were calculated as 2-∆∆Crt with Thermo Fisher Cloud Relative Quantification software [234]. U6 and spike-in controls were used as endogenous and exogenous controls, respectively. Primers miRCURY LNA miRNA PCR Assays (Qiagen) were as follows: Doctoral Thesis Patricia de la Cruz Ojeda 123 Table 5. List of primers used in miRNA PCR assays, including reference number and usage of the oligonucleotides for PCR analysis. miRNA Reference Usage miR-27a-3p YP00206038 miRNA to investigate miR-122-5p YP00205664 miRNA to investigate miR-148b-3p YP00204047 miRNA to investigate miR-193b-3p YP00204226 miRNA to investigate miR-194-5p YP00204080 miRNA to investigate miR-200c-3p YP00204482 miRNA to investigate miR-222-5p YP00204314 miRNA to investigate miR-375 YP00204362 miRNA to investigate miR-505-5p YP00205657 miRNA to investigate miR-512-3p YP00204382 miRNA to investigate miR-551a YP00204331 miRNA to investigate U6 YP00203907 Endogenous control UniSp4 YP00203953 Exogenous control 3.5 Transient transfections with miRNA mimics and inhibitors In order to assess the functional impact of miRNAs selected in the profiling study, we used mimics for downregulated miRNAs, and inhibitors for upregulated miRNAs. miRNA mimics are based on three RNA strands: one guide RNA strand based on miRNA sequence, and one passenger strand split into two strands that protect the guide strand. On the other hand, inhibitors are antisense oligonucleotides with perfect complementary to their miRNA targets. Their mechanism of action is based on the blockade of natural mature miRNAs inside the cells. Doctoral Thesis Patricia de la Cruz Ojeda 124 HepG2 cells (50,000 cells/cm2) were transfected with miRNA mimics and inhibitor oligonucleotides, and their respective transfection controls (miRCURY LNA™ miRNA, Qiagen). 24 hours after plating, transfections were carried out using Lipofectamine RNAiMAX reagent (Ref. 13778075, Thermo Fisher Scientific) according to the manufacturer’s instructions. Briefly, cell culture medium was changed to antibiotic free medium. miRNA-Lipofectamine complexes were stablished in Opti-MEM™ (Ref. 31985062, Thermo Fisher Scientific) medium. After 6 hours of transfection, medium was changed to complete medium. miRNA mimics and inhibitors oligonucleotides (Qiagen) were used at effective concentrations (Table 6). Concentrations for each mimic and inhibitor were specifically optimized by qRT-PCR. For mimics, oligonucleotides were tested at 0.5 nM, 5 nM and 50 nM, whereas inhibitor oligonucleotides were tested at 1 nM, 10 nM and 100 nM, following manufacturer’s recommendations. Table 6. List of mimics and inhibitors used in this study, including reference number and concentration used in functional studies. miRNA Type Reference Concentration miR-27a-3p Inhibitor YI04102151-ADA 1 nM miR-122-5p Inhibitor YI04100402-ADA 10 nM miR-148b-3p Mimic YM00471310-ADA 50 nM miR-193b-3p Inhibitor YI04101855-ADA 10 nM miR-194-5p Mimic YM00471895-ADA 5 nM miR-200c-3p Inhibitor YI04100887-ADA 10 nM miR-222-5p Mimic YM00470554-ADA 50 nM miR-375 Inhibitor YM00470554-ADA 10 nM miR-505-5p Inhibitor YI04101501-ADA 10 nM Doctoral Thesis Patricia de la Cruz Ojeda 125 miR-512-3p Mimic YM00472321-ADA 5 nM miR-551a Mimic YM00473198-ADA 5 nM Negative Control 4 Mimic YM00479903-ADA 50 nM Negative Control A Inhibitor YI00199006-ADA 10 nM 3.6 Cell proliferation assay Cell proliferation was determined with the colorimetric test Cell Proliferation ELISA (Ref. 11647229001, Sigma-Aldrich) based on the incorporation of BromodeoxyUridine (BrdU) in the replicating DNA. BrdU was diluted 1:100 in medium and 10 µL were added to each well including cultured cells in 100 µL 2 hours before sample collection (24 hours). Next, media were removed and 100 µL of FixDenat reagent were added to ensure fixation and denaturalization of DNA, and incubated for 30 minutes at Room Temperature (RT). After removal, anti-BrdU antibody was diluted 1:100 and 100 µL/well were added, and incubated for 90 minutes at RT. Labelling solution was removed and cells were washed three times with the Washing solution included in the kit. 100 µL of ready-to-use substrate solution were incubated for 5 minutes at RT until blue color development. Absorbance was recorded at 370 nm using 492 nm as the reference wavelength in an Infinite 200 PRO Microplate Reader (TECAN, Männedorf, Switzerland). Assay controls were also performed in the experiment, regarding background wells without BrdU. For data analysis, absorbance was calculated as A370 nm – A494 nm. Then, background values were subtracted and normalized to controls. 3.7 Preparation of cell lysate Samples were treated with lysis solution including 50 mM HEPES (H3375, Sigma-Aldrich) pH 7.5, 5 mM EDTA (E7889, Sigma-Aldrich), 150 mM NaCl (S9888, Sigma-Aldrich), 1 % NP‐40 (A1694, AppliChem), protease inhibitor Doctoral Thesis Patricia de la Cruz Ojeda 126 cocktail (P8340, Sigma‐Aldrich), 1 mM PhenylMethaneSulFonyl fluoride (PMSF) (A0999, AppliChem), 1 mM NaF (A0547, AppliChem), and 1 mM Na3VO4 (A2196, AppliChem). Cell lysates were transferred to 1,5 ml tubes, incubated on ice and regularly vortexed for 15 seconds in each five minutes. Samples were centrifuged at 16,000 x g at 4°C for 5 minutes. Supernatants were collected for protein quantification and downstream analysis. 3.8 Protein quantification Protein content in samples was measured with the DC Protein Assay (Bio- Rad, Hercules, USA), which is based on the Lowry method. Sample protein concentration was estimated using a calibration curve using Bovine Serum Albumin (BSA) as standard in a range between 0 and 1.5 µg/µL. 5 µL in 96-clear bottom plates (Ref. 9017, Corning, New York, USA). For samples containing detergent, Protein Assay Reagent A (#5000113, Bio-Rad) was mixed with Protein Assay Reagent S (#5000115, Bio-Rad) in proportion 50:1. 25 µL of freshly prepared mix were added to standards and samples, and followed by 200 µL of Protein Assay Reagent B (#5000114, Bio-Rad). Samples were incubated for 15 minutes at RT, and measured their absorbance at 750 in an Infinite 200 PRO Microplate Reader (TECAN). 3.9 Cell death assay Caspase-Glo® 3/7 (Ref. G8090/G8091, Promega, Madison, USA) chemiluminescent assay was used to measure apoptosis. This assay is based on a caspase-3/7 substrate containing the sequence DEVD susceptible to be enzymatically cleaved by caspases releasing a luminogenic substrate that in presence of luciferin yields a luminescent signal. Therefore, the amount of signal is proportional to caspase activity. According to manufacturer’s instructions, Caspase-Glo® 3/7 Buffer and lyophilized Caspase-Glo® 3/7 Substrate were equilibrated at RT and mixed before use, to make assay buffer. Cells were disrupted with lysis buffer and protein quantified as described above. For Doctoral Thesis Patricia de la Cruz Ojeda 127 caspase activity assessment, 20 µL of samples containing 25 µg of total protein were incubated with 20 µL of assay buffer in white bottom 384-well plates (Ref. 3824, CORNING) for 45 minutes at RT in darkness. After that, luminescence was recorded in an Infinite 200 PRO Microplate Reader (TECAN). For analysis, luminescence values were normalized to control values. 3.10 Cell migration assay Cells were transfected with miRNA mimics and antisense oligonucleotides as described above. Cells were allowed to reach confluence for 48 hours post-transfection, starved for 6 hours (0% FBS) and then scratches were made with a 200 µL pipette tip. Cell monolayers were washed twice with warm medium and were incubated for 24 hours with Sorafenib at 2 % FBS (F7524, Sigma-Aldrich, batch BCBX9154). Image acquisition was done at 0 and 24 hours with an inverted microscope Olympus IX-71. Image J software was used for image analysis. 3.11 Cell invasion assay Cell invasiveness properties were measured using the QCM ECMatrix Cell Invasion Assay (Ref. ECM550, Chemicon®, Merck Millipore, Burlington, USA). Transfected cells (500,000 cells/mL) in serum free medium with or without Sorafenib were added to the inserts. After 24 hours of incubation, invasive cells were treated with the staining solution included in the kit and dissolved with 10% acetic acid. Absorbance at 560 nm was measured with an Infinite 200 PRO Microplate Reader (TECAN). 3.12 Isolation of extracellular vesicles 3.12.1 EVs depletion from FBS Depletion of EVs and protein aggregates from FBS was carried out by ultracentrifugation to remove existing bovine EVs. Up to 50 mL of serum were Doctoral Thesis Patricia de la Cruz Ojeda 128 diluted in 250 mL of non-complemented medium and divided into eight ultracentrifuge tubes (Ref. 344326, Beckman Coulter, Brea, USA). After weight balance, tubes were ultracentrifuged overnight for 14 hours at 100,000 x g in an Optima L100-XP ultracentrifuge with 70 Ti rotor (Ref. 337922, Beckman Coulter). Next, medium was recovered, filtered through 0.22 µm (Ref. 38.1826.001, Sarstedt) and complemented up to 500 mL. 3.12.2 Experimental procedure EVs were isolated through differential centrifugation. Dead cells and debris were removed by centrifuging conditioned media for 15 minutes at 300 x g. This pellet was added to the cellular pellet for further caspase-3 analysis. Big debris cell free media were used for miRNA determinations. Next, media were centrifuged at 2,000 x g for 20 minutes to obtain a fraction called “Large EVs”. Supernatant was collected and centrifuged at 20,000 x g for 30 minutes to obtain a fraction called “Small EVs”. These two centrifugation steps were carried out in a Sorvall™ RC 6 Plus centrifuge (Ref. 12121680, Thermo Fisher Scientific, Waltham, USA). Eventually, remaining supernatant was filtered through 0.22 µm (Ref. 38.1826.001, Sarstedt) and ultracentrifuged at 120,000 x g for 75 minutes to obtain “Very Small EVs” in an Optima L100-XP ultracentrifuge with 70 Ti rotor (Ref. 337922, Beckman Coulter) (Figure 9). Doctoral Thesis Patricia de la Cruz Ojeda 129 Figure 9. Diagram showing protocol of EV isolation by differential centrifugation. 3.13 EVs size analysis based on Brownian motion of particles The Dynamic Light Scattering (DLS) and Nanoparticle Tracking Analysis (NTA) are based on physical properties of particles, recording light fluctuations in the scattered light of moving particles in solutions (Brownian motion). Both methods are useful to analyze EVs as well as any other particle in the fluid, not being able to identify EVs by their biological properties. 3.13.1 Dynamic Light Scattering DLS was performed in a Zetasizer Nano ZSP (Malvern Panalytical, Malvern, UK). The procedure is suitable for size determination or Z-potential calculation of particles, but it does not provide information about concentration. Thus, intensity plots were used to estimate EVs size. Samples were diluted 1:50 Doctoral Thesis Patricia de la Cruz Ojeda 136 3.15.4 Library quantity and quality assessments Suitability of libraries for Illumina sequencing was tested by assessing base pair (bp) distribution. First, libraries were quantified using the Qubit® 3 Fluorometer (Ref. Q33238, Thermo Fisher Scientific) using the dsDNA HS Assay Kit (Ref Q32851, Thermo Fisher Scientific). A working solution containing dsDNA HS Reagent dye and dsDNA HS Buffer in a proportion 1:200 was prepared. 10 µL of standards or 1 µL were mixed with the Working Solution in a final volume of 200 µL in optical tubes. Standards and samples were mixed by vortex and incubated at RT for 2-3 minutes. After calibration with standards, samples were read. Size profile of libraries was studied with High Sensitivity D1000 ScreenTape System for the TapeStation 4150 system (Ref. G2992AA) was used. 1 µL of libraries or Ladder (Ref. 5067-5586, Agilent Technologies) were mixed with 2 µL of Sample Buffer (Ref. 5067-5602, Agilent Technologies). Samples were automatedly loaded in the ScreenTape Ref. 5067-5584, Agilent Technologies). Electropherograms were obtained and regions between 160-1000 bp were selected for quantification (pg/µL) and median peak size determinations. No libraries presented adapter amplification below 160 bp or overcycling. 3.15.5 Library pooling and dilution Libraries were pooled together at a final concentration of 2 nM. Then, they were diluted with commercial RBS buffer with Tween20 as diluent to the final loading concentration of 750 pM in a final volume of 24 µL. Library pool was spiked with 2% of PhiX to provide a positive control and additional metrics and base diversity. 3.15.6 mRNA sequencing data analysis Primary analysis was done with Illumina DRAGEN FASTQ Generation online software (v. 3.8.4) in order to perform intensity extraction, phasing Doctoral Thesis Patricia de la Cruz Ojeda 137 correction, base calling and quality scoring, to obtain FASTQ files and metrics. Secondary analysis, concerning alignment, mapping, and differential expression analysis, was carried out using Bluebee® Quantseq pipeline. Briefly, reads were quality and adapter trimmed and mapped to the human genome version GRCh38 using STAR Aligner with modified ENCODE settings [236]. HTSeqcount was used for gene read counting and Differential Expression Analysis (DEA) was performed using the DESeq2 method [237]. Principal component analysis was done with R Studio using packages BiocManager, DESeq2 and ggplot2. Heatmaps were constructed using R Studio with ComplexHeatmap, viridis and dplyr packages. GO terms and KEGG pathways enrichment analysis was performed with DAVID online tool [235] using all genes with counts > 0 as background. Also, to interpret genomic data, Gene Set Enrichment Analysis (GSEA) was performed [238,239]. Biological connections among selected targets were estimated using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) [240]. STRING analysis was performed with medium confidence (interaction score 0.4) only for query proteins. Sequencing data were provided as Fold-Change (FC) values with base mean counts, p-value and adjusted p-value (p-adj). FC values were calculated as: (counts in the experimental condition)/(counts in the control condition). In order to select direct and indirect targets of each miRNA studied, Venn diagrams were generated using cut-offs of base mean > 30 and log2FC > 0.5 (upregulation) or < -0.5 (downregulation). 3.16 Circulating Epithelial Cell enrichment Enrichment of CECs from peripheral blood was carried out with the commercially available kit from Isoflux based on the measurement of rare CTCs including assessment of epithelial and EMT markers (Ref. 910-0106, IsoFlux, Fluxion Biosciences, Alameda, USA). This method is based on the microfluidic separation of immunomagnetic beads covered by monoclonal mouse IgG Doctoral Thesis Patricia de la Cruz Ojeda 138 antibodies against the epidermal EpCAM and EGFR, and the mesenchymal markers c-Met, N-cadherin and vimentin. Total blood samples (6 mL) were collected in EDTA-K2 Vacutainer™ tubes (Becton Dickinson) and processed no longer than 6 hours after extraction. Separation of Peripheral Mononuclear Blood Cells (PBMCs) was done with density gradient Ficoll-Paque™ Plus (Ref. 17-1440-02, GE Healthcare, Chicago, USA) in frit coupled Leucosep™ tubes (Ref. 227290, Greiner Bio-One, Kremsmünster, Austria). 15.2 mL of Ficoll were added per tube and centrifuged at 1000 x g for 1 minute. Next, 5 mL of PBS were added to avoid that blood could stick to the frit. Blood was left to decant inside the tube and blood tubes were rinsed twice with 10 mL of PBS. Processed samples were centrifuged at 8,000 x g for 15 minutes without brake and the fraction of PBMCs above the frit was recovered into a new clean tube. After washing with 10 mL of PBS, cell fraction was pelleted at 280 x g for 10 minutes. Supernatant was removed leaving an excess of 500 µL. Fc blocking solution was added for pellets resuspension by tapping the tube and further incubation on ice. Cell suspension was transferred to a microcentrifuge tube. Next, antibodies-coated beads were coupled to cell samples. Anti-EpCAM-coupled beads were provided by manufacturer ready-to- use. The coupling of the rest of antibodies and beads were prepared by mixing specific volumes of Ig-immunomagnetic-coupled beads to anti-EGFR, anti-c-Met, anti-N-cadherin and anti-vimentin. After addition of antibodies, samples were incubated for 2 hours at 4°C with rotation, and afterwards loaded into Isoflux microfluidic cartridges. Eventually, after enrichment procedure in Isoflux machine, CECs were recovered for further analysis 3.17 Circulating Epithelial Cell enumeration Upon CEC enrichment, cells isolated from one Isoflux cartridge (6 mL of blood) were fixed at RT for 20 minutes, and negatively selected using CD45 immunofluorescent labelling included in the commercial Isoflux™ CTC Enumeration Kit (Ref. 910-0093, IsoFlux). Samples were previously blocked with Doctoral Thesis Patricia de la Cruz Ojeda 139 normal donkey serum for 5 minutes. Cells were incubated with rabbit anti-CD45 primary antibody and donkey anti-rabbit-Cy™3-conjugated secondary antibody for 20 minutes. Next, cells were permeabilized in 0.2 % TX-100 and incubated with mouse monoclonal anti-cytokeratin-FITC-conjugated for 40 minutes. Cells were washed with Hoechst 0.02% to stain nuclei and placed on microscope slides with commercially supplied Mounting Media. The acquisition of images was done with a fluorescence direct Olympus BX-61 microscope (Shinjuku, Tokyo, Japan). Images were taken from the whole area of the sample. Imaging processing was done with VIS software for creating superimages. Individual CECs were enumerated as intact nucleated DAPI+ cells with positive green fluorescence (Cytokeratin+) and negative red fluorescence (CD45-). Grouping of individual CECs was named as cluster and the number of cells inside these groups were named as clustered CECs. Total DAPI+ cells (nucleated cells) were counted with ImageJ software. Results were expressed as the percentage of cytokeratin+ cells divided by total detected DAPI+ nucleated cells (%), clusters or clustered cells. Negative controls included beads coupled to antibodies without biological samples in order to discriminate positive counts (Figure 11). Figure 11. (A) Representative images of CECs immunofluorescence and (B) Negative control of immunomagnetic beads. CD45+ blood cells were nucleated cells (blue) with positive red fluorescence (arrowhead). Individual CECs were defined as colocalization of one nucleus (blue) and cytokeratin-green fluorescence (green) (arrow). Clustered CECs were recognized as grouped CECs (dotted arrow). Doctoral Thesis Patricia de la Cruz Ojeda 140 3.17.1 Technique efficiency evaluation To test the efficiency of the Isoflux for isolation of cancer cells, liver cancer cells were stained and spiked into blood samples for quantification. Briefly, HepG2 cells were labelled with CellTracker Green (Ref. C7025, Invitrogen, Thermo Fisher Scientific) at a concentration of 2 µM in serum-free medium for 30 minutes at 37°C. Cells were harvested, and 1,000 cells were added to 6 mL of blood from healthy subjects. Isoflux enrichment procedure was carried as described above. Tumor positive green fluorescence cells were determined by three independent evaluators. The percentage of recovery obtained was 82±7% (n=3). 3.18 Assessment of cell proliferation and death in CECs 3.18.1 CTCs cell culture Cells isolated from one Isoflux cartridge (6 mL of blood) were used. After isolation, cells were washed twice with 200 µL of commercially supplied binding buffer, and resuspended in 200 µL of complemented MEM medium described above. From this solution, 5 µL were used for cell and bead counting with Neubauer’s chamber with trypan blue dye. Cell suspension was plated into 6 wells, and after 24 hours of stabilization, cells were treated with Sorafenib, Regorafenib, Lenvatinib, Cabozantinib and Doxorubicin (and control) (see Table 4) for 12 hours. Then, cells were harvested and washed twice with 200 µL PBS. To avoid loss of attached cells, plates were treated with trypsin and cell pellets were joined together. Cells were used in further experiments. 3.18.2 Flow cytometry Cultured CECs were fixed and permeabilized with CytoFix/CytoPerm solution included in the FITC Active Caspase-3 Apoptosis Kit (Ref. 550480, Becton Dickinson Biosciences, Franklin Lakes, USA). Next, they were washed twice with Permeabilization and Washing commercial solution and incubated for Doctoral Thesis Patricia de la Cruz Ojeda 141 30 minutes with the antibody at RT as described in the kit. Afterwards, cells were resuspended in Permeabilization and Washing commercial solution and analyzed in BD FACSCanto II Flow Cytometer (Becton Dickinson Biosciences). Side Scatter (SSC), Forward Scatter (FSC), and fluorescence (Table 8) parameters were recorded. For gating analysis (Figure 12), first population was defined using a negative control of magnetic beads without bound cells. Then, CECs were defined as cytokeratin positive cells, being negative for CD45. Proliferation (Ki67) and apoptosis (Caspase-3) were recorded in this subpopulation. Table 8. Antibodies used in flow cytometric analysis of proliferative and apoptotic properties of CECs. Table includes information about lasers and filter configuration for each marker. Marker Antibody Reference Laser Filter Epithelial cell (CECs) Monoclonal Anti-Cytokeratin (Pan-reactive)-PE antibody SAB4700668 (Sigma-Aldrich) 488 nm 585/42 Leukocytes CD45 Monoclonal Antibody (HI30), eFluor™ 450, eBioscience™ 48-0459-42 (Invitrogen) 405 nm 450/50 Proliferation Ki-67 Monoclonal Antibody (20Raj1), APC, eBioscience™ 17-5699-42 (Invitrogen) 633 nm 630/30 Apoptosis FITC-Active Caspase-3 Apoptosis Kit 550480 (Becton- Dickinson, Pharmingen) 488 nm 530/30 Doctoral Thesis Patricia de la Cruz Ojeda 142 Figure 12. Diagram showing gating strategy of CECs samples labelled with proliferation, apoptosis, epithelial and blood cell markers. CECs were identified as singlets positive for cytokeratin and negative for CD45 markers. This population was further used for proliferation and death assessments. 3.19 Assessment of effectiveness of CDplexes functionalized with miRNA mimics 3.19.1 Preparation of CDplexes The polycationic amphiphilic cyclodextrin (paCD) ADM70 [241] and AMC6 [242] used in this PhD thesis were synthetized according to reported procedures. The synthetic strategy was based on the face-selective chemical derivatization of the cyclodextrin scaffold (β-CD in this case) (Figure 13). For such goal, the regioselective halogenation conditions developed by Gadelle and Defaye [243] were implemented to furnish β-CD derivative 1, featuring 7 bromine atoms at the narrower rim. In a second step, secondary hydroxyls at the wider rim of hepta-bromo β-CD 1 were exhaustively acylated with hexanoic anhydride to yield the facially differentiated derivative 2. At this point, the synthetic scheme Doctoral Thesis Patricia de la Cruz Ojeda 143 diverges. For the synthesis of ADM70, derivative 2 is treated with N-Boc- protected cysteamine (→ 3, Scheme 1, upper panel). The amine protecting group (Boc) is then cleaved off by acidic treatment to furnish compound 4. Sequential transformation of the polyamine 4 into the hepta-isothiocyanate (→ 5) by treatment with thiophosgene, further thiourea “click-type” multiconjugation with the suitably di-N,N’’-Boc-protected diethylenetriamine, and final Bocgroup cleavage afforded the target paCD ADM70, with all its 14 primary amino groups as the corresponding hydrochloride salt. For the synthesis of AMC6, the copper(I)-catalysed azide-alkyne dipolar cycloaddition multiconjugation (CuAAC, or simply “click chemistry”) strategy was employed [244]. In this case, derivative 2 was treated sodium azide and the corresponding hepta-azido derivative 6 was click-coupled with a propynamideappended tetraethyleneimine derivative. Ultimately, AMC6 was obtained by acid-promoted Boc-group cleavage as its 28-hydrochloride salt (7 primary and 21 secondary ammonium groups (Figure 13). Molecular identity and homogeneity of the synthesized paCDs ADM70 and AMC6 was evidenced by NMR and ESI-MS analysis. In one hand, 1H and 13C-NMR spectra were consistent with the characteristic 7-fold symmetry of βCD scaffold expected for this type of constructs. On the other, ESI-MS spectra exclusively showed peaks for the pseudomolecular ions corresponding to multiply-protonated of each paCDs. Doctoral Thesis Patricia de la Cruz Ojeda 144 Figure 13. Synthesis of paCDs ADM70 and AMC6. Formulations of CDplexes were prepared using two different phases: aqueous RNA phase with diluted miRNA mimic, and DMSO vector phase with diluted CDs in DMSO. ‐ Aqueous RNA phase: the miRNA phase was prepared by dissolving the miR-200c-3p mimic (Applied Biological Materials, Vancouver, Canada) (molecular weight 15081.8 g/mol; 44 phosphate groups) in RNase free water at 4 µM. Then, it was dissolved with water or 5% glycosylated 2-(N- Doctoral Thesis Patricia de la Cruz Ojeda 145 Morpholino) EthaneSulfonic acid (MES) buffer (Ref. 69889, Sigma- Aldrich). ‐ DMSO vector phase: CDs were provided as lyophilized powders. AMC6 was dissolved in DMSO at a concentration of 1 mM (molecular weight= 5394.3 g/mol), while ADM70 was dissolved at 2 mM (molecular weight= 4449.9 g/mol). This constituted the DMSO vector phase. The RNA and cyclodextrin phases were mixed in a ratio 9:1 to reach a final phosphate concentration of 0.019 mM, and a final miRNA concentration of 549 nM. To test the optimal conditions for nanoparticle assembly, different N/P ratios were assessed. For that, the concentration of cyclodextrin, was varied according to table 9, that is that is the concentration of cationic groups with respect to phosphate groups in the mimic. Table 9. Calculations for the preparation of CDplexes using different N/P ratios. Aqueous RNA phase DMSO vector phase N/P miR-200-3p (µl) MES 6x (µl) Water (µl) Resuspended CD (µl) DMSO (µl) 0 1.374 2.167 8.159 0.000 1.300 1 1.374 2.167 8.159 0.009 1.291 2 1.374 2.167 8.159 0.017 1.283 3 1.374 2.167 8.159 0.026 1.274 4 1.374 2.167 8.159 0.035 1.265 5 1.374 2.167 8.159 0.043 1.257 6 1.374 2.167 8.159 0.052 1.248 7.5 1.374 2.167 8.159 0.065 1.235 Doctoral Thesis Patricia de la Cruz Ojeda 248 5.4.2 miRNA profile of HepG2 cells treated with Sorafenib and their prognostic role in HCC We obtained a miRNA profile of Sorafenib response based on the expression of 11 miRNAs. We observed downregulation of miR-551a, and upregulation of miR-122-5p, miR-200c-3p and miR-505-5p at 6 hours of Sorafenib treatment in HepG2 cells, while downregulation of miR-148b-3p, miR-194-5p, miR-222-5p and miR-512-3p, and upregulation of miR-27a-3p, miR-193b-3p and miR-375 after 24 hours of treatments. From these, miR-27a-3p and miR-200c-3p exerted clear anti-tumoral properties, while miR-122-5p, miR-148b-3p, miR-194- 5p, miR-505-5p and miR-512-3p displayed unequivocal pro-tumoral functions. To assess how they might influence disease outcome, we investigated their transfer into EVs in vitro and as circulating biomarkers in plasma. Sorafenib increased miRNA secretion in all EVs measured (24 hours) From the total miRNA profile, baseline levels of miR-200c-3p and time-dependent levels of miR-512-3p were related to patient prognosis in patients with advanced HCC treated with Sorafenib. Moreover, in order to inquire in their functional properties, we performed experiments with mimics and inhibitors to test their impact on transcriptomic profiles of HepG2 cells treated with Sorafenib to unravel potential mechanisms of action. 5.4.2.1 Circulating miRNA profile Few studies have addressed the use of miRNA circulating as biomarkers of Sorafenib responsiveness in patients with advanced HCC. Although low levels of miR-122-5p and high levels of miR-miRNA-21 and miRNA-96 in EVs and plasma have been tested as diagnostic or potential prognostic biomarkers in HCC, no risk models were performed in this study as well as being not related to the effectiveness of therapy [292]. Another study evaluated the longitudinal expression of miR-23b-3p and miR-126-3p in a cohort of seven patients under Sorafenib treatment without establishing any correlation with survival or progression [179]. miR-31-5p, miR-221, miR-30e-3p, or miR-30d have been related Doctoral Thesis Patricia de la Cruz Ojeda 249 to Sorafenib resistance in cultured renal and liver cancer cells [144,180,293,294]. However, as explained in the Introduction section, no robust in vitro, in vivo, and clinical studies have been developed to identify a miRNA signature useful to predict disease outcome and treatment response in advanced HCC. Here, we provided Cox regression models that accurately validated the prognostic role of miR-200c-3p, miR-222-5p, and miR-512-3p in two different populations. Although we tested their secretion in circulating plasma EVs, circulating miRNA expression is preferred, as their measurement is cost-effective and provided herein information about clinical outcome. 5.4.2.2 miR-122-5p (6 hours) miR-122 is the most abundant miRNA in the liver [295], and it is frequently downregulated in primary HCC [296]. By contrast, upon HCC, the loss of miR- 122 expression is closely related to poor prognosis and metastasis of liver cancer [286,297]. Interestingly, Sorafenib upregulated miR-122-5p in HepG2 cells (6 hours, Figure 29). This miRNA was also secreted into very small EVs (Figure 35). In gastric cancer, exosomal miR-122-5p has been described as a tumor suppressor miRNA that is able to control proliferation and metastasis [298]. Nonetheless, upregulation of miR-122-5p reduced caspase-3 in Sorafenib-treated cells. Few terms were enriched in the transcriptomic analysis (Figure 38). One of the upregulated targets of miR-122-5p with functional impact was the phosphatase DUSP6. Inactivation of the MAPK signaling pathways mediated by phosphatases seems to be crucial for Sorafenib response [299]. Also, intratumor DUSP6 levels might be elevated during recurrence after resection [300], showing dual roles in HCC. Signaling in the tumor microenvironment is another key factor for therapy response. Collagen-ITGA2 interactions in liver cancer mediate the connections between CAFs and tumor cells, being responsible for stemness induction through YAP signaling. Thus, ITGA is related with worse patient prognosis [301]. Precisely, we observed higher expression of this integrin in the transcriptomic studies after miRNA inhibition. All in all, in concordance with previous Doctoral Thesis Patricia de la Cruz Ojeda 250 literature, our sequencing data might suggest that miR-122-5p could have an antitumoral role in our setting. 5.4.2.3 miR-200c-3p (6 hours) Of note, the upregulation of miR-200c-3p (6 hours, Figure 29) by Sorafenib has been shown to be coherently related to the anti-tumoral properties in HepG2 and its plasma levels were associated with increased survival (Figure 49). The anti-tumoral role of miR-200c-3p has been related to reduced metastasis in colorectal xenograft models [302] and reduces the infiltration capacity of macrophages co-cultured with breast cancer cells [303]. Here, we additionally demonstrated that miR-200c-3p regulated the damage response by altering HSPA1B or NFE2L2 (Figure 39). HSPA1B is a chaperone that regulates protein folding. Higher accumulation of unfolded proteins could lead to higher ER stress, an early event during Sorafenib response. Therefore, we correlate here the augmentation of unfolded protein response mechanisms with the response to Sorafenib. In fact, miR-200c-3p has been shown to regulate ER stress in prostate cancer [304]. Additionally, we have recently shown that the downregulation of Nrf2 (NFE2L2) and thioredoxin-1 are associated with the anti-tumoral activity of Sorafenib in cultured HepG2, and in a xenograft model [55]. Nrf2 has also been shown to have an important role in ferroptosis inhibition upon Sorafenib treatment as a mechanism of resistance through the expression of MTs [305]. We identified several MTs including MT1B or MT1M as highly expressed upon miR- 200c-3p inhibition. Hence, it seems that heavy metal detoxification and antioxidants might be regulating resistance in our setting. Importantly, PIM3 is a protooncogene with serine/threonine kinase activity that is usually upregulated in HCC. Furthermore, PIM3 accelerates hepatocarcinogenesis induced by diethylnitrosamine in mice [306]. Not only that, but PIM3 controls intracellular cascades regulating migration and invasion [307] as well Bcl-2 related antiapoptotic proteins [308]. All in all, in light of these previous studies, we can conclude that signaling induced by miR-200c-3p inhibition is potentially pro- Doctoral Thesis Patricia de la Cruz Ojeda 251 tumoral, anti-apoptotic, and pro-resistance, supporting the good prognosis value of miR-200c-3p in the plasma of patients treated with Sorafenib. 5.4.2.4 miR-505-5p (6 hours) miR-505-5p has been proposed as a diagnostic marker, detecting HCC with higher accuracy than AFP at the time of diagnosis in different validation cohorts [309]. The expression of miR-505-5p increased 6 hours after Sorafenib administration (Figure 29). The administration of its antisense oligonucleotide increased caspase-3 (Table 32). This result suggests that miR-505-5p upregulation plays a pro-tumoral role in Sorafenib response. Also, miR-505-5p was secreted into EVs only when HepG2 cells were treated with Sorafenib, but not in control cells (Figure 36). In concordance with these results, miR-505-5p has been identified to be an oncomir in lung adenocarcinoma. Similar to our study, miR- 505-5p was upregulated in plasma EVs, and impaired apoptosis by targeting Tumor Protein P53‑regulated Apoptosis‑Inducing Protein 1 (TP53AIP1) [310]. Moreover, as explained in previous lines, PIM3 has a negative impact on prognosis in liver cancer. Not only this, but the anti-stress role of miR-505-5p by regulating chaperones, together with the fact that it is able to control drug uptake support its pro-tumoral role during Sorafenib response. In particular, SLC22A7 was upregulated in the RNA-seq studies (Figure 40). This membrane transporter, also known as Organic Anion Transporter 2 (OAT2) is widely expressed in the liver and has shown to be important for the up-take of several drugs, including 5-fluorouracil [311]. 5.4.2.5 miR-551a (6 hours) The administration of Sorafenib significantly downregulated miR-551a (6 hours, Figure 29). miR-551 has been found to regulate the expression of cathepsin L [312]. Precisely, proteolytic enzymes such as cathepsin L, a lysosomal cysteine protease, are a common occurrence in a variety of human cancers, and they have been widely correlated with metastatic aggressiveness and poor patient Doctoral Thesis Patricia de la Cruz Ojeda 252 prognosis. In fact, cathepsins have multiple biological functions including degradation of extracellular matrix and tissue remodeling, thereby impacting cell transformation and differentiation, motility, adhesion, invasion, angiogenesis, and metastasis [313]. In concordance with this background, downregulation of miR-551a reduced cell migration, and moderately increased cell invasiveness in Sorafenib-treated HepG2 (Table 32). However, circulating miR-551a did not correlate with survival or disease progression. In vitro, miR-551a was not detected neither in the extracellular medium nor in EVs, suggesting that this was not secreted by HepG2 cells (Figure 35 and 36). Regarding transcriptomics (Figure 41), miR-551a clearly impacted the TGF-β signaling pathway. The canonical pathway typically involves SMAD proteins. Among them, the inhibitory SMAD7 was downregulated in response to miR-551a mimics, meaning that this miRNA is able to potentiate TGF-β response [314]. This signaling is interconnected with c-Myc, that was also regulated in this study. TGF-β could mediate anti-tumor functions by inhibiting c-Myc to regulate cell cycle and cellular senescence. This would be in line with our results. Very importantly, high expression of c-Myc correlates with poor overall survival in HCC [315]. Moreover, components of the Wnt signaling were downregulated, including Axin2. Taking into account that Wnt/β-catenin constitutes a driver of HCC [316], the effects of miR-551a could be seen as anti-tumoral. 5.4.2.6 miR-27a-3p (24 hours) miR-27a-3p upregulation after Sorafenib treatment showed a clear antitumor profile (24 hours, Figure 30), reducing cell migration and invasion (Table 32). In the context of HCC, miR-27a-3p regulates EMT [317]. Also, miR-27a- 3p might control cell proliferation by targeting the phosphatase DUSP16 [318]. LncRNA SNAI3-AS1-mediated decoy of miR-27a-3p constitutes one mechanism for HCC development [319]. Importantly, our results also showed that miR-27a- 3p was secreted in response to Sorafenib (Figure 35), possibly contributing to therapy response. However, we did not observe any beneficial effect of miR-27a- 3p in the clinical study. miR-27a-3p targets the EGFR. Curiously, this was not Doctoral Thesis Patricia de la Cruz Ojeda 253 directly affected in the transcriptomic profile of miRNA inhibition (Figure 42). Instead, downstream signaling was upregulated, including SOS1, NRAS or PIK3CA. Another aspect that supports its antitumoral role is the upregulation of NRAS or KRAS after inhibition, meaning that the upregulation mediated by Sorafenib treatment reduces their prooncogenic properties. Even if NRAS or KRAS are not drivers of HCC development, they might contribute to disease progression and Sorafenib treatment resistance [320,321]. Another important aspect to address is the impact of miR-27a-3p on mitochondria. miR-27a-3p seemed to regulate several mitochondrial components to increase Sorafenib response (Cluster 4). Targeting of mitochondria, in particular of complex I and complex III or mitochondrial DNA, leads to increase ROS production and apoptosis induction [322]. 5.4.2.7 miR-148b-3p (24 hours) miR-148b-3p has been associated with tumor suppression properties in colorectal [323] and pancreatic cancer [324]. In fact, miR-148b overexpression induces apoptosis and cell cycle arrest, as well as inhibits cell invasion though reducing the expression of WNT1, β-catenin and c-Myc, while it upregulates E- cadherin expression in control HepG2 cells [325]. Sorafenib downregulated miR- 148-3p expression in our liver cancer cell model (24 hours, Figure 30). However, the administration of miR-148-3p mimic increased cell proliferation and invasion properties (Table 32), supporting a beneficial effect of its downregulation by Sorafenib. Moreover, miR-148b-3p was enriched in EVs at 24 hours of Sorafenib treatment (Figure 35). This miRNA has been shown to participate in the protumoral role of tumor microenvironment, as CAF derive exosomal miR-148b-3p is able to enhance the malignant phenotype of cancer cells by decreasing PTEN expression. This leads, in turn, to activation of the WNT/β-catenin pathway that promotes EMT and metastatic properties [326]. Even if we do not see that this signaling cascade could be directly affected in the transcriptomic profiles (Figure 43), we observed that miR-148b-3p was able to alter the proliferative and migratory capacities of HepG2 cells. Instead, we observed downregulation of ER Doctoral Thesis Patricia de la Cruz Ojeda 254 stress, apoptosis, antigen processing and peroxisomal metabolism, among other hallmarks. For instance, ACOX1 was downregulated as a consequence of miRNA mimics. The peroxisomal acyl-CoA oXidase 1 (ACOX1) is the rate-limiting enzyme in fatty acid β-oxidation and a major producer of H2O2. Although high ACOX1 has been correlated with poor prognosis in HCC [327], it should be taken into account that ROS play a dual role in cancer. Whether if hydrogen peroxide produced by ACOX1 in our system could be a pro-tumoral role or anti-tumoral effects by increasing Sorafenib response, remains still unclear. More experimental data would be needed to address this question. 5.4.2.8 miR-193b-3p (24 hours) miR-193b-3p is dysregulated in cancer and could exert its properties by regulation of its predicted target Mcl-1 [328]. Sponging of miR-193b-3p by long non-coding RNA LINC00152 or by the circular RNA Circ_0000745 might be responsible of inhibiting its anti-tumoral properties in cancer [329,330]. In fact, we found that Sorafenib upregulated miR-193b-3p in cell lysates (Figure 30) and also in EVs (Figure 35). Nonetheless, this miRNA showed controversial roles in functional studies (Table 32). In pancreatic cancer, a six-miRNA signature in plasma that included both miR-122-5p and miR-193b-3p has been shown to be helpful in the diagnosis of cancer. This might confirm that miR-193b-3p is effectively secreted and plays a role in cancer [331]. However, according to the RNA-seq experiments (Figure 44), augmentation of miR-193b-3p by Sorafenib could have anti-tumoral effects, as it could increase the susceptibility to treatment by decreasing mechanisms of DNA repair. In particular, BRCA1 was upregulated after miRNA inhibition. In HCC, BRCA1 expression is frequently higher in HCC and correlates with worse prognosis [332]. ADH5 or S-Nitrosoglutathione reductase (GSNOR) was also upregulated in the transcriptomic studies. The presence of GSNOR is necessary for the activation of DNA repair mechanisms, in whose absence hepatocarcinogenesis is induced [333]. Therefore, there could be interconnections among direct or indirect targets of miR-193b-3p. Doctoral Thesis Patricia de la Cruz Ojeda 255 5.4.2.9 miR-194-5p (24 hours) miR-194-5p is usually found to be a tumor suppressor miRNA. It might be downregulated in HCC by LINC01006 to induce pro-metastatic properties specifically targeting cell adhesion molecule 1 (CADM1) [334]. Very similarly, in colorectal adenocarcinoma, lncRNA H19 regulates miR-194-5p expression in order to induce EMT [335]. Studies involving the administration of miRNA mimics of miR-194-5p showed that downregulation of miR-194-5p played a relevant inhibitory role in cell migration and invasion in Sorafenib-treated HepG2 cells (Table 32). We also found that miR-194-5p was secreted in response to Sorafenib (Figure 35). Contrary to its anti-tumoral functions in cells, the release of miR-194-5p from dying cells in pancreatic cancer contributes to tumor recurrence after radiotherapy [336]. As in the case of miR-27a-3p, miR-194-5p exerts a direct impact on mitochondria. In the RNA-seq experiments (Figure 45) we found several mitochondrial genes (nuclear encoded) downregulated after miRNA mimics. Other authors have identified the TEFM (Transcription Elongation Factor of Mitochondria) to be a direct target of miR-194-5p that is frequently upregulated in HCC [337]. Proteostasis constitute another important process affected by miR-194-5p. In particular, Sorafenib has been demonstrated to alter the translation of AFP due to the induction of ER stress, and decreases the secretory machinery [338]. In our hands, miR-194-5p was able to regulate both ER stress and the secretory pathway, suggesting control over the proteostasis. 5.4.2.10 miR-222-5p (24 hours) The overexpression of miR-222 has been found in liver cancer [339]. The administration of the miR-222 mimic plays a crucial role in promoting cell proliferation, migration, and invasion, and decreases cell apoptosis in HCC cells [340]. In this sense, the reduction of miR-222-5p (Figure 30) by Sorafenib exerted anti-apoptotic properties in HepG2 cells (Table 32). According to this result, miR- 222-5p has been found as one of the key biomarkers related to death in patients Doctoral Thesis Patricia de la Cruz Ojeda 256 (Figure 49). Sequencing studies revealed that miR-222-5p suppressed cell cycle and reduced cell lipid and carbon metabolism (Figure 46). However, mitochondrial functionality seemed to be significantly enriched due to the downregulation of the MT-TF and MT-CO3 transcripts. Deregulation of mitochondria and impaired respiration have been linked with HCC, in particular, the loss of mtDNA [341,342]. Therefore, the downregulation of mitochondrial components might constitute a pro-survival mechanism. Moreover, we observed a downregulation of TK and growth receptor related pathways that include AXL, IRS1, or SRC. The reduction in Sorafenib targets has been described as a potential resistance mechanism, in particular, the reduction in phosphorylation of the Ras pathway. Therefore, our results support this idea as a mechanism of plausible resistance and reduced response to Sorafenib [343]. Pro-tumoral effects of miR-222-5p were supported by the reduction of several key enzymes of metabolism. For instance, low expression of UGP2 and ENO3 have been related to poor outcome in HCC [344,345]. In addition, UGP2 has been linked to fatty acid metabolism, supporting our results that indicate that lowered lipid metabolism is related to miR-222-5p poor outcome [344]. Regarding cell cycle, one of the key regulators of cell cycle progression is RB1, which has been characterized as a target of miR-222-5p. By means of regulating RB1, miR-222-5p contributes to migration and invasion, and also to altered lipid metabolism [346]. Additionally, miR-222-5p repressed SOX9, whose downregulation during YAP signaling has been proposed as a mechanism of malignancy in HCC [347]. All in all, these findings underwrite the pro-tumoral properties of miR-222-5p during Sorafenib therapy response. 5.4.2.11 miR-375 (24 hours) Upregulation of miR-375 in response to Sorafenib is considered to be beneficial for treatment response. miR-375 inhibits tumor angiogenesis and avoids Sorafenib resistance [348]. One of the classical mechanisms governing treatment resistance is autophagy induction. miR-375 confers Sorafenib sensibility by targeting ATG14 [349,350]. Therefore, nanovector based therapies Doctoral Thesis Patricia de la Cruz Ojeda 257 that combine miR-375 and Sorafenib could be useful to increase Sorafenib effectiveness [351]. In this study, Sorafenib upregulated miR-375 (Figure 30) and increased its secretion at 24 hours (Figure 35), but we did not observe any impact in the functional studies (Table 32). miR-375 could be regulating cell migration related targets (Figure 47), such as RHOA. In liver cancer stem cells, fluid shear stress induces migration by activation of autophagy through RhoA signaling [352]. Therefore, miR-375 could be seen as an anti-tumoral miRNA that decreases pro-migratory cascades. 5.4.2.12 miR-512-3p (24 hours) Sorafenib also induced miR-512-3p downregulation in our study (24 hours, Figure 30). The expression of miR-512-3p has been shown to be increased in HCC tissues compared with adjacent non-tumor tissues obtained in patients submitted to liver resection for VHB-related HCC [353]. It has also been associated with a pro-tumoral activity characterized by cisplatin-resistant phenotype in human germ cell tumors [354]. Our functional studies showed that the administration of the miR-512-3p mimic increased cell proliferation and cell migration (Table 32). In fact, increasing expression of this miRNA could be correlated with poor prognosis in BCLC-C stage patients (Figure 49). Oxidative metabolism was one of the items controlled by miR-512-3p (Figure 48). In particular, we observed the downregulation of several ribosomal proteins in mitochondria such as MRPS22 or MRPS36, among others. MRPS31 loss has been identified as a poor outcome biomarker in HCC, behaving as a driver of malignancy and showing prognostic value [355]. This miRNA blocked mitochondrial metabolism, mitochondrial complex assembly, and, possibly as a consequence, oxidant response. For instance, Glutathione Peroxidase 3 (GPx3) has been correlated to a higher degree of cell invasiveness and tumor stage after liver resection in HCC [356]. Additionally, although in a different context, miR- 512-3p has been found to regulate oxidative damage in endothelial dysfunction [357]. Hence, mitochondrial organization and oxidative metabolism are key processes related to miR-512-3p upregulation and poor outcome after Sorafenib Doctoral Thesis Patricia de la Cruz Ojeda 264 8. CDplexes were able to encapsulate miR-200c-3p mimics at N/P ratios of 10 to efficiently deliver miR-200c-3p to liver cancer cells. The incorporation of NPs was mediated through endosomal processes. Doctoral Thesis Patricia de la Cruz Ojeda 265 BIBLIOGRAPHY Doctoral Thesis Patricia de la Cruz Ojeda 266 Doctoral Thesis Patricia de la Cruz Ojeda 267 7. BIBLIOGRAPHY 1. Fact sheets by Population-Globocan-IARC. Available online: http://globocan.iarc.fr/Pages/fact_sheets_population.aspx (accessed on Fith of April, 2022). 2. 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Doctoral Thesis Patricia de la Cruz Ojeda 296 Doctoral Thesis Patricia de la Cruz Ojeda 297 SCIENTIFIC CONTRIBUTIONS Doctoral Thesis Patricia de la Cruz Ojeda 298 Doctoral Thesis Patricia de la Cruz Ojeda 299 SCIENTIFIC CONTRIBUTIONS Publications ORIGINAL ARTICLES miR-200c-3p, miR-222-5p and miR-512-3p constitute a biomarker signature of Sorafenib effectiveness in advanced hepatocellular carcinoma. Cells. MDPI, 28/08/2022. DOI: 10.3390/cells11172673 de la Cruz-Ojeda, P; Schmid, T; Boix, L; Moreno, M; Sapena, V; Praena- Fernández, J.M; Castell, F J; Falcón-Pérez, J. M; Reig, M; Brüne, B; Gómez-Bravo, M.A; Giráldez, Á; Bruix, J; Ferrer, M.T; Muntané, J WOS (JCR) Category: Science Edition - CELL BIOLOGY Impact Factor: 7.666 Contribution: main article of mi PhD project. Exception: statistical analysis of BCLC cohort data that was performed by BCLC team Long non-coding RNA H19 as biomarker for hepatocellular carcinoma. Liver International. WILEY, 03/03/2022. ISSN 1478-3223. DOI: 10.1111/liv.15230 Rojas, Á; Gil-Gómez, A; de la Cruz-Ojeda, P; Muñoz-Hernández, R; Sánchez- Torrijos, Y; Gallego-Durán, R; Milán, R; Rico, M.C; Montero-Vallejo, R; Gato, S; Mayas-Miles, D; Ferrer, M.T; Muntané, J; Robles-Frías, M.J; Ampuero, J; Padillo, F.J; Romero-Gómez, M WOS (JCR) Category: Science Edition - GASTROENTEROLOGY & HEPATOLOGY Impact Factor: 5.825 Contribution: patient derived samples Doctoral Thesis Patricia de la Cruz Ojeda 300 MicroRNA-200c Attenuates the Tumor-Infiltrating Capacity of Macrophages. Biology. 11 - 3, pp. 349. MDPI, 22/02/2022. ISSN 2079-7737. DOI: 10.3390/biology11030349 Raue, R; Frank, A; Fuhrmann, D; de la Cruz-Ojeda P; Rösser, S; Bauer, R; Cardamone, G; Weigert, A; Nawaz Syed, S; Schmid, T; Brüne, B WOS (JCR) Category: Science Edition - BIOLOGY Impact Factor: 5.079 Contribution: miRNA target prediction PDA-Based Glyconanomicelles for Hepatocellular Carcinoma Cells Active Targeting Via Mannose and Asialoglycoprotein Receptors. ACS APPLIED BIO MATERIALS. 4 - 6, pp. 4789 - 4799. AMER CHEMICAL SOCIETY, 21/06/2021. ISSN 2576-6422. DOI: 10.1021/acsabm.0c01679 Negrete, M; Romero-Ben, E; Gutierrez-Valencia, A; Rosales-Barrios, C; Ales, E; Mena-Barragan, T; Flores, J.A.; Castillejos, M. C; de la Cruz-Ojeda, P; Navarro- Villaran, E; Cepeda-Franco, C; Khiar, N; Muntane, J Contribution: Huh7 experimental data Molecular Pathways Leading to Induction of Cell Death and Anti-Proliferative Properties by Tacrolimus and mTOR Inhibitors in Liver Cancer Cells. Cellular physiology and biochemistry. 54 – 3, pp. 457 - 473. 06/05/2020. ISSN 1015-8987. DOI: 10.33594/000000230 Navarro-Villarán, E; de la Cruz-Ojeda, P; Contreras, L; González, R; Negrete, M; Rodríguez-Hernández, M.A; Marín-Gómez, L.M; Álamo, J.M; Calvo, A; Gómez- Bravo, M.A; de la Cruz, J; Padillo, J; Muntané, J WOS (JCR) Category: Physiology Impact Factor: 5.5 Contribution: miRNA expression profiles Doctoral Thesis Patricia de la Cruz Ojeda 301 Downregulation of thioredoxin-1-dependent CD95 S-nitrosation by Sorafenib reduces liver cancer. Redox Biology. 34 – 101528, Elsevier, 04/04/2020. ISSN 2213-2317. DOI: 10.1016/j.redox.2020.101528 Gonzalez, R; Rodríguez-Hernández, M.A; Negrete, M; Ranguelova, K; Rossin, A; Choya-Foces, C; de la Cruz-Ojeda, P; Miranda-Vizuete, A; Martínez-Ruiz, A; Rius-Pérez, S; Sastre, J; Bárcena, J.A; Hueber, A; Padilla, C.A; Muntané, J WOS (JCR) Category: Biochemistry & Molecular Biology Impact Factor: 9.986 Contribution: in vivo study (together with Rodríguez-Hernández) Dose-dependent regulation of mitochondrial function and cell death pathway by sorafenib in liver cancer cells. Biochemical pharmacology. 176 - 113902, PERGAMON-ELSEVIER SCIENCE LTD, 07/03/2020. ISSN0006-2952. DOI: 10.1016/j.bcp.2020.113902 Rodríguez-Hernández, M.A; de la Cruz-Ojeda, P; Gallego, P; Navarro-Villarán, E; Staňková, P; Del Campo, J.A; Kučera, O; Elkalaf, M; Maseko, T.E; Červinková, Z; Muntané, J WOS (JCR) Category: Pharmacology & Pharmacy Impact Factor: 4.960 Contribution: mitochondrial and glycolytic assays, AMPK and autophagy pathway analysis, manuscript writing and revisions NLRP3 Inflammasome Inhibition by MCC950 in Aged Mice Improves Health via Enhanced Autophagy and PPARα Activity. The Journals of Gerontology: Series A. 75 - 8, pp. 1457 - 1464. 11/10/2019. ISSN 1079-5006. DOI: 10.1093/gerona/glz239 Marín-Aguilar, F; Castejón-Vega, B; Alcocer-Gómez, E; Lendines-Cordero, D; Cooper, M.A; de la Cruz, P; Andújar-Pulido, E; Pérez-Alegre, M; Muntané, J; Doctoral Thesis Patricia de la Cruz Ojeda 302 Pérez-Pulido, A.J; Ryffel, B; Robertson, A.B.B; Ruiz-Cabello, J; Bullón, P; Cordero, M.D Tipo de producción: Artículo científico Tipo de soporte: Revista WOS (JCR) Category: Gerontology Impact Factor: 5.236 Contribution: NLRP3 knock-down assays Two coffins and a funeral: early or late caspase activation determines two types of apoptosis induced by DNA damaging agents. Apoptosis. 3 - 22, pp. 421 - 436. Spinger, 06/12/2016. DOI: 10.1007/s10495-016-1337-z Oropesa-Ávila, M; de la Cruz-Ojeda, P; Porcuna, J; Villanueva-Paz, M; Fernández-Vega, A; de la Mata, M; de Lavera, I; Suarez Rivero, J.M; Luzón– Hidalgo, R; Álvarez-Córdoba, M; Cotán, D; Zaderenko, A.P; Cordero, M.D; Sánchez-Alcázar, J.A WOS (JCR) Category: Cell Biology Impact Factor: 3.967 Contribution: RhoA activation and in vivo microscopy assays (together with Oropesa-Ávila) REVIEWS The Role of Non-Coding RNAs in Autophagy During Carcinogenesis. Frontiers in Cell and Developmental Biology. FRONTIERS MEDIA SA,02/03/2022. DOI: 10.3389/fcell.2022.799392 de la Cruz-Ojeda, P; Flores-Campos, R; Navarro-Villarán, E; Muntané, J WOS (JCR) Category: Science Edition - CELL BIOLOGY Impact Factor: 6.684 Doctoral Thesis Patricia de la Cruz Ojeda 303 Role of Nitric Oxide in Gene Expression Regulation during Cancer: Epigenetic Modifications and Non-Coding RNAs. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES. 22 - 12, MDPI, 10/06/2021. ISSN 1422-0067. DOI: 10.3390/ijms22126264 de la Cruz-Ojeda, P; Flores-Campos, R; Dios-Barbeito, S; Navarro-Villaran, E; Muntane, J. WOS (JCR) Category: Science Edition - BIOCHEMISTRY & MOLECULAR BIOLOGY Impact Factor: 5,923 Integrated molecular signaling related to mitochondrial dysfunction and the antitumoral properties of tyrosine kinase inhibitors in cancer. Redox Biology. 36 -101510, Elsevier, 01/09/2020. ISSN 2213-2317. DOI: 10.1016/j.redox.2020.101510 Rodríguez-Hernández, M.A; de la Cruz-Ojeda, P; López-Grueso, M.J; Navarro- Villarán, E; Requejo-Aguilar, R; Castejón-Vega, B; Negrete, M; Gallego, P; Vega- Ochoa, A; Victor, V.M; Cordero, M.D; Del Campo, J.A; Bárcena, J.A; Padilla, C.A; Muntané, J WOS (JCR) Category: Biochemistry & Molecular Biology Impact Factor: 9.986 Assessing Autophagy in Archived Tissue or How to Capture Autophagic Flux from a Tissue Snapshot. Biology. 9 -3, MDPI, 21/03/2020. ISSN 2079-7737. DOI: 10.3390/biology9030059 Humbert, M; Morán, M; de la Cruz-Ojeda, P; Muntané, J; Wiedmer, T; Apostolova, N; McKenna, S.L; Velasco, G; Balduini, W; Eckhart, L; Janji, B; Sampaio-Marques, B; Ludovico, P; Žerovnik, E; Langer, R; Perren, A; Engedal, N; Tschan, M.P WOS (JCR) Category: Biology Doctoral Thesis Patricia de la Cruz Ojeda 304 Impact Factor: 3.796 Dynamic reorganization of the cytoskeleton during apoptosis: the two coffins hypothesis. International Journal of Molecular Sciences. 18 - 11, MDPI, 11/11/2017. ISSN 1422-0067. DOI: 10.3390/ijms18112393 Povea-Cabello, S; Oropesa-Ávila, M; de la Cruz-Ojeda, P; Villanueva-Paz, M; De La Mata, M; Suárez-Rivero, J.M; Álvarez-Córdoba, M; Villalón-García I; Cotán, D; Ybot-González, P; Sánchez-Alcázar, J.A WOS (JCR) Category: Chemistry, Multidisciplinary Impact Factor: 3.687 Mitochondrial dynamics in mitochondrial diseases. Diseases. 5 - 1, 23/12/2016 Suárez-Rivero, J.M; Villanueva-Paz, M; de la Cruz-Ojeda, P; de la Mata, M; Cotán, D; Oropesa-Ávila, M; de Lavera, I; Álvarez-Córdoba, M; Luzón-Hidalgo, R; Sánchez-Alcázar, J.A BOOK CHAPTERS Cytoskeleton rearrangements during the execution phase of apoptosis. Cytoskeleton. Wiley, 17/05/2017. ISSN 1949-3592. DOI: 10.5772/66865 Porcuna, J; de la Cruz-Ojeda, P; Oropesa-Ávila, M; Villanueva-Paz, M; de Lavera, I; de la Mata, M; Álvarez-Córdoba, M; Luzón–Hidalgo, R; Suárez-Rivero, J.M; Cotán, D; Sánchez-Alcázar, J.A Doctoral Thesis Patricia de la Cruz Ojeda 305 Participation in congresses and seminars XIII GEIRLI Meeting, Seville, July 2022. Oral Communication. Presenting author. The induction of peroxynitrite generation by Sorafenib plays a relevant role during mitochondrial dysfunction in liver cancer cells de la Cruz-Ojeda, P; Navarro-Villarán, E; Kučera, O; Elkalaf, M; Maseko, T; Červinková, Z; Navas, P; López-Lluch, G; Muntané, J Celebration date: 20/07/2022-22/07/2022 Organizer: Grupo Español de Investigación en Radicales Libres (GERLI) VIII International workshop on NO and cancer, Copenhagen, 2022. Oral presentation and Poster. Collaborating author. Role of GSNOR during the downregulation of Thioredoxin 1 in Sorafenib-treated liver cancer cells Ramírez, P; Navarro-Villarán, E; de la Cruz-Ojeda, P; Rizza, S; Filomeni, G; Muntané, J Celebration date: 08/06/2022-10/06/2022 Organizer: International Society for Nitric Oxide and Cancer (ISNOC) VIII International workshop on NO and cancer, Copenhagen, 2022. Keynote talk. Collaborating author. Induction of peroxynitrite generation by Sorafenib plays a relevant role during mitochondrial dysfunction in liver cancer cells Navarro-Villarán, E; de la Cruz-Ojeda, P; Kučera, O; Elkalaf, M; Maseko, T; Červinková, Z; Navas, P; López-Lluch, G; Muntané, J Celebration date: 08/06/2022-10/06/2022 Organizer: International Society for Nitric Oxide and Cancer (ISNOC) Doctoral Thesis Patricia de la Cruz Ojeda 312 Doctoral Thesis Patricia de la Cruz Ojeda 313 APPENDICES APPENDICES Appendix 1. Expression data of regulated genes by miR-122-5p. Ensembl ID Gene name Base mean log2(Fold- Change) p-value p-adj Base mean log2(Fold- Change) p-value p-adj ENSG00000099860 GADD45B 827.119 0.950 5.278E-10 1.942E-06 556.157 0.380 1.855E-02 7.703E-01 ENSG00000169688 MT1B 365.499 0.774 3.682E-06 3.426E-03 189.137 0.073 3.577E-01 9.992E-01 ENSG00000121060 TRIM25 473.269 -0.296 6.303E-02 9.990E-01 361.974 -0.750 1.480E-07 3.507E-04 ENSG00000089057 SLC23A2 486.352 -0.412 1.284E-02 9.990E-01 379.930 -0.744 3.798E-07 6.429E-04 ENSG00000135048 TMEM2 1028.584 -0.281 8.726E-02 9.990E-01 709.950 -0.653 2.653E-06 2.417E-03 ENSG00000165494 PCF11 290.539 -0.025 8.824E-01 9.990E-01 241.034 -0.681 8.326E-06 6.576E-03 ENSG00000109971 HSPA8 1262.701 -0.115 4.699E-01 9.990E-01 973.364 -0.537 2.105E-05 1.247E-02 ENSG00000189057 FAM111B 290.440 -0.318 5.446E-02 9.990E-01 231.327 -0.683 2.018E-05 1.247E-02 ENSG00000119927 GPAM 749.123 -0.471 3.963E-03 9.990E-01 527.704 -0.671 2.923E-05 1.649E-02 ENSG00000124209 RAB22A 302.234 -0.128 4.370E-01 9.990E-01 203.536 -0.658 3.530E-05 1.818E-02 ENSG00000095752 IL11 101.133 -0.409 1.328E-02 NA 79.593 -0.759 4.340E-05 1.978E-02 ENSG00000109321 AREG 529.275 -0.258 1.092E-01 9.990E-01 454.827 -0.629 4.899E-05 2.001E-02 ENSG00000168386 FILIP1L 291.617 -0.442 6.700E-03 9.990E-01 222.312 -0.651 5.428E-05 2.143E-02 ENSG00000019186 CYP24A1 117.990 -0.328 4.573E-02 9.990E-01 120.223 -0.691 1.131E-04 3.723E-02 ENSG00000188206 HNRNPU-AS1 62.197 -0.063 6.916E-01 NA 49.479 -0.711 1.252E-04 3.902E-02 ENSG00000120738 EGR1 70.086 -0.409 1.098E-02 NA 53.586 -0.683 1.872E-04 4.948E-02 ENSG00000178951 ZBTB7A 750.427 -0.197 2.208E-01 9.990E-01 673.091 -0.512 2.022E-04 5.208E-02 ENSG00000164171 ITGA2 253.603 -0.366 2.635E-02 9.990E-01 194.530 -0.637 2.246E-04 5.544E-02 ENSG00000210144 MT-TY 116.251 -0.357 2.781E-02 9.990E-01 84.760 -0.650 2.975E-04 7.049E-02 ENSG00000279789 AC120114.4 69.855 -0.192 2.196E-01 NA 42.157 -0.652 3.521E-04 7.870E-02 ENSG00000130164 LDLR 430.426 -0.329 3.736E-02 9.990E-01 284.933 -0.575 3.955E-04 8.220E-02 ENSG00000184992 BRI3BP 589.040 -0.241 1.428E-01 9.990E-01 428.762 -0.520 4.730E-04 9.340E-02 ENSG00000166068 SPRED1 109.484 -0.019 9.082E-01 9.990E-01 76.667 -0.631 5.554E-04 9.969E-02 ENSG00000139318 DUSP6 307.455 -0.154 3.471E-01 9.990E-01 242.111 -0.553 6.504E-04 1.117E-01 ENSG00000178567 EPM2AIP1 463.209 -0.343 2.823E-02 9.990E-01 336.396 -0.505 6.731E-04 1.123E-01 ENSG00000159110 IFNAR2 215.133 -0.196 2.376E-01 9.990E-01 177.541 -0.521 9.391E-04 1.483E-01 ENSG00000120675 DNAJC15 224.149 -0.049 7.706E-01 9.990E-01 194.121 -0.544 1.086E-03 1.582E-01 ENSG00000168575 SLC20A2 229.961 -0.170 3.104E-01 9.990E-01 240.901 -0.551 1.074E-03 1.582E-01 ENSG00000126773 PCNX4 201.579 -0.110 5.067E-01 9.990E-01 145.160 -0.581 1.193E-03 1.663E-01 ENSG00000268858 AL118506.1 81.981 -0.154 3.488E-01 NA 49.678 -0.600 1.248E-03 1.700E-01 ENSG00000164251 F2RL1 35.521 -0.224 1.086E-01 NA 42.172 -0.554 1.994E-03 2.250E-01 ENSG00000176438 SYNE3 84.261 -0.390 1.658E-02 NA 46.461 -0.552 2.968E-03 3.031E-01 ENSG00000006576 PHTF2 98.191 -0.199 2.297E-01 NA 67.740 -0.542 3.184E-03 3.113E-01 I-miR-122-5p (Sorafenib-Control) Transfection Control (Sorafenib-control) Appendix 2. Expression data of regulated genes by miR-200c-3p. Ensembl ID Gene name Base mean log2(Fold- Change) p-value p-adj Base mean log2(Fold- Change) p-value p-adj ENSG00000099860 GADD45B 856.575 3.148 1.231E-67 3.635E-64 556.157 0.380 1.855E-02 7.703E-01 ENSG00000169688 MT1B 150.877 4.035 5.081E-51 1.000E-47 189.137 0.073 3.577E-01 9.992E-01 ENSG00000205364 MT1M 132.002 2.439 8.718E-21 1.030E-17 192.340 0.155 1.702E-01 9.992E-01 ENSG00000275993 SIK1B 45.693 1.738 4.150E-10 1.691E-07 24.322 0.531 1.568E-03 1.967E-01 ENSG00000210077 MT-TV 216.376 1.388 7.836E-08 2.153E-05 173.938 0.338 6.237E-02 9.992E-01 ENSG00000103460 TOX3 453.941 0.973 1.458E-07 3.559E-05 325.003 0.292 4.867E-02 9.992E-01 ENSG00000204388 HSPA1B 311.691 1.070 3.934E-07 8.449E-05 302.114 0.169 3.006E-01 9.992E-01 ENSG00000132677 RHBG 810.682 0.795 1.569E-06 2.808E-04 550.386 0.331 2.023E-02 7.780E-01 ENSG00000196756 SNHG17 535.232 0.801 3.619E-06 5.857E-04 350.414 0.460 1.869E-03 2.170E-01 ENSG00000160972 PPP1R16A 300.748 0.972 8.791E-06 1.251E-03 233.439 0.381 2.461E-02 8.413E-01 ENSG00000205362 MT1A 154.314 1.046 1.290E-05 1.732E-03 87.935 0.373 3.636E-02 9.340E-01 ENSG00000198355 PIM3 2235.756 0.749 1.616E-05 2.052E-03 1505.591 0.365 7.451E-03 5.147E-01 ENSG00000135111 TBX3 1632.003 0.584 1.659E-05 2.066E-03 931.210 0.479 4.799E-05 2.001E-02 ENSG00000168209 DDIT4 281.018 0.838 3.018E-05 3.496E-03 191.002 0.487 3.219E-03 3.113E-01 ENSG00000186301 MST1P2 219.707 0.932 3.147E-05 3.554E-03 143.099 0.356 3.133E-02 8.939E-01 ENSG00000187837 HIST1H1C 1562.764 0.906 3.159E-05 3.554E-03 1156.529 0.157 3.400E-01 9.992E-01 ENSG00000157827 FMNL2 689.755 0.674 6.307E-05 6.314E-03 446.991 0.294 3.147E-02 8.940E-01 ENSG00000122085 MTERF4 305.978 0.813 6.964E-05 6.856E-03 193.567 0.158 3.114E-01 9.992E-01 ENSG00000188529 SRSF10 1316.842 0.566 7.841E-05 7.470E-03 805.400 0.321 1.245E-02 6.403E-01 ENSG00000267519 AC020916.1 41.889 1.104 8.814E-05 8.199E-03 26.090 0.220 2.126E-01 9.992E-01 ENSG00000169155 ZBTB43 265.885 0.805 9.125E-05 8.356E-03 176.862 0.396 1.749E-02 7.566E-01 ENSG00000274605 AL355338.1 109.370 0.983 1.357E-04 1.152E-02 73.643 0.301 9.401E-02 9.992E-01 ENSG00000176046 NUPR1 515.604 0.702 1.366E-04 1.152E-02 431.528 0.370 7.826E-03 5.180E-01 ENSG00000113318 MSH3 216.663 0.847 1.518E-04 1.245E-02 137.280 0.073 6.765E-01 9.992E-01 ENSG00000165416 SUGT1 893.418 0.617 1.511E-04 1.245E-02 601.514 0.198 1.047E-01 9.992E-01 ENSG00000143153 ATP1B1 3581.934 0.522 1.721E-04 1.383E-02 2520.418 0.206 7.373E-02 9.992E-01 ENSG00000272888 LINC01578 390.829 0.705 2.140E-04 1.610E-02 254.854 0.294 6.722E-02 9.992E-01 ENSG00000171970 ZNF57 33.976 1.000 2.317E-04 1.700E-02 23.273 0.119 5.076E-01 9.992E-01 ENSG00000114127 XRN1 151.073 0.876 2.398E-04 1.748E-02 122.749 0.352 5.040E-02 9.992E-01 ENSG00000197647 ZNF433 54.525 1.032 2.441E-04 1.769E-02 29.906 0.797 1.138E-05 8.425E-03 ENSG00000130529 TRPM4 44.749 1.019 2.937E-04 2.006E-02 31.005 0.388 2.748E-02 8.800E-01 ENSG00000138336 TET1 383.523 0.678 3.139E-04 2.103E-02 270.331 0.173 2.859E-01 9.992E-01 ENSG00000153914 SREK1 1517.370 0.607 3.196E-04 2.103E-02 1037.944 0.298 1.388E-02 6.687E-01 ENSG00000182809 CRIP2 137.499 0.889 3.696E-04 2.348E-02 104.342 0.197 2.793E-01 9.992E-01 ENSG00000116044 NFE2L2 2254.523 0.536 3.864E-04 2.390E-02 1355.198 0.319 1.165E-02 6.281E-01 ENSG00000204387 C6orf48 1298.937 0.568 4.207E-04 2.549E-02 809.379 0.419 7.936E-04 1.288E-01 ENSG00000185551 NR2F2 953.358 0.664 4.316E-04 2.577E-02 634.102 0.240 9.194E-02 9.992E-01 ENSG00000137204 SLC22A7 57.814 0.978 4.721E-04 2.775E-02 40.624 0.215 2.418E-01 9.992E-01 ENSG00000121067 SPOP 1553.150 0.502 5.150E-04 2.953E-02 1219.345 0.241 7.139E-02 9.992E-01 ENSG00000152382 TADA1 140.382 0.854 5.434E-04 3.057E-02 87.916 0.194 2.788E-01 9.992E-01 ENSG00000077463 SIRT6 72.518 0.943 6.391E-04 3.479E-02 58.294 0.249 1.764E-01 9.992E-01 ENSG00000197905 TEAD4 464.063 0.652 7.855E-04 4.124E-02 319.690 -0.017 9.039E-01 9.992E-01 ENSG00000108375 RNF43 900.415 0.579 9.276E-04 4.703E-02 500.043 0.446 1.497E-03 1.925E-01 ENSG00000274976 AC087588.2 33.186 0.882 9.983E-04 4.955E-02 18.771 0.274 8.623E-02 9.992E-01 ENSG00000163602 RYBP 884.182 0.548 1.039E-03 5.091E-02 660.804 0.416 6.266E-03 4.640E-01 ENSG00000198563 DDX39B 50.445 0.921 1.046E-03 5.105E-02 32.036 0.333 6.899E-02 9.992E-01 ENSG00000118246 FASTKD2 376.753 0.615 1.124E-03 5.354E-02 217.249 -0.058 7.104E-01 9.992E-01 ENSG00000153140 CETN3 2430.659 0.524 1.150E-03 5.456E-02 1722.011 0.213 9.374E-02 9.992E-01 ENSG00000175575 PAAF1 159.239 0.754 1.215E-03 5.688E-02 113.662 0.208 2.144E-01 9.992E-01 ENSG00000082438 COBLL1 606.761 0.568 1.218E-03 5.688E-02 413.744 0.132 3.393E-01 9.992E-01 ENSG00000245848 CEBPA 1193.792 0.523 1.212E-03 5.688E-02 725.931 0.252 5.182E-02 9.992E-01 ENSG00000081913 PHLPP1 260.444 0.679 1.243E-03 5.757E-02 187.667 0.184 2.292E-01 9.992E-01 ENSG00000102710 SUPT20H 346.186 0.664 1.266E-03 5.818E-02 205.102 0.283 8.124E-02 9.992E-01 ENSG00000115718 PROC 596.740 0.541 1.383E-03 6.212E-02 377.204 0.184 1.799E-01 9.992E-01 ENSG00000171729 TMEM51 499.433 0.611 1.557E-03 6.664E-02 320.638 0.180 2.495E-01 9.992E-01 ENSG00000189046 ALKBH2 176.602 0.810 1.568E-03 6.688E-02 133.409 0.072 6.735E-01 9.992E-01 ENSG00000120694 HSPH1 1569.327 0.517 1.626E-03 6.812E-02 1084.010 0.158 2.390E-01 9.992E-01 ENSG00000163516 ANKZF1 246.999 0.673 1.710E-03 7.062E-02 163.355 0.249 1.204E-01 9.992E-01 ENSG00000168564 CDKN2AIP 182.576 0.736 1.759E-03 7.191E-02 121.578 0.190 2.724E-01 9.992E-01 ENSG00000183337 BCOR 325.442 0.703 1.768E-03 7.203E-02 233.971 0.163 2.845E-01 9.992E-01 ENSG00000129484 PARP2 307.236 0.641 1.804E-03 7.248E-02 216.072 0.104 4.919E-01 9.992E-01 ENSG00000120616 EPC1 743.153 0.559 1.831E-03 7.331E-02 538.288 0.365 3.396E-03 3.168E-01 ENSG00000124177 CHD6 467.537 0.674 1.853E-03 7.393E-02 383.736 0.323 2.904E-02 8.861E-01 I-miR-200c-3p (Sorafenib-Control) Transfection Control (Sorafenib-control) ENSG00000171227 TMEM37 623.056 0.682 1.918E-03 7.603E-02 384.189 0.256 9.188E-02 9.992E-01 ENSG00000165030 NFIL3 448.290 0.556 2.015E-03 7.882E-02 309.309 0.350 2.116E-02 7.869E-01 ENSG00000186204 CYP4F12 63.061 0.864 2.045E-03 7.948E-02 41.722 0.129 4.869E-01 9.992E-01 ENSG00000067606 PRKCZ 224.581 0.670 2.268E-03 8.615E-02 162.044 0.103 5.658E-01 9.992E-01 ENSG00000068120 COASY 678.313 0.549 2.337E-03 8.820E-02 454.750 0.334 1.865E-02 7.703E-01 ENSG00000103245 NARFL 61.048 0.826 2.653E-03 9.763E-02 42.053 0.183 3.244E-01 9.992E-01 ENSG00000188290 HES4 213.886 0.751 2.738E-03 9.853E-02 109.974 0.295 1.016E-01 9.992E-01 ENSG00000102390 PBDC1 411.876 0.578 2.749E-03 9.853E-02 322.286 0.276 4.911E-02 9.992E-01 ENSG00000198408 MGEA5 505.852 0.550 2.712E-03 9.853E-02 319.967 0.395 7.517E-03 5.147E-01 ENSG00000116717 GADD45A 546.253 0.510 2.778E-03 9.915E-02 416.814 0.385 6.748E-03 4.845E-01 ENSG00000128228 SDF2L1 768.675 0.568 2.799E-03 9.951E-02 496.321 0.082 5.623E-01 9.992E-01 ENSG00000087074 PPP1R15A 156.907 0.706 2.848E-03 1.006E-01 128.727 0.498 5.760E-03 4.460E-01 ENSG00000174953 DHX36 979.757 0.517 2.906E-03 1.013E-01 635.854 0.118 4.219E-01 9.992E-01 ENSG00000107554 DNMBP 110.524 0.769 2.931E-03 1.018E-01 84.908 0.129 4.770E-01 9.992E-01 ENSG00000197329 PELI1 54.899 0.822 3.061E-03 1.048E-01 47.235 -0.096 6.069E-01 9.992E-01 ENSG00000129347 KRI1 174.728 0.687 3.091E-03 1.055E-01 116.665 0.268 1.285E-01 9.992E-01 ENSG00000072682 P4HA2 293.765 0.678 3.141E-03 1.069E-01 179.176 0.160 3.106E-01 9.992E-01 ENSG00000126778 SIX1 276.395 0.584 3.302E-03 1.106E-01 187.172 0.302 5.266E-02 9.992E-01 ENSG00000251562 MALAT1 25480.818 0.503 3.461E-03 1.141E-01 18181.725 0.122 3.560E-01 9.992E-01 ENSG00000143921 ABCG8 56.616 0.813 3.527E-03 1.157E-01 32.435 0.331 7.116E-02 9.992E-01 ENSG00000182749 PAQR7 114.208 0.761 3.677E-03 1.197E-01 58.747 -0.199 2.837E-01 9.992E-01 ENSG00000214753 HNRNPUL2 631.085 0.603 3.695E-03 1.198E-01 383.912 0.060 6.714E-01 9.992E-01 ENSG00000145703 IQGAP2 913.711 0.512 3.701E-03 1.198E-01 589.530 -0.014 9.211E-01 9.992E-01 ENSG00000118369 USP35 43.962 0.814 3.822E-03 1.219E-01 33.577 0.131 4.769E-01 9.992E-01 ENSG00000162664 ZNF326 569.566 0.551 3.841E-03 1.220E-01 351.606 0.121 4.202E-01 9.992E-01 ENSG00000153094 BCL2L11 236.135 0.644 3.867E-03 1.225E-01 140.540 0.432 1.131E-02 6.232E-01 ENSG00000164180 TMEM161B 221.832 0.689 3.932E-03 1.235E-01 136.321 0.114 4.963E-01 9.992E-01 ENSG00000184897 H1FX 1001.821 0.535 4.041E-03 1.266E-01 604.391 0.363 4.849E-03 4.013E-01 ENSG00000140386 SCAPER 223.570 0.704 4.067E-03 1.268E-01 124.668 0.053 7.552E-01 9.992E-01 ENSG00000170802 FOXN2 116.143 0.757 4.619E-03 1.381E-01 83.526 0.204 2.625E-01 9.992E-01 ENSG00000167081 PBX3 268.593 0.616 4.716E-03 1.407E-01 193.073 0.239 1.422E-01 9.992E-01 ENSG00000149262 INTS4 129.566 0.711 4.809E-03 1.413E-01 84.962 -0.087 6.300E-01 9.992E-01 ENSG00000196208 GREB1 418.071 0.520 4.900E-03 1.427E-01 240.691 0.307 4.129E-02 9.525E-01 ENSG00000119844 AFTPH 389.390 0.532 5.387E-03 1.541E-01 251.844 0.162 2.686E-01 9.992E-01 ENSG00000267296 CEBPA-AS1 77.895 0.751 5.759E-03 1.619E-01 58.295 -0.003 9.864E-01 9.995E-01 ENSG00000175745 NR2F1 730.653 0.512 5.773E-03 1.619E-01 426.707 0.134 3.313E-01 9.992E-01 ENSG00000160888 IER2 824.639 0.546 5.826E-03 1.623E-01 584.136 0.181 1.770E-01 9.992E-01 ENSG00000097096 SYDE2 39.988 0.773 6.012E-03 1.655E-01 31.510 0.328 7.163E-02 9.992E-01 ENSG00000170439 METTL7B 72.662 0.761 6.106E-03 1.670E-01 51.201 0.161 3.825E-01 9.992E-01 ENSG00000141391 PRELID3A 54.358 0.769 6.207E-03 1.680E-01 30.540 -0.128 4.849E-01 9.992E-01 ENSG00000145390 USP53 196.821 0.659 6.381E-03 1.709E-01 117.455 0.455 1.286E-02 6.407E-01 ENSG00000011376 LARS2 176.313 0.610 6.479E-03 1.724E-01 100.427 -0.121 4.885E-01 9.992E-01 ENSG00000278909 AC007608.4 430.924 0.642 6.562E-03 1.734E-01 282.080 0.490 4.374E-03 3.728E-01 ENSG00000151135 TMEM263 291.700 0.550 7.213E-03 1.864E-01 203.857 0.077 6.139E-01 9.992E-01 ENSG00000103168 TAF1C 222.281 0.579 7.522E-03 1.923E-01 137.947 0.175 2.759E-01 9.992E-01 ENSG00000100150 DEPDC5 33.622 0.749 7.782E-03 1.964E-01 22.541 0.419 1.808E-02 7.636E-01 ENSG00000169249 ZRSR2 87.195 0.733 7.919E-03 1.995E-01 65.773 0.314 8.583E-02 9.992E-01 ENSG00000060566 CREB3L3 123.744 0.726 8.021E-03 2.012E-01 61.490 0.489 8.412E-03 5.370E-01 ENSG00000146776 ATXN7L1 66.542 0.721 8.014E-03 2.012E-01 58.033 0.145 4.292E-01 9.992E-01 ENSG00000237149 ZNF503-AS2 79.260 0.734 8.735E-03 2.144E-01 50.520 0.215 2.478E-01 9.992E-01 ENSG00000105755 ETHE1 306.004 0.550 8.767E-03 2.144E-01 170.835 0.261 9.862E-02 9.992E-01 ENSG00000158528 PPP1R9A 460.642 0.527 9.125E-03 2.191E-01 314.760 0.108 4.966E-01 9.992E-01 ENSG00000166140 ZFYVE19 98.151 0.713 9.249E-03 2.212E-01 68.683 0.272 1.304E-01 9.992E-01 ENSG00000214595 EML6 198.944 0.673 9.369E-03 2.231E-01 114.751 0.090 6.198E-01 9.992E-01 ENSG00000171723 GPHN 94.995 0.703 9.674E-03 2.272E-01 71.986 -0.026 8.853E-01 9.992E-01 ENSG00000040487 PQLC2 86.414 0.678 9.720E-03 2.278E-01 49.518 0.188 3.126E-01 9.992E-01 ENSG00000224272 AC131097.3 68.768 0.717 9.852E-03 2.300E-01 33.239 0.092 6.159E-01 9.992E-01 ENSG00000111727 HCFC2 45.467 0.726 9.928E-03 2.304E-01 43.845 -0.016 9.323E-01 9.992E-01 ENSG00000073050 XRCC1 246.506 0.622 1.016E-02 2.326E-01 178.149 0.209 2.200E-01 9.992E-01 ENSG00000247400 DNAJC3-AS1 126.332 0.671 1.029E-02 2.347E-01 69.728 0.197 2.790E-01 9.992E-01 ENSG00000094631 HDAC6 223.871 0.566 1.043E-02 2.359E-01 130.659 0.069 6.778E-01 9.992E-01 ENSG00000180423 HARBI1 33.617 0.713 1.047E-02 2.361E-01 16.232 -0.113 5.019E-01 9.992E-01 ENSG00000198382 UVRAG 275.983 0.564 1.055E-02 2.361E-01 192.520 0.441 7.150E-03 5.006E-01 ENSG00000173531 MST1 347.314 0.531 1.061E-02 2.362E-01 206.096 0.409 7.982E-03 5.253E-01 ENSG00000163032 VSNL1 319.121 0.507 1.091E-02 2.400E-01 234.059 -0.010 9.442E-01 9.992E-01 ENSG00000067836 ROGDI 155.058 0.613 1.095E-02 2.400E-01 102.742 0.081 6.442E-01 9.992E-01 ENSG00000144655 CSRNP1 142.747 0.672 1.102E-02 2.404E-01 89.762 0.325 7.148E-02 9.992E-01 ENSG00000148335 NTMT1 209.408 0.621 1.142E-02 2.442E-01 185.595 0.081 6.420E-01 9.992E-01 ENSG00000237729 AC002075.2 33.745 0.687 1.152E-02 2.451E-01 22.640 0.048 7.829E-01 9.992E-01 ENSG00000109911 ELP4 75.119 0.686 1.167E-02 2.462E-01 39.150 -0.006 9.724E-01 9.992E-01 ENSG00000149503 INCENP 321.191 0.504 1.212E-02 2.524E-01 228.041 0.093 5.802E-01 9.992E-01 ENSG00000161835 GRASP 39.701 0.704 1.237E-02 2.537E-01 17.427 0.149 3.775E-01 9.992E-01 ENSG00000179456 ZBTB18 56.648 0.703 1.256E-02 2.549E-01 34.546 0.111 5.469E-01 9.992E-01 ENSG00000169727 GPS1 787.424 0.510 1.280E-02 2.573E-01 475.577 0.102 4.289E-01 9.992E-01 ENSG00000016864 GLT8D1 202.458 0.537 1.304E-02 2.599E-01 146.459 0.303 6.769E-02 9.992E-01 ENSG00000172602 RND1 34.714 0.687 1.314E-02 2.608E-01 18.294 0.252 1.203E-01 9.992E-01 ENSG00000100764 PSMC1 762.251 0.548 1.346E-02 2.639E-01 417.745 0.079 6.015E-01 9.992E-01 ENSG00000156239 N6AMT1 52.759 0.687 1.370E-02 2.646E-01 46.290 0.047 8.018E-01 9.992E-01 ENSG00000102996 MMP15 117.518 0.632 1.367E-02 2.646E-01 61.607 -0.134 4.617E-01 9.992E-01 ENSG00000139546 TARBP2 186.274 0.620 1.369E-02 2.646E-01 127.045 0.097 5.613E-01 9.992E-01 ENSG00000110172 CHORDC1 320.046 0.542 1.405E-02 2.659E-01 221.404 0.033 8.252E-01 9.992E-01 ENSG00000119720 NRDE2 210.710 0.522 1.400E-02 2.659E-01 144.786 0.260 1.099E-01 9.992E-01 ENSG00000116117 PARD3B 104.087 0.624 1.448E-02 2.697E-01 79.187 0.054 7.634E-01 9.992E-01 ENSG00000235169 SMIM1 125.129 0.615 1.455E-02 2.704E-01 85.326 0.142 4.276E-01 9.992E-01 ENSG00000205323 SARNP 95.561 0.657 1.463E-02 2.708E-01 72.063 0.225 2.172E-01 9.992E-01 ENSG00000140548 ZNF710 73.966 0.683 1.509E-02 2.750E-01 52.413 0.139 4.530E-01 9.992E-01 ENSG00000124216 SNAI1 35.493 0.661 1.534E-02 2.754E-01 26.061 0.310 8.091E-02 9.992E-01 ENSG00000186529 CYP4F3 98.496 0.642 1.527E-02 2.754E-01 70.372 0.394 3.125E-02 8.939E-01 ENSG00000164414 SLC35A1 126.119 0.598 1.617E-02 2.830E-01 56.011 0.158 3.888E-01 9.992E-01 ENSG00000148219 ASTN2 103.973 0.628 1.628E-02 2.831E-01 67.198 0.045 8.024E-01 9.992E-01 ENSG00000119446 RBM18 172.001 0.567 1.649E-02 2.832E-01 110.966 0.144 4.026E-01 9.992E-01 ENSG00000273142 AC073335.2 33.852 0.668 1.700E-02 2.864E-01 17.213 0.153 3.661E-01 9.992E-01 ENSG00000163214 DHX57 180.167 0.537 1.703E-02 2.866E-01 100.033 0.214 2.393E-01 9.992E-01 ENSG00000117408 IPO13 48.571 0.667 1.739E-02 2.898E-01 39.519 -0.010 9.563E-01 9.992E-01 ENSG00000187634 SAMD11 72.934 0.667 1.767E-02 2.913E-01 41.972 0.393 3.462E-02 9.212E-01 ENSG00000101049 SGK2 159.262 0.551 1.787E-02 2.927E-01 93.042 0.349 4.710E-02 9.986E-01 ENSG00000198929 NOS1AP 132.521 0.597 1.793E-02 2.929E-01 89.573 0.303 9.086E-02 9.992E-01 ENSG00000069399 BCL3 304.593 0.522 1.802E-02 2.933E-01 180.604 0.459 3.204E-03 3.113E-01 ENSG00000224597 SVIL-AS1 147.126 0.581 1.824E-02 2.944E-01 112.775 0.133 4.477E-01 9.992E-01 ENSG00000141556 TBCD 404.072 0.564 1.908E-02 3.007E-01 249.815 0.119 4.656E-01 9.992E-01 ENSG00000176371 ZSCAN2 200.283 0.516 1.906E-02 3.007E-01 115.943 0.174 3.174E-01 9.992E-01 ENSG00000004766 VPS50 37.931 0.658 1.957E-02 3.051E-01 37.108 -0.073 6.937E-01 9.992E-01 ENSG00000198551 ZNF627 34.951 0.638 1.953E-02 3.051E-01 29.421 0.233 2.017E-01 9.992E-01 ENSG00000205212 CCDC144NL 30.565 0.650 1.969E-02 3.057E-01 18.387 0.244 1.549E-01 9.992E-01 ENSG00000167702 KIFC2 37.926 0.656 1.980E-02 3.057E-01 41.303 -0.006 9.746E-01 9.992E-01 ENSG00000133104 SPART 99.985 0.597 2.067E-02 3.113E-01 64.213 -0.001 9.968E-01 9.999E-01 ENSG00000033170 FUT8 80.948 0.630 2.105E-02 3.142E-01 48.407 -0.024 8.987E-01 9.992E-01 ENSG00000173681 BCLAF3 59.142 0.640 2.159E-02 3.189E-01 37.267 0.141 4.476E-01 9.992E-01 ENSG00000081923 ATP8B1 50.512 0.639 2.164E-02 3.191E-01 27.799 0.329 6.569E-02 9.992E-01 ENSG00000139998 RAB15 216.671 0.513 2.263E-02 3.257E-01 147.399 0.004 9.814E-01 9.992E-01 ENSG00000066827 ZFAT 44.376 0.639 2.310E-02 3.296E-01 16.482 0.241 1.455E-01 9.992E-01 ENSG00000168916 ZNF608 44.117 0.635 2.407E-02 3.349E-01 22.410 0.002 9.912E-01 9.995E-01 ENSG00000138050 THUMPD2 148.112 0.543 2.391E-02 3.349E-01 72.763 0.091 6.174E-01 9.992E-01 ENSG00000130158 DOCK6 88.767 0.584 2.446E-02 3.362E-01 52.008 0.260 1.618E-01 9.992E-01 ENSG00000166439 RNF169 275.310 0.504 2.472E-02 3.376E-01 209.329 0.072 6.419E-01 9.992E-01 ENSG00000125772 GPCPD1 256.868 0.532 2.540E-02 3.430E-01 143.953 0.396 1.811E-02 7.636E-01 ENSG00000184979 USP18 37.234 0.623 2.561E-02 3.446E-01 35.038 0.238 1.965E-01 9.992E-01 ENSG00000059728 MXD1 118.245 0.597 2.690E-02 3.559E-01 85.907 0.357 4.322E-02 9.716E-01 ENSG00000109103 UNC119 74.846 0.607 2.723E-02 3.593E-01 59.768 0.226 2.182E-01 9.992E-01 ENSG00000134899 ERCC5 146.572 0.546 2.737E-02 3.600E-01 111.779 -0.247 1.453E-01 9.992E-01 ENSG00000196456 ZNF775 35.712 0.617 2.769E-02 3.620E-01 19.015 0.272 1.159E-01 9.992E-01 ENSG00000169683 LRRC45 43.980 0.617 2.769E-02 3.620E-01 24.351 0.047 7.887E-01 9.992E-01 ENSG00000046647 GEMIN8 41.261 0.619 2.801E-02 3.629E-01 29.194 0.134 4.545E-01 9.992E-01 ENSG00000162924 REL 142.828 0.542 2.795E-02 3.629E-01 102.767 0.149 4.179E-01 9.992E-01 ENSG00000100116 GCAT 117.587 0.552 2.872E-02 3.682E-01 79.705 0.286 1.108E-01 9.992E-01 ENSG00000109099 PMP22 171.674 0.569 2.884E-02 3.683E-01 88.887 0.129 4.854E-01 9.992E-01 ENSG00000171174 RBKS 106.284 0.562 2.919E-02 3.694E-01 59.571 -0.031 8.635E-01 9.992E-01 ENSG00000168952 STXBP6 195.996 0.519 2.931E-02 3.694E-01 119.690 0.122 4.724E-01 9.992E-01 ENSG00000111670 GNPTAB 239.035 0.538 2.985E-02 3.715E-01 162.974 0.039 8.212E-01 9.992E-01 ENSG00000169692 AGPAT2 42.829 0.606 3.038E-02 3.755E-01 36.207 -0.075 6.842E-01 9.992E-01 ENSG00000165175 MID1IP1 58.883 0.600 3.188E-02 3.821E-01 37.077 0.198 2.849E-01 9.992E-01 ENSG00000104957 CCDC130 220.559 0.517 3.257E-02 3.840E-01 131.911 0.112 5.201E-01 9.992E-01 ENSG00000113916 BCL6 138.393 0.535 3.269E-02 3.847E-01 88.163 0.418 2.016E-02 7.780E-01 ENSG00000197857 ZNF44 121.340 0.554 3.302E-02 3.855E-01 74.752 0.262 1.545E-01 9.992E-01 ENSG00000121989 ACVR2A 113.958 0.559 3.308E-02 3.856E-01 77.538 0.243 1.866E-01 9.992E-01 ENSG00000226742 HSBP1L1 111.201 0.544 3.338E-02 3.885E-01 84.070 0.029 8.737E-01 9.992E-01 ENSG00000011243 AKAP8L 42.749 0.594 3.381E-02 3.912E-01 27.128 0.086 6.364E-01 9.992E-01 ENSG00000120725 SIL1 145.458 0.551 3.529E-02 4.020E-01 73.593 0.124 4.906E-01 9.992E-01 ENSG00000188051 TMEM221 34.866 0.591 3.577E-02 4.063E-01 28.360 0.020 9.105E-01 9.992E-01 ENSG00000184678 HIST2H2BE 32.719 0.553 3.642E-02 4.105E-01 18.752 -0.202 2.428E-01 9.992E-01 ENSG00000054690 PLEKHH1 33.228 0.583 3.704E-02 4.140E-01 23.038 0.017 9.244E-01 9.992E-01 ENSG00000106384 MOGAT3 176.778 0.528 3.704E-02 4.140E-01 117.133 0.037 8.239E-01 9.992E-01 ENSG00000105483 CARD8 102.469 0.554 3.737E-02 4.160E-01 73.444 0.022 9.027E-01 9.992E-01 ENSG00000173212 MAB21L3 48.138 0.583 3.768E-02 4.176E-01 27.110 0.032 8.617E-01 9.992E-01 ENSG00000011422 PLAUR 52.453 0.582 3.760E-02 4.176E-01 33.563 0.069 7.047E-01 9.992E-01 ENSG00000171163 ZNF692 53.259 0.585 3.782E-02 4.177E-01 37.511 -0.069 7.073E-01 9.992E-01 ENSG00000130173 ANGPTL8 117.716 0.568 3.898E-02 4.211E-01 68.078 0.122 5.076E-01 9.992E-01 ENSG00000134324 LPIN1 103.579 0.563 3.942E-02 4.221E-01 79.581 0.144 4.234E-01 9.992E-01 ENSG00000177854 TMEM187 44.786 0.577 4.031E-02 4.256E-01 28.809 0.019 9.157E-01 9.992E-01 ENSG00000131171 SH3BGRL 41.368 0.577 4.036E-02 4.256E-01 19.418 -0.050 7.688E-01 9.992E-01 ENSG00000184178 SCFD2 131.522 0.503 4.028E-02 4.256E-01 81.719 0.075 6.748E-01 9.992E-01 ENSG00000099821 POLRMT 126.405 0.537 4.051E-02 4.262E-01 86.425 -0.054 7.631E-01 9.992E-01 ENSG00000258457 AL132780.2 47.008 0.576 4.083E-02 4.266E-01 32.602 0.258 1.558E-01 9.992E-01 ENSG00000157077 ZFYVE9 138.160 0.529 4.113E-02 4.277E-01 107.812 0.075 6.652E-01 9.992E-01 ENSG00000104375 STK3 44.296 0.570 4.280E-02 4.368E-01 44.829 0.197 2.890E-01 9.992E-01 ENSG00000120054 CPN1 97.075 0.514 4.421E-02 4.415E-01 66.412 -0.117 5.184E-01 9.992E-01 ENSG00000120370 GORAB 39.109 0.557 4.480E-02 4.451E-01 25.747 0.299 9.736E-02 9.992E-01 ENSG00000243364 EFNA4 79.668 0.549 4.554E-02 4.499E-01 55.258 -0.116 5.313E-01 9.992E-01 ENSG00000023892 DEF6 68.112 0.560 4.605E-02 4.525E-01 47.428 0.083 6.546E-01 9.992E-01 ENSG00000105829 BET1 77.448 0.534 4.672E-02 4.546E-01 61.382 0.259 1.629E-01 9.992E-01 ENSG00000168874 ATOH8 67.782 0.541 4.728E-02 4.569E-01 43.714 0.157 3.994E-01 9.992E-01 ENSG00000174989 FBXW8 47.188 0.552 4.877E-02 4.650E-01 22.272 0.356 4.396E-02 9.762E-01 ENSG00000069667 RORA 66.066 0.533 4.880E-02 4.650E-01 48.957 0.140 4.512E-01 9.992E-01 ENSG00000125846 ZNF133 101.594 0.521 4.891E-02 4.656E-01 64.503 0.446 1.589E-02 7.130E-01 ENSG00000115137 DNAJC27 34.053 0.536 4.942E-02 4.665E-01 22.139 -0.154 3.892E-01 9.992E-01 ENSG00000186020 ZNF529 37.509 0.541 4.958E-02 4.668E-01 29.882 0.061 7.373E-01 9.992E-01 ENSG00000121671 CRY2 102.336 0.504 4.972E-02 4.668E-01 71.719 0.200 2.757E-01 9.992E-01 ENSG00000188785 ZNF548 59.294 0.538 5.023E-02 4.685E-01 29.904 0.421 2.105E-02 7.865E-01 ENSG00000108239 TBC1D12 73.454 0.529 5.060E-02 4.696E-01 58.109 0.120 5.121E-01 9.992E-01 ENSG00000136840 ST6GALNAC4 141.247 0.513 5.059E-02 4.696E-01 88.126 0.232 1.960E-01 9.992E-01 ENSG00000196646 ZNF136 37.631 0.548 5.176E-02 4.735E-01 29.398 0.222 2.150E-01 9.992E-01 ENSG00000113070 HBEGF 48.405 0.546 5.209E-02 4.738E-01 29.364 0.135 4.586E-01 9.992E-01 ENSG00000102743 SLC25A15 55.799 0.538 5.251E-02 4.753E-01 43.645 0.164 3.762E-01 9.992E-01 ENSG00000169507 SLC38A11 34.926 0.543 5.303E-02 4.771E-01 18.326 -0.009 9.543E-01 9.992E-01 ENSG00000172331 BPGM 32.836 0.536 5.539E-02 4.857E-01 21.816 -0.155 3.852E-01 9.992E-01 ENSG00000106100 NOD1 39.228 0.504 5.584E-02 4.881E-01 25.097 0.137 4.455E-01 9.992E-01 ENSG00000196843 ARID5A 70.931 0.532 5.716E-02 4.965E-01 47.232 -0.203 2.744E-01 9.992E-01 ENSG00000114745 GORASP1 94.177 0.514 5.825E-02 4.999E-01 60.410 0.245 1.801E-01 9.992E-01 ENSG00000087116 ADAMTS2 43.264 0.531 5.918E-02 5.044E-01 26.610 0.080 6.555E-01 9.992E-01 ENSG00000130270 ATP8B3 46.988 0.530 5.990E-02 5.066E-01 32.525 0.015 9.333E-01 9.992E-01 ENSG00000109323 MANBA 89.174 0.513 5.978E-02 5.066E-01 70.087 -0.192 3.019E-01 9.992E-01 ENSG00000146232 NFKBIE 105.159 0.505 6.029E-02 5.083E-01 60.035 0.147 4.262E-01 9.992E-01 ENSG00000162129 CLPB 77.398 0.516 6.102E-02 5.123E-01 62.453 0.283 1.222E-01 9.992E-01 ENSG00000132256 TRIM5 51.309 0.525 6.224E-02 5.160E-01 34.625 -0.270 1.461E-01 9.992E-01 ENSG00000149582 TMEM25 41.217 0.521 6.422E-02 5.272E-01 28.448 -0.041 8.194E-01 9.992E-01 ENSG00000189057 FAM111B 368.557 -0.360 6.473E-02 5.279E-01 231.327 -0.683 2.018E-05 1.247E-02 ENSG00000215067 ALOX12-AS1 45.722 0.519 6.506E-02 5.286E-01 26.697 -0.081 6.496E-01 9.992E-01 ENSG00000239382 ALKBH6 56.164 0.513 6.778E-02 5.374E-01 39.248 -0.181 3.303E-01 9.992E-01 ENSG00000175895 PLEKHF2 40.103 0.514 6.788E-02 5.378E-01 44.350 -0.050 7.863E-01 9.992E-01 ENSG00000112367 FIG4 39.292 0.509 6.831E-02 5.404E-01 34.253 0.206 2.661E-01 9.992E-01 ENSG00000184903 IMMP2L 49.095 0.509 7.073E-02 5.454E-01 29.543 0.031 8.651E-01 9.992E-01 ENSG00000132563 REEP2 49.935 0.506 7.171E-02 5.476E-01 31.905 0.158 3.885E-01 9.992E-01 ENSG00000143995 MEIS1 30.631 0.503 7.191E-02 5.478E-01 20.914 0.234 1.797E-01 9.992E-01 ENSG00000240616 RPS6P25 42.573 0.501 7.533E-02 5.592E-01 31.196 0.086 6.350E-01 9.992E-01 ENSG00000120675 DNAJC15 329.355 -0.299 1.309E-01 6.615E-01 194.121 -0.544 1.086E-03 1.582E-01 ENSG00000006576 PHTF2 96.604 -0.172 5.086E-01 8.956E-01 67.740 -0.542 3.184E-03 3.113E-01 Appendix 3. Expression data of regulated genes by miR-505-5p. Ensembl ID Gene name Base mean log2(Fold- Change) p-value p-adj Base mean log2(Fold- Change) p-value p-adj ENSG00000169688 MT1B 213.5455 4.7089 3.633E-67 4.454E-63 189.1371 0.0729 3.577E-01 9.992E-01 ENSG00000205364 MT1M 223.1414 3.2568 1.985E-33 4.867E-30 192.3396 0.1554 1.702E-01 9.992E-01 ENSG00000275993 SIK1B 33.4588 2.0550 2.846E-12 2.493E-09 24.3219 0.5312 1.568E-03 1.967E-01 ENSG00000142178 SIK1 38.3365 2.0249 6.172E-12 4.729E-09 16.5574 0.6049 1.008E-04 3.529E-02 ENSG00000099860 GADD45B 866.1908 1.6412 2.647E-08 1.047E-05 556.1571 0.3797 1.855E-02 7.703E-01 ENSG00000164683 HEY1 38.8849 1.3787 2.977E-06 6.887E-04 20.5908 0.1918 2.735E-01 9.992E-01 ENSG00000199377 RNU5F-1 47.5876 1.3211 4.738E-06 1.056E-03 28.4446 0.3097 8.710E-02 9.992E-01 ENSG00000210077 MT-TV 146.9428 1.2227 8.020E-06 1.639E-03 173.9377 0.3381 6.237E-02 9.992E-01 ENSG00000197647 ZNF433 31.6999 1.3099 8.656E-06 1.712E-03 29.9063 0.7973 1.138E-05 8.425E-03 ENSG00000171970 ZNF57 52.5764 1.2947 1.115E-05 2.135E-03 23.2734 0.1189 5.076E-01 9.992E-01 ENSG00000105697 HAMP 1400.6073 0.7752 2.139E-05 3.642E-03 980.4307 0.4502 1.732E-04 4.773E-02 ENSG00000171448 ZBTB26 45.2798 1.2310 2.264E-05 3.798E-03 29.5093 0.3554 5.059E-02 9.992E-01 ENSG00000187634 SAMD11 56.5565 1.2351 2.858E-05 4.551E-03 41.9718 0.3926 3.462E-02 9.212E-01 ENSG00000198355 PIM3 1977.9478 0.7707 6.045E-05 8.423E-03 1505.5912 0.3645 7.451E-03 5.147E-01 ENSG00000081923 ATP8B1 44.9792 1.0828 2.276E-04 2.568E-02 27.7990 0.3290 6.569E-02 9.992E-01 ENSG00000175906 ARL4D 139.2052 0.9286 2.520E-04 2.784E-02 96.2835 0.4885 6.831E-03 4.875E-01 ENSG00000163602 RYBP 924.7038 0.6742 4.850E-04 4.997E-02 660.8043 0.4159 6.266E-03 4.640E-01 ENSG00000168209 DDIT4 318.9034 0.8742 5.056E-04 5.123E-02 191.0023 0.4870 3.219E-03 3.113E-01 ENSG00000196756 SNHG17 507.0970 0.6914 5.187E-04 5.213E-02 350.4137 0.4597 1.869E-03 2.170E-01 ENSG00000166886 NAB2 81.7169 0.9855 5.879E-04 5.767E-02 39.0018 0.1583 3.938E-01 9.992E-01 ENSG00000188186 LAMTOR4 225.4741 0.8518 6.542E-04 6.218E-02 151.4520 0.2284 1.644E-01 9.992E-01 ENSG00000169155 ZBTB43 270.9406 0.7404 7.856E-04 7.082E-02 176.8622 0.3959 1.749E-02 7.566E-01 ENSG00000215154 AC141586.1 71.2429 0.9268 8.462E-04 7.411E-02 39.8773 0.1881 3.111E-01 9.992E-01 ENSG00000179456 ZBTB18 50.3096 0.9602 9.858E-04 8.512E-02 34.5458 0.1106 5.469E-01 9.992E-01 ENSG00000116044 NFE2L2 2030.3089 0.5901 1.028E-03 8.692E-02 1355.1978 0.3187 1.165E-02 6.281E-01 ENSG00000205362 MT1A 126.1553 0.8066 1.114E-03 9.264E-02 87.9352 0.3732 3.636E-02 9.340E-01 ENSG00000176046 NUPR1 448.6883 0.7463 1.188E-03 9.520E-02 431.5281 0.3701 7.826E-03 5.180E-01 ENSG00000272888 LINC01578 309.6899 0.8054 1.260E-03 9.877E-02 254.8541 0.2943 6.722E-02 9.992E-01 ENSG00000224032 EPB41L4A-AS1 359.1371 0.7430 1.265E-03 9.877E-02 296.9656 0.3276 3.007E-02 8.861E-01 ENSG00000198804 MT-CO1 17941.5859 0.5186 1.380E-03 1.051E-01 13625.0767 0.2994 9.881E-03 5.915E-01 ENSG00000134851 TMEM165 282.0471 0.6948 1.433E-03 1.078E-01 200.5711 0.1261 4.346E-01 9.992E-01 ENSG00000126603 GLIS2 43.2165 0.9346 1.520E-03 1.116E-01 31.2262 0.2284 2.122E-01 9.992E-01 ENSG00000248049 UBA6-AS1 55.4127 0.8999 1.786E-03 1.251E-01 34.6194 0.3020 1.032E-01 9.992E-01 ENSG00000163449 TMEM169 41.0691 0.9049 2.169E-03 1.434E-01 23.5404 -0.0469 7.929E-01 9.992E-01 ENSG00000153015 CWC27 467.2326 0.6641 2.149E-03 1.434E-01 393.8559 -0.0644 6.531E-01 9.992E-01 ENSG00000176428 VPS37D 53.3142 0.8981 2.233E-03 1.456E-01 30.2039 0.3510 4.737E-02 9.986E-01 ENSG00000251562 MALAT1 19494.1223 0.5997 2.228E-03 1.456E-01 18181.7253 0.1216 3.560E-01 9.992E-01 ENSG00000114423 CBLB 46.2665 0.8810 2.353E-03 1.510E-01 34.9393 -0.0476 7.976E-01 9.992E-01 ENSG00000087074 PPP1R15A 168.5856 0.7727 2.367E-03 1.511E-01 128.7271 0.4977 5.760E-03 4.460E-01 ENSG00000153914 SREK1 1285.3745 0.6179 2.390E-03 1.511E-01 1037.9440 0.2983 1.388E-02 6.687E-01 ENSG00000234741 GAS5 986.1827 0.5693 2.602E-03 1.611E-01 699.7703 0.2126 8.514E-02 9.992E-01 ENSG00000121075 TBX4 31.8390 0.8737 2.846E-03 1.664E-01 14.9764 0.1288 4.404E-01 9.992E-01 ENSG00000188868 ZNF563 58.8168 0.8446 2.849E-03 1.664E-01 29.3432 0.2181 2.242E-01 9.992E-01 ENSG00000156030 ELMSAN1 125.7701 0.8128 2.839E-03 1.664E-01 104.0391 0.2647 1.402E-01 9.992E-01 ENSG00000113916 BCL6 117.2565 0.7720 2.849E-03 1.664E-01 88.1632 0.4181 2.016E-02 7.780E-01 ENSG00000116717 GADD45A 420.8704 0.6357 2.792E-03 1.664E-01 416.8143 0.3851 6.748E-03 4.845E-01 ENSG00000120694 HSPH1 1436.8385 0.5469 3.062E-03 1.746E-01 1084.0096 0.1576 2.390E-01 9.992E-01 ENSG00000186166 CCDC84 273.1001 0.6256 3.134E-03 1.771E-01 200.7295 0.0471 7.651E-01 9.992E-01 ENSG00000189143 CLDN4 382.6529 0.6024 3.250E-03 1.811E-01 230.2898 0.2722 1.002E-01 9.992E-01 ENSG00000204387 C6orf48 1042.2409 0.6539 3.304E-03 1.825E-01 809.3791 0.4187 7.936E-04 1.288E-01 ENSG00000125618 PAX8 86.6193 0.7885 3.418E-03 1.871E-01 50.7997 0.3848 3.737E-02 9.340E-01 ENSG00000139194 RBP5 56.6071 0.8509 3.478E-03 1.887E-01 32.2195 -0.0271 8.832E-01 9.992E-01 ENSG00000168298 HIST1H1E 177.5967 0.8249 3.583E-03 1.927E-01 146.1473 0.1597 2.549E-01 9.992E-01 ENSG00000135111 TBX3 1451.3825 0.5421 3.651E-03 1.944E-01 931.2102 0.4789 4.799E-05 2.001E-02 ENSG00000103145 HCFC1R1 207.0866 0.6572 3.845E-03 1.972E-01 156.0097 0.2041 2.099E-01 9.992E-01 ENSG00000196757 ZNF700 46.5359 0.8363 4.115E-03 2.059E-01 21.4437 0.1615 3.590E-01 9.992E-01 ENSG00000198408 MGEA5 461.4567 0.5744 4.103E-03 2.059E-01 319.9666 0.3947 7.517E-03 5.147E-01 ENSG00000095739 BAMBI 144.8478 0.8098 4.132E-03 2.060E-01 114.1041 0.3740 3.464E-02 9.212E-01 ENSG00000198382 UVRAG 294.3455 0.6365 4.200E-03 2.068E-01 192.5205 0.4412 7.150E-03 5.006E-01 ENSG00000173531 MST1 358.5237 0.6475 4.235E-03 2.077E-01 206.0960 0.4091 7.982E-03 5.253E-01 ENSG00000158246 FAM46B 34.0153 0.8402 4.413E-03 2.147E-01 13.6940 0.4278 8.790E-03 5.569E-01 ENSG00000013441 CLK1 335.4633 0.6014 4.446E-03 2.154E-01 248.3248 0.2887 7.025E-02 9.992E-01 ENSG00000108375 RNF43 800.7970 0.5506 4.537E-03 2.173E-01 500.0431 0.4458 1.497E-03 1.925E-01 ENSG00000110172 CHORDC1 280.0993 0.5966 5.227E-03 2.428E-01 221.4043 0.0331 8.252E-01 9.992E-01 ENSG00000181472 ZBTB2 226.3637 0.6961 5.365E-03 2.473E-01 147.7826 0.1122 4.933E-01 9.992E-01 I-miR-505-5p (Sorafenib-Control) Transfection Control (Sorafenib-control) ENSG00000171940 ZNF217 252.2675 0.6074 5.423E-03 2.490E-01 168.2447 0.4617 4.037E-03 3.569E-01 ENSG00000060566 CREB3L3 126.7919 0.7214 5.524E-03 2.518E-01 61.4905 0.4886 8.412E-03 5.370E-01 ENSG00000132275 RRP8 266.9602 0.6510 5.667E-03 2.545E-01 170.0524 0.4133 1.251E-02 6.403E-01 ENSG00000114315 HES1 896.6163 0.7142 5.728E-03 2.554E-01 732.5568 0.4597 1.495E-03 1.925E-01 ENSG00000198917 SPOUT1 370.5832 0.7395 6.126E-03 2.673E-01 186.7793 0.2582 9.316E-02 9.992E-01 ENSG00000162885 B3GALNT2 89.5419 0.7273 6.344E-03 2.692E-01 71.1391 0.0661 7.200E-01 9.992E-01 ENSG00000204388 HSPA1B 327.3375 0.7469 6.804E-03 2.799E-01 302.1135 0.1689 3.006E-01 9.992E-01 ENSG00000108239 TBC1D12 87.7606 0.7452 7.223E-03 2.923E-01 58.1094 0.1201 5.121E-01 9.992E-01 ENSG00000125352 RNF113A 102.2726 0.6904 8.034E-03 3.117E-01 68.1056 -0.0179 9.211E-01 9.992E-01 ENSG00000135100 HNF1A 98.7125 0.7532 8.254E-03 3.162E-01 79.4780 0.3044 9.619E-02 9.992E-01 ENSG00000141428 C18orf21 95.3589 0.7222 8.350E-03 3.165E-01 66.3155 -0.3820 3.548E-02 9.257E-01 ENSG00000160972 PPP1R16A 342.7273 0.5799 8.539E-03 3.194E-01 233.4395 0.3814 2.461E-02 8.413E-01 ENSG00000122085 MTERF4 302.0790 0.5616 8.793E-03 3.218E-01 193.5671 0.1581 3.114E-01 9.992E-01 ENSG00000185551 NR2F2 714.7994 0.5552 9.059E-03 3.267E-01 634.1023 0.2397 9.194E-02 9.992E-01 ENSG00000243927 MRPS6 276.3895 0.5812 9.256E-03 3.309E-01 186.4607 0.2977 5.728E-02 9.992E-01 ENSG00000198551 ZNF627 55.9263 0.7673 9.340E-03 3.319E-01 29.4215 0.2331 2.017E-01 9.992E-01 ENSG00000124216 SNAI1 32.2646 0.7590 9.324E-03 3.319E-01 26.0610 0.3097 8.091E-02 9.992E-01 ENSG00000145390 USP53 196.2980 0.6359 9.470E-03 3.356E-01 117.4551 0.4552 1.286E-02 6.407E-01 ENSG00000002016 RAD52 66.6387 0.7174 9.713E-03 3.422E-01 32.3261 0.1641 3.672E-01 9.992E-01 ENSG00000247498 GPRC5D-AS1 53.7315 0.7352 1.004E-02 3.528E-01 38.7506 -0.0074 9.680E-01 9.992E-01 ENSG00000106327 TFR2 79.3641 0.7138 1.083E-02 3.723E-01 47.3936 0.0811 6.620E-01 9.992E-01 ENSG00000165030 NFIL3 432.0275 0.5594 1.092E-02 3.724E-01 309.3088 0.3499 2.116E-02 7.869E-01 ENSG00000114019 AMOTL2 269.1129 0.6772 1.105E-02 3.741E-01 179.6616 0.3883 1.120E-02 6.209E-01 ENSG00000148362 PAXX 169.6281 0.6468 1.131E-02 3.787E-01 103.4285 0.1380 4.263E-01 9.992E-01 ENSG00000197857 ZNF44 104.5557 0.7045 1.142E-02 3.796E-01 74.7516 0.2621 1.545E-01 9.992E-01 ENSG00000175634 RPS6KB2 114.1480 0.7425 1.164E-02 3.846E-01 48.1112 -0.0729 6.930E-01 9.992E-01 ENSG00000170906 NDUFA3 105.2526 0.7431 1.176E-02 3.877E-01 57.6523 -0.2407 1.902E-01 9.992E-01 ENSG00000144655 CSRNP1 147.5557 0.6160 1.211E-02 3.925E-01 89.7623 0.3252 7.148E-02 9.992E-01 ENSG00000102805 CLN5 89.5210 0.6727 1.223E-02 3.945E-01 61.2336 0.1078 5.613E-01 9.992E-01 ENSG00000175155 YPEL2 89.7333 0.6854 1.234E-02 3.950E-01 59.3458 0.4790 9.964E-03 5.915E-01 ENSG00000037042 TUBG2 168.1774 0.6767 1.233E-02 3.950E-01 105.6644 0.2020 2.622E-01 9.992E-01 ENSG00000126368 NR1D1 40.1989 0.7350 1.278E-02 4.050E-01 37.8676 0.1130 5.322E-01 9.992E-01 ENSG00000205323 SARNP 102.7961 0.6895 1.288E-02 4.059E-01 72.0632 0.2246 2.172E-01 9.992E-01 ENSG00000155330 C16orf87 148.0478 0.6454 1.302E-02 4.087E-01 108.4623 0.1258 4.672E-01 9.992E-01 ENSG00000154124 OTULIN 203.9679 0.5918 1.319E-02 4.114E-01 133.1352 0.1040 5.260E-01 9.992E-01 ENSG00000110711 AIP 121.5587 0.7083 1.340E-02 4.150E-01 66.9337 0.2834 1.259E-01 9.992E-01 ENSG00000119547 ONECUT2 281.0267 0.5309 1.386E-02 4.231E-01 207.7188 0.0081 9.601E-01 9.992E-01 ENSG00000004975 DVL2 285.3179 0.5182 1.387E-02 4.231E-01 189.5581 0.2322 1.491E-01 9.992E-01 ENSG00000154781 CCDC174 244.5421 0.5943 1.394E-02 4.242E-01 195.5515 0.1792 2.684E-01 9.992E-01 ENSG00000092978 GPATCH2 254.9944 0.5589 1.403E-02 4.256E-01 169.9216 0.2671 9.683E-02 9.992E-01 ENSG00000184634 MED12 73.6802 0.7188 1.433E-02 4.320E-01 54.9012 -0.1097 5.536E-01 9.992E-01 ENSG00000107201 DDX58 46.9064 0.7181 1.471E-02 4.351E-01 28.7937 0.1047 5.667E-01 9.992E-01 ENSG00000125846 ZNF133 117.9280 0.6871 1.494E-02 4.371E-01 64.5032 0.4462 1.589E-02 7.130E-01 ENSG00000274605 AL355338.1 90.3907 0.6917 1.507E-02 4.389E-01 73.6430 0.3014 9.401E-02 9.992E-01 ENSG00000168564 CDKN2AIP 172.7437 0.5981 1.517E-02 4.398E-01 121.5775 0.1903 2.724E-01 9.992E-01 ENSG00000120370 GORAB 33.4808 0.7129 1.552E-02 4.459E-01 25.7471 0.2994 9.736E-02 9.992E-01 ENSG00000148339 SLC25A25 182.8996 0.6281 1.572E-02 4.459E-01 145.6415 0.3295 4.796E-02 9.992E-01 ENSG00000116574 RHOU 221.5290 0.5441 1.612E-02 4.484E-01 153.8830 0.2602 1.128E-01 9.992E-01 ENSG00000102543 CDADC1 83.3485 0.6679 1.703E-02 4.590E-01 49.6712 0.1261 4.970E-01 9.992E-01 ENSG00000108733 PEX12 31.1653 0.7017 1.744E-02 4.596E-01 16.0339 0.1373 4.088E-01 9.992E-01 ENSG00000103460 TOX3 417.0690 0.5623 1.720E-02 4.596E-01 325.0034 0.2923 4.867E-02 9.992E-01 ENSG00000079689 SCGN 227.6816 0.5413 1.764E-02 4.624E-01 143.9318 0.1332 4.181E-01 9.992E-01 ENSG00000125814 NAPB 116.1810 0.6202 1.777E-02 4.638E-01 75.9725 -0.0654 7.174E-01 9.992E-01 ENSG00000170802 FOXN2 100.9160 0.6472 1.798E-02 4.663E-01 83.5263 0.2037 2.625E-01 9.992E-01 ENSG00000140830 TXNL4B 139.2176 0.5754 1.806E-02 4.663E-01 87.4434 0.1950 2.678E-01 9.992E-01 ENSG00000197461 PDGFA 102.5405 0.6161 1.851E-02 4.679E-01 70.9337 0.2228 2.275E-01 9.992E-01 ENSG00000179094 PER1 44.0950 0.6893 1.894E-02 4.749E-01 38.6378 0.1119 5.444E-01 9.992E-01 ENSG00000115289 PCGF1 50.0188 0.6879 1.952E-02 4.830E-01 33.7713 0.2296 1.999E-01 9.992E-01 ENSG00000189060 H1F0 1605.7074 0.5753 1.970E-02 4.830E-01 1268.4518 0.0714 6.907E-01 9.992E-01 ENSG00000164631 ZNF12 130.4160 0.5875 2.002E-02 4.901E-01 100.0869 0.1005 5.600E-01 9.992E-01 ENSG00000278909 AC007608.4 351.9749 0.5585 2.026E-02 4.939E-01 282.0798 0.4897 4.374E-03 3.728E-01 ENSG00000234771 SLC25A25-AS1 33.1912 0.6798 2.114E-02 5.071E-01 15.8229 0.2606 1.102E-01 9.992E-01 ENSG00000197472 ZNF695 30.4309 0.6684 2.134E-02 5.078E-01 24.3460 0.1935 2.549E-01 9.992E-01 ENSG00000126705 AHDC1 123.5981 0.5878 2.141E-02 5.078E-01 88.3216 0.3097 9.219E-02 9.992E-01 ENSG00000100395 L3MBTL2 233.4582 0.5383 2.167E-02 5.099E-01 139.6976 0.1384 3.965E-01 9.992E-01 ENSG00000168874 ATOH8 96.4639 0.6245 2.208E-02 5.148E-01 43.7137 0.1566 3.994E-01 9.992E-01 ENSG00000177410 ZFAS1 2310.9623 0.5534 2.226E-02 5.163E-01 1858.8657 0.2716 3.169E-02 8.961E-01 ENSG00000222041 CYTOR 419.4309 0.5032 2.228E-02 5.163E-01 302.6051 0.1784 2.197E-01 9.992E-01 ENSG00000126822 PLEKHG3 144.9318 0.6004 2.255E-02 5.207E-01 82.7118 0.3827 3.139E-02 8.939E-01 ENSG00000059728 MXD1 132.3023 0.6205 2.276E-02 5.226E-01 85.9071 0.3568 4.322E-02 9.716E-01 ENSG00000256222 MTRNR2L3 124.5024 0.6161 2.292E-02 5.240E-01 63.8373 0.1576 3.963E-01 9.992E-01 ENSG00000148737 TCF7L2 548.3638 0.5045 2.308E-02 5.251E-01 412.1860 0.3024 2.570E-02 8.542E-01 ENSG00000155906 RMND1 113.4869 0.6419 2.399E-02 5.372E-01 92.1380 0.1489 4.102E-01 9.992E-01 ENSG00000109917 ZPR1 394.6812 0.5014 2.398E-02 5.372E-01 246.8194 0.0643 6.710E-01 9.992E-01 ENSG00000160678 S100A1 133.3084 0.6070 2.496E-02 5.431E-01 86.2884 0.0676 7.042E-01 9.992E-01 ENSG00000144504 ANKMY1 43.0076 0.6594 2.505E-02 5.436E-01 28.5930 0.2822 1.166E-01 9.992E-01 ENSG00000148426 PROSER2 217.8482 0.5158 2.576E-02 5.503E-01 169.9769 0.2296 1.473E-01 9.992E-01 ENSG00000259429 UBE2Q2P2 34.5309 0.6575 2.590E-02 5.510E-01 20.2994 0.1477 3.947E-01 9.992E-01 ENSG00000155090 KLF10 146.5106 0.6496 2.594E-02 5.510E-01 108.9260 0.1126 5.418E-01 9.992E-01 ENSG00000160097 FNDC5 35.7751 0.6515 2.651E-02 5.578E-01 23.2065 0.1950 2.453E-01 9.992E-01 ENSG00000164463 CREBRF 78.2580 0.6218 2.661E-02 5.578E-01 53.4787 0.2820 1.281E-01 9.992E-01 ENSG00000150961 SEC24D 97.6875 0.5858 2.684E-02 5.586E-01 89.6002 0.0282 8.759E-01 9.992E-01 ENSG00000258704 SRP54-AS1 67.4026 0.6286 2.721E-02 5.620E-01 48.8274 0.2973 1.097E-01 9.992E-01 ENSG00000213918 DNASE1 50.0199 0.6415 2.752E-02 5.623E-01 34.3249 -0.1853 3.131E-01 9.992E-01 ENSG00000102710 SUPT20H 287.9663 0.5178 2.793E-02 5.671E-01 205.1022 0.2825 8.124E-02 9.992E-01 ENSG00000148572 NRBF2 200.4616 0.5545 2.822E-02 5.694E-01 137.2168 0.2077 2.078E-01 9.992E-01 ENSG00000125089 SH3TC1 52.1189 0.6349 2.847E-02 5.711E-01 26.0095 0.1323 4.608E-01 9.992E-01 ENSG00000137834 SMAD6 171.3819 0.5295 2.848E-02 5.711E-01 100.3057 0.1007 5.755E-01 9.992E-01 ENSG00000171160 MORN4 52.4384 0.6411 2.899E-02 5.751E-01 26.5881 0.1146 5.285E-01 9.992E-01 ENSG00000276980 AC008760.2 92.7062 0.6094 2.886E-02 5.751E-01 70.6601 0.1993 2.693E-01 9.992E-01 ENSG00000142669 SH3BGRL3 212.3791 0.6013 2.895E-02 5.751E-01 116.4903 0.1069 5.327E-01 9.992E-01 ENSG00000097046 CDC7 90.7081 0.5874 2.932E-02 5.777E-01 50.2801 0.3287 7.679E-02 9.992E-01 ENSG00000125772 GPCPD1 201.7218 0.5231 2.940E-02 5.777E-01 143.9533 0.3961 1.811E-02 7.636E-01 ENSG00000173875 ZNF791 261.4039 0.5111 2.954E-02 5.787E-01 154.7674 0.2508 1.115E-01 9.992E-01 ENSG00000099812 MISP 103.8226 0.6006 3.030E-02 5.868E-01 58.3670 0.2282 2.177E-01 9.992E-01 ENSG00000277223 AC090116.1 64.0218 0.6354 3.040E-02 5.879E-01 43.5291 0.1596 3.741E-01 9.992E-01 ENSG00000095397 WHRN 35.9528 0.6365 3.098E-02 5.954E-01 20.1149 0.0622 7.198E-01 9.992E-01 ENSG00000198746 GPATCH3 33.9128 0.6237 3.136E-02 5.985E-01 21.0518 -0.1661 3.358E-01 9.992E-01 ENSG00000198964 SGMS1 82.3031 0.5811 3.178E-02 6.031E-01 53.8998 0.2182 2.402E-01 9.992E-01 ENSG00000139324 TMTC3 212.4182 0.5339 3.276E-02 6.160E-01 174.7769 -0.0529 7.402E-01 9.992E-01 ENSG00000256618 MTRNR2L1 48.9152 0.6254 3.310E-02 6.205E-01 38.8271 0.2120 2.511E-01 9.992E-01 ENSG00000108819 PPP1R9B 129.4921 0.5403 3.341E-02 6.244E-01 90.5600 -0.0525 7.707E-01 9.992E-01 ENSG00000175895 PLEKHF2 49.5389 0.6275 3.353E-02 6.257E-01 44.3503 -0.0504 7.863E-01 9.992E-01 ENSG00000180879 SSR4 354.8426 0.5771 3.471E-02 6.344E-01 173.3631 0.4881 1.771E-03 2.077E-01 ENSG00000163607 GTPBP8 134.6296 0.5248 3.448E-02 6.344E-01 98.6014 0.0917 5.981E-01 9.992E-01 ENSG00000151532 VTI1A 190.6457 0.5079 3.482E-02 6.344E-01 139.4698 0.1307 4.264E-01 9.992E-01 ENSG00000135127 BICDL1 30.6859 0.6141 3.549E-02 6.399E-01 18.9401 0.1788 3.000E-01 9.992E-01 ENSG00000117625 RCOR3 146.7531 0.5198 3.559E-02 6.408E-01 120.4610 0.2860 8.572E-02 9.992E-01 ENSG00000181450 ZNF678 30.0270 0.6182 3.607E-02 6.436E-01 17.1882 0.1726 2.979E-01 9.992E-01 ENSG00000198039 ZNF273 38.6437 0.6152 3.653E-02 6.436E-01 25.9119 0.3690 3.907E-02 9.448E-01 ENSG00000132950 ZMYM5 44.2377 0.6150 3.654E-02 6.436E-01 36.2109 0.1063 5.667E-01 9.992E-01 ENSG00000232445 AC006329.1 34.7884 0.6092 3.625E-02 6.436E-01 25.6046 -0.1742 3.349E-01 9.992E-01 ENSG00000234327 AC012146.1 103.9349 0.5783 3.648E-02 6.436E-01 56.4149 0.2141 2.433E-01 9.992E-01 ENSG00000204406 MBD5 42.5211 0.6127 3.661E-02 6.437E-01 36.4707 0.1473 4.274E-01 9.992E-01 ENSG00000143622 RIT1 59.1266 0.5950 3.794E-02 6.572E-01 40.9473 0.1130 5.417E-01 9.992E-01 ENSG00000186908 ZDHHC17 108.6609 0.5591 3.852E-02 6.614E-01 73.8823 0.2694 1.303E-01 9.992E-01 ENSG00000137193 PIM1 537.9866 0.6089 3.886E-02 6.636E-01 416.5771 0.4438 7.784E-03 5.180E-01 ENSG00000146232 NFKBIE 97.6336 0.5789 3.892E-02 6.637E-01 60.0346 0.1471 4.262E-01 9.992E-01 ENSG00000066651 TRMT11 182.6469 0.5183 3.969E-02 6.689E-01 126.6764 -0.0245 8.876E-01 9.992E-01 ENSG00000100802 C14orf93 64.9641 0.5904 4.066E-02 6.750E-01 54.6486 0.2612 1.597E-01 9.992E-01 ENSG00000127423 AUNIP 55.7631 0.5891 4.171E-02 6.798E-01 45.8684 0.0458 8.050E-01 9.992E-01 ENSG00000164414 SLC35A1 92.6315 0.5649 4.167E-02 6.798E-01 56.0112 0.1582 3.888E-01 9.992E-01 ENSG00000170417 TMEM182 46.4548 0.6006 4.190E-02 6.808E-01 27.9531 -0.1231 5.032E-01 9.992E-01 ENSG00000130203 APOE 613.1099 0.5414 4.192E-02 6.808E-01 403.7657 0.0830 6.076E-01 9.992E-01 ENSG00000137204 SLC22A7 58.9097 0.5966 4.216E-02 6.811E-01 40.6245 0.2152 2.418E-01 9.992E-01 ENSG00000196646 ZNF136 44.0216 0.5931 4.213E-02 6.811E-01 29.3980 0.2218 2.150E-01 9.992E-01 ENSG00000124209 RAB22A 244.9956 -0.4482 4.273E-02 6.855E-01 203.5357 -0.6581 3.530E-05 1.818E-02 ENSG00000164008 C1orf50 103.3028 0.5439 4.337E-02 6.897E-01 65.7622 0.1206 5.091E-01 9.992E-01 ENSG00000012174 MBTPS2 130.4060 0.5120 4.324E-02 6.897E-01 72.0415 0.1194 5.091E-01 9.992E-01 ENSG00000117114 ADGRL2 30.0884 0.5947 4.375E-02 6.899E-01 30.7890 0.0761 6.783E-01 9.992E-01 ENSG00000138764 CCNG2 35.5728 0.5697 4.366E-02 6.899E-01 22.3715 0.0803 6.525E-01 9.992E-01 ENSG00000166887 VPS39 92.3779 0.5554 4.370E-02 6.899E-01 65.5933 -0.1346 4.618E-01 9.992E-01 ENSG00000160993 ALKBH4 95.1196 0.5303 4.354E-02 6.899E-01 59.3090 0.1233 5.059E-01 9.992E-01 ENSG00000172766 NAA16 140.7929 0.5097 4.413E-02 6.938E-01 125.6263 0.0433 7.948E-01 9.992E-01 ENSG00000114127 XRN1 164.8561 0.5149 4.428E-02 6.942E-01 122.7488 0.3523 5.040E-02 9.992E-01 ENSG00000214022 REPIN1 350.7278 0.5066 4.463E-02 6.948E-01 216.7257 0.0427 7.749E-01 9.992E-01 ENSG00000168071 CCDC88B 33.0040 0.5852 4.654E-02 7.002E-01 16.6318 0.2826 8.076E-02 9.992E-01 ENSG00000104859 CLASRP 143.0035 0.5149 4.711E-02 7.035E-01 135.6782 0.0816 6.326E-01 9.992E-01 ENSG00000163291 PAQR3 52.800 1.202 1.017E-02 7.544E-02 45.843 0.357 3.941E-01 6.574E-01 ENSG00000141452 RMC1 60.951 1.147 1.016E-02 7.544E-02 42.706 0.324 4.903E-01 7.298E-01 ENSG00000186908 ZDHHC17 115.546 0.961 1.037E-02 7.641E-02 110.685 0.462 1.626E-01 4.024E-01 ENSG00000023318 ERP44 385.365 0.646 1.058E-02 7.772E-02 381.677 -0.012 9.632E-01 9.844E-01 ENSG00000197798 FAM118B 148.327 0.859 1.062E-02 7.782E-02 133.280 0.321 3.433E-01 6.110E-01 ENSG00000198901 PRC1 797.155 0.592 1.090E-02 7.902E-02 863.883 0.223 2.285E-01 4.882E-01 ENSG00000127831 VIL1 863.388 -0.481 1.091E-02 7.902E-02 878.271 -0.759 1.005E-05 2.318E-04 ENSG00000065491 TBC1D22B 193.787 0.830 1.129E-02 8.116E-02 147.955 0.101 7.312E-01 8.779E-01 ENSG00000071051 NCK2 149.607 0.820 1.135E-02 8.160E-02 100.720 0.436 2.623E-01 5.282E-01 ENSG00000111897 SERINC1 392.287 0.646 1.167E-02 8.296E-02 338.098 0.274 2.820E-01 5.491E-01 ENSG00000116473 RAP1A 281.575 0.784 1.174E-02 8.327E-02 233.553 0.453 1.215E-01 3.337E-01 ENSG00000143748 NVL 113.871 0.825 1.187E-02 8.411E-02 122.935 0.433 1.926E-01 4.420E-01 ENSG00000180817 PPA1 393.864 0.696 1.199E-02 8.444E-02 275.242 0.054 8.677E-01 9.454E-01 ENSG00000130312 MRPL34 746.260 0.691 1.218E-02 8.549E-02 623.060 -0.166 5.171E-01 7.484E-01 ENSG00000133026 MYH10 1278.631 -0.463 1.225E-02 8.580E-02 1316.779 -0.623 6.479E-04 7.377E-03 ENSG00000103018 CYB5B 923.921 -0.484 1.226E-02 8.587E-02 798.827 -0.760 4.637E-05 8.470E-04 ENSG00000157110 RBPMS 624.578 0.587 1.229E-02 8.587E-02 450.818 0.055 8.190E-01 9.252E-01 ENSG00000121073 SLC35B1 741.530 0.508 1.236E-02 8.637E-02 608.308 0.327 1.264E-01 3.425E-01 ENSG00000196233 LCOR 518.355 0.597 1.240E-02 8.654E-02 476.230 0.259 1.852E-01 4.324E-01 ENSG00000145337 PYURF 328.856 0.625 1.244E-02 8.675E-02 307.108 0.136 5.875E-01 7.968E-01 ENSG00000165169 DYNLT3 64.222 1.047 1.245E-02 8.676E-02 59.847 0.405 3.336E-01 6.019E-01 ENSG00000169375 SIN3A 395.534 0.564 1.252E-02 8.715E-02 333.722 0.371 9.832E-02 2.910E-01 ENSG00000174606 ANGEL2 166.700 0.758 1.262E-02 8.779E-02 164.428 0.280 3.521E-01 6.194E-01 ENSG00000171224 FAM241B 42.695 1.143 1.281E-02 8.885E-02 15.733 0.160 7.416E-01 8.838E-01 ENSG00000163320 CGGBP1 260.582 0.661 1.283E-02 8.890E-02 237.011 0.372 1.918E-01 4.414E-01 ENSG00000163132 MSX1 552.977 0.504 1.299E-02 8.966E-02 543.821 0.493 2.021E-02 9.957E-02 ENSG00000094880 CDC23 219.182 0.739 1.304E-02 8.995E-02 251.844 0.403 1.700E-01 4.136E-01 ENSG00000103160 HSDL1 275.726 0.788 1.306E-02 9.003E-02 256.510 0.320 2.522E-01 5.168E-01 ENSG00000217128 FNIP1 263.226 0.645 1.310E-02 9.020E-02 221.014 0.090 7.321E-01 8.784E-01 ENSG00000076043 REXO2 582.408 0.693 1.325E-02 9.099E-02 514.915 0.292 1.774E-01 4.236E-01 ENSG00000115109 EPB41L5 184.796 0.780 1.332E-02 9.134E-02 209.437 0.472 8.253E-02 2.597E-01 ENSG00000129657 SEC14L1 368.374 0.634 1.343E-02 9.182E-02 311.794 0.192 5.289E-01 7.563E-01 ENSG00000042286 AIFM2 1022.123 0.531 1.364E-02 9.305E-02 1116.981 0.462 7.276E-03 4.851E-02 ENSG00000205765 C5orf51 65.304 0.978 1.385E-02 9.416E-02 65.827 0.039 9.255E-01 9.708E-01 ENSG00000279692 AC110285.7 94.530 0.944 1.406E-02 9.522E-02 81.469 -0.342 3.655E-01 6.322E-01 ENSG00000181789 COPG1 314.920 0.645 1.415E-02 9.556E-02 281.013 0.130 5.994E-01 8.035E-01 ENSG00000164244 PRRC1 603.619 0.509 1.418E-02 9.556E-02 604.614 0.340 1.137E-01 3.198E-01 ENSG00000184203 PPP1R2 302.878 0.611 1.423E-02 9.574E-02 228.910 0.213 4.926E-01 7.318E-01 ENSG00000131115 ZNF227 77.238 1.127 1.444E-02 9.673E-02 56.237 -0.229 6.086E-01 8.086E-01 ENSG00000138593 SECISBP2L 225.054 0.716 1.463E-02 9.768E-02 193.257 0.277 3.092E-01 5.771E-01 ENSG00000115163 CENPA 248.167 0.781 1.467E-02 9.789E-02 201.670 0.236 4.462E-01 6.979E-01 ENSG00000008282 SYPL1 334.048 0.633 1.470E-02 9.798E-02 327.432 0.143 5.896E-01 7.982E-01 ENSG00000011426 ANLN 458.416 0.593 1.489E-02 9.855E-02 480.555 0.500 1.844E-02 9.365E-02 ENSG00000186314 PRELID2 84.427 0.916 1.493E-02 9.859E-02 77.822 -0.817 1.986E-02 9.852E-02 ENSG00000183291 SELENOF 369.959 0.644 1.494E-02 9.863E-02 337.574 -0.011 9.690E-01 9.866E-01 ENSG00000165669 FAM204A 280.302 0.660 1.550E-02 1.010E-01 252.775 0.119 6.711E-01 8.460E-01 ENSG00000182903 ZNF721 79.789 0.979 1.556E-02 1.014E-01 69.141 0.134 7.493E-01 8.876E-01 ENSG00000180190 TDRP 167.531 0.792 1.563E-02 1.015E-01 133.326 0.374 2.224E-01 4.816E-01 ENSG00000143641 GALNT2 431.763 0.534 1.566E-02 1.017E-01 378.713 0.379 9.240E-02 2.786E-01 ENSG00000037241 RPL26L1 213.170 0.705 1.570E-02 1.018E-01 202.301 0.375 1.927E-01 4.422E-01 ENSG00000166479 TMX3 182.352 0.757 1.572E-02 1.018E-01 173.844 0.223 4.334E-01 6.901E-01 ENSG00000116903 EXOC8 78.117 0.982 1.583E-02 1.024E-01 48.392 -0.396 3.499E-01 6.171E-01 ENSG00000149923 PPP4C 194.458 0.938 1.591E-02 1.028E-01 142.791 0.155 7.512E-01 8.888E-01 ENSG00000081721 DUSP12 112.122 0.883 1.596E-02 1.030E-01 86.013 -0.073 8.517E-01 9.388E-01 ENSG00000089022 MAPKAPK5 327.291 0.686 1.605E-02 1.033E-01 299.388 0.178 4.957E-01 7.342E-01 ENSG00000164934 DCAF13 394.991 0.603 1.605E-02 1.033E-01 339.547 0.356 1.287E-01 3.458E-01 ENSG00000136819 C9orf78 556.040 0.574 1.620E-02 1.039E-01 498.609 0.357 8.272E-02 2.599E-01 ENSG00000240682 ISY1 455.353 0.602 1.633E-02 1.045E-01 458.797 -0.005 9.816E-01 9.916E-01 ENSG00000166002 SMCO4 192.781 0.700 1.671E-02 1.064E-01 194.036 0.264 4.093E-01 6.704E-01 ENSG00000105926 MPP6 213.796 0.633 1.679E-02 1.067E-01 253.827 0.498 5.630E-02 2.032E-01 ENSG00000155438 NIFK 986.024 0.503 1.682E-02 1.068E-01 768.474 0.314 1.104E-01 3.135E-01 ENSG00000072756 TRNT1 125.292 0.810 1.702E-02 1.077E-01 113.473 0.336 2.762E-01 5.442E-01 ENSG00000170852 KBTBD2 171.272 0.823 1.717E-02 1.083E-01 150.588 0.389 1.792E-01 4.258E-01 ENSG00000146476 ARMT1 129.036 0.803 1.717E-02 1.083E-01 101.859 -0.082 8.465E-01 9.370E-01 ENSG00000043093 DCUN1D1 112.116 0.810 1.766E-02 1.105E-01 93.572 -0.205 5.377E-01 7.627E-01 ENSG00000119048 UBE2B 694.992 0.561 1.770E-02 1.106E-01 692.521 -0.186 3.487E-01 6.158E-01 ENSG00000180530 NRIP1 775.936 0.592 1.788E-02 1.114E-01 784.512 0.157 3.856E-01 6.503E-01 ENSG00000072401 UBE2D1 126.282 0.854 1.791E-02 1.115E-01 120.332 -0.289 4.541E-01 7.044E-01 ENSG00000151503 NCAPD3 183.843 0.708 1.802E-02 1.119E-01 175.192 0.173 5.419E-01 7.655E-01 ENSG00000171448 ZBTB26 58.139 1.150 1.810E-02 1.121E-01 62.768 0.156 6.967E-01 8.600E-01 ENSG00000185246 PRPF39 250.058 0.611 1.835E-02 1.132E-01 250.603 0.358 1.577E-01 3.949E-01 ENSG00000136754 ABI1 159.550 0.742 1.845E-02 1.135E-01 141.245 0.405 1.671E-01 4.099E-01 ENSG00000168438 CDC40 249.638 0.682 1.866E-02 1.144E-01 247.767 0.385 1.233E-01 3.363E-01 ENSG00000127334 DYRK2 182.828 0.704 1.871E-02 1.146E-01 151.724 0.176 5.753E-01 7.893E-01 ENSG00000165417 GTF2A1 208.414 0.858 1.891E-02 1.152E-01 180.013 0.339 3.104E-01 5.786E-01 ENSG00000219529 AP000580.1 40.485 1.117 1.894E-02 1.153E-01 23.798 0.060 9.025E-01 9.618E-01 ENSG00000163235 TGFA 115.535 0.789 1.901E-02 1.154E-01 79.718 0.277 4.445E-01 6.968E-01 ENSG00000135763 URB2 80.023 0.894 1.930E-02 1.167E-01 80.319 0.212 5.538E-01 7.735E-01 ENSG00000182923 CEP63 311.376 0.568 1.942E-02 1.173E-01 299.685 0.213 3.514E-01 6.188E-01 ENSG00000160908 ZNF394 88.383 0.926 1.982E-02 1.187E-01 48.962 -0.024 9.553E-01 9.810E-01 ENSG00000253251 AC008560.1 43.497 1.084 1.995E-02 1.190E-01 31.147 0.202 6.697E-01 8.451E-01 ENSG00000267519 AC020916.1 43.783 1.069 1.995E-02 1.190E-01 26.704 1.375 5.008E-03 3.656E-02 ENSG00000122958 VPS26A 340.522 0.626 1.997E-02 1.190E-01 305.053 0.081 7.420E-01 8.838E-01 ENSG00000129484 PARP2 356.956 0.570 2.007E-02 1.194E-01 362.050 0.369 8.547E-02 2.650E-01 ENSG00000129460 NGDN 1671.918 0.547 2.008E-02 1.194E-01 1343.887 0.450 1.988E-02 9.854E-02 ENSG00000162819 BROX 197.687 0.714 2.024E-02 1.199E-01 152.352 0.159 5.991E-01 8.034E-01 ENSG00000124641 MED20 200.924 0.672 2.052E-02 1.210E-01 135.948 -0.106 7.211E-01 8.716E-01 ENSG00000126821 SGPP1 112.889 0.837 2.055E-02 1.211E-01 90.280 0.302 4.232E-01 6.814E-01 ENSG00000067646 ZFY 33.268 1.114 2.079E-02 1.220E-01 27.033 0.335 4.775E-01 7.209E-01 ENSG00000064102 INTS13 334.840 0.622 2.081E-02 1.220E-01 337.571 0.294 2.000E-01 4.527E-01 ENSG00000106682 EIF4H 159.405 0.806 2.098E-02 1.226E-01 122.107 -0.233 4.788E-01 7.218E-01 ENSG00000120942 UBIAD1 297.260 0.597 2.119E-02 1.237E-01 294.989 0.195 4.435E-01 6.965E-01 ENSG00000175550 DRAP1 477.846 0.764 2.134E-02 1.241E-01 410.235 0.427 1.014E-01 2.963E-01 ENSG00000133703 KRAS 358.361 0.590 2.148E-02 1.247E-01 346.751 0.151 4.960E-01 7.346E-01 ENSG00000145685 LHFPL2 349.086 0.617 2.154E-02 1.249E-01 302.864 0.472 6.725E-02 2.263E-01 ENSG00000065970 FOXJ2 124.864 0.760 2.171E-02 1.253E-01 114.302 0.434 2.000E-01 4.527E-01 ENSG00000147642 SYBU 37.352 1.090 2.184E-02 1.258E-01 22.685 1.113 2.226E-02 1.062E-01 ENSG00000106591 MRPL32 180.887 0.832 2.193E-02 1.263E-01 157.782 0.101 7.761E-01 9.023E-01 ENSG00000137185 ZSCAN9 94.560 0.959 2.230E-02 1.275E-01 73.211 0.405 3.051E-01 5.723E-01 ENSG00000127720 METTL25 34.913 1.090 2.231E-02 1.275E-01 14.095 -0.707 1.492E-01 3.811E-01 ENSG00000166233 ARIH1 348.608 0.583 2.232E-02 1.275E-01 299.186 0.040 8.899E-01 9.560E-01 ENSG00000135999 EPC2 277.384 0.631 2.244E-02 1.280E-01 292.745 0.457 6.767E-02 2.273E-01 ENSG00000080822 CLDND1 100.284 0.906 2.269E-02 1.291E-01 68.373 0.220 5.775E-01 7.904E-01 ENSG00000078699 CBFA2T2 224.291 0.643 2.275E-02 1.293E-01 207.533 0.207 4.552E-01 7.049E-01 ENSG00000198074 AKR1B10 89.983 0.856 2.317E-02 1.308E-01 77.351 0.410 3.080E-01 5.754E-01 ENSG00000135241 PNPLA8 105.471 0.821 2.325E-02 1.310E-01 84.109 0.402 2.764E-01 5.445E-01 ENSG00000196839 ADA 57.303 1.018 2.392E-02 1.331E-01 49.518 0.185 6.701E-01 8.453E-01 ENSG00000114541 FRMD4B 45.431 1.040 2.412E-02 1.338E-01 30.362 0.150 7.505E-01 8.882E-01 ENSG00000076770 MBNL3 2132.837 -0.364 2.417E-02 1.339E-01 2282.950 -0.502 9.979E-04 1.059E-02 ENSG00000167635 ZNF146 225.601 0.811 2.469E-02 1.357E-01 205.931 0.421 2.086E-01 4.646E-01 ENSG00000112339 HBS1L 277.464 0.608 2.468E-02 1.357E-01 273.146 0.212 3.761E-01 6.422E-01 ENSG00000109775 UFSP2 221.338 0.666 2.479E-02 1.359E-01 191.578 -0.046 8.839E-01 9.535E-01 ENSG00000050393 MCUR1 374.520 0.557 2.478E-02 1.359E-01 338.580 0.220 3.272E-01 5.952E-01 ENSG00000253729 PRKDC 954.155 -0.494 2.487E-02 1.363E-01 1026.800 -0.515 1.770E-03 1.652E-02 ENSG00000158122 AAED1 111.426 0.784 2.496E-02 1.365E-01 108.608 0.144 6.738E-01 8.476E-01 ENSG00000163608 NEPRO 274.888 0.601 2.495E-02 1.365E-01 232.436 0.480 5.901E-02 2.091E-01 ENSG00000064932 SBNO2 81.827 0.922 2.520E-02 1.376E-01 94.689 0.415 2.575E-01 5.228E-01 ENSG00000120029 C10orf76 164.814 0.661 2.522E-02 1.376E-01 137.490 0.083 7.801E-01 9.051E-01 ENSG00000008394 MGST1 1024.487 0.575 2.522E-02 1.376E-01 818.509 0.238 3.271E-01 5.952E-01 ENSG00000238172 RPS2P35 35.160 1.055 2.532E-02 1.380E-01 39.137 0.226 6.078E-01 8.085E-01 ENSG00000162368 CMPK1 462.070 0.549 2.535E-02 1.380E-01 379.877 -0.272 2.035E-01 4.568E-01 ENSG00000170310 STX8 181.814 0.684 2.539E-02 1.382E-01 191.908 0.453 1.892E-01 4.372E-01 ENSG00000107643 MAPK8 162.237 0.750 2.558E-02 1.389E-01 135.707 0.311 4.091E-01 6.704E-01 ENSG00000091542 ALKBH5 569.942 0.518 2.566E-02 1.390E-01 484.507 0.154 5.162E-01 7.482E-01 ENSG00000215908 CROCCP2 175.564 0.676 2.568E-02 1.390E-01 185.845 0.271 3.049E-01 5.721E-01 ENSG00000186193 SAPCD2 891.372 -0.431 2.574E-02 1.393E-01 734.690 -0.655 1.988E-03 1.786E-02 ENSG00000108561 C1QBP 806.784 0.562 2.579E-02 1.394E-01 624.237 -0.498 2.937E-01 5.613E-01 ENSG00000112208 BAG2 349.390 0.612 2.612E-02 1.407E-01 381.790 0.309 1.641E-01 4.053E-01 ENSG00000104381 GDAP1 100.348 0.769 2.617E-02 1.409E-01 84.518 -0.347 3.195E-01 5.876E-01 ENSG00000096070 BRPF3 123.142 0.760 2.634E-02 1.414E-01 97.911 0.324 3.689E-01 6.352E-01 ENSG00000143862 ARL8A 500.462 0.608 2.631E-02 1.414E-01 386.929 0.409 1.059E-01 3.054E-01 ENSG00000158158 CNNM4 102.148 0.861 2.637E-02 1.415E-01 77.919 0.376 3.288E-01 5.963E-01 ENSG00000156136 DCK 51.565 0.945 2.644E-02 1.417E-01 39.374 -0.251 5.716E-01 7.863E-01 ENSG00000101856 PGRMC1 325.956 0.604 2.681E-02 1.431E-01 277.451 -0.115 6.309E-01 8.218E-01 ENSG00000197989 SNHG12 282.850 0.616 2.688E-02 1.432E-01 337.231 0.386 1.156E-01 3.231E-01 ENSG00000196262 PPIA 685.187 -0.468 2.700E-02 1.434E-01 628.891 -0.739 1.318E-04 2.072E-03 ENSG00000214087 ARL16 68.460 0.958 2.703E-02 1.435E-01 57.671 0.351 4.183E-01 6.772E-01 ENSG00000105085 MED26 113.479 0.924 2.737E-02 1.445E-01 83.350 0.495 1.841E-01 4.309E-01 ENSG00000136098 NEK3 252.804 0.642 2.733E-02 1.445E-01 220.579 0.373 1.476E-01 3.789E-01 ENSG00000109184 DCUN1D4 168.887 0.783 2.774E-02 1.459E-01 174.105 0.342 2.411E-01 5.038E-01 ENSG00000175105 ZNF654 70.221 0.976 2.794E-02 1.465E-01 58.212 0.285 4.848E-01 7.260E-01 ENSG00000066583 ISOC1 256.723 0.770 2.820E-02 1.474E-01 216.273 -0.491 1.315E-01 3.513E-01 ENSG00000159461 AMFR 474.495 0.524 2.844E-02 1.483E-01 422.620 0.468 2.697E-02 1.220E-01 ENSG00000130935 NOL11 866.496 -0.394 2.943E-02 1.523E-01 738.299 -0.699 2.277E-04 3.217E-03 ENSG00000230002 ALMS1-IT1 30.199 1.042 2.950E-02 1.524E-01 20.435 1.401 4.130E-03 3.159E-02 ENSG00000000419 DPM1 540.332 0.666 2.952E-02 1.524E-01 438.558 0.113 6.391E-01 8.255E-01 ENSG00000100804 PSMB5 3320.392 -0.333 2.949E-02 1.524E-01 3228.766 -0.558 2.455E-04 3.429E-03 ENSG00000204147 ASAH2B 39.775 1.069 2.971E-02 1.529E-01 8.972 0.195 6.776E-01 8.496E-01 ENSG00000173681 BCLAF3 57.519 0.973 2.980E-02 1.532E-01 69.093 0.257 5.370E-01 7.621E-01 ENSG00000084636 COL16A1 73.473 0.864 2.984E-02 1.532E-01 49.257 0.290 5.153E-01 7.474E-01 ENSG00000164169 PRMT9 60.926 0.926 2.999E-02 1.538E-01 43.930 0.212 6.298E-01 8.214E-01 ENSG00000134152 KATNBL1 214.183 0.652 3.020E-02 1.548E-01 141.632 0.050 8.849E-01 9.541E-01 ENSG00000182208 MOB2 89.567 0.870 3.027E-02 1.549E-01 96.330 0.273 4.415E-01 6.953E-01 ENSG00000154710 RABGEF1 59.573 0.904 3.035E-02 1.551E-01 47.679 -0.126 7.657E-01 8.963E-01 ENSG00000164828 SUN1 220.893 0.798 3.044E-02 1.554E-01 173.308 0.051 8.757E-01 9.492E-01 ENSG00000120699 EXOSC8 500.450 0.514 3.050E-02 1.556E-01 422.599 0.246 2.477E-01 5.105E-01 ENSG00000139793 MBNL2 239.856 0.585 3.052E-02 1.556E-01 235.780 0.453 8.480E-02 2.639E-01 ENSG00000139132 FGD4 132.310 0.682 3.113E-02 1.575E-01 120.529 0.380 2.827E-01 5.496E-01 ENSG00000247626 MARS2 47.712 1.025 3.146E-02 1.585E-01 29.727 -0.312 5.238E-01 7.529E-01 ENSG00000113638 TTC33 43.467 0.981 3.164E-02 1.588E-01 34.623 -0.126 7.966E-01 9.128E-01 ENSG00000171100 MTM1 38.323 1.007 3.203E-02 1.599E-01 46.823 0.268 5.272E-01 7.550E-01 ENSG00000252498 RNU6-1016P 40.242 0.974 3.201E-02 1.599E-01 30.529 -0.514 2.738E-01 5.413E-01 ENSG00000146416 AIG1 437.837 -0.480 3.204E-02 1.599E-01 420.094 -0.592 8.991E-03 5.617E-02 ENSG00000100207 TCF20 231.064 0.676 3.211E-02 1.600E-01 182.951 0.483 1.103E-01 3.134E-01 ENSG00000145990 GFOD1 210.146 0.609 3.218E-02 1.602E-01 213.464 0.291 2.789E-01 5.463E-01 ENSG00000242259 C22orf39 346.543 0.530 3.228E-02 1.605E-01 304.801 0.324 1.447E-01 3.741E-01 ENSG00000100567 PSMA3 830.141 0.549 3.240E-02 1.609E-01 625.658 -0.130 5.145E-01 7.466E-01 ENSG00000265096 C1QTNF1-AS1 28.572 -1.052 3.257E-02 1.613E-01 33.573 -1.205 7.544E-03 4.979E-02 ENSG00000169032 MAP2K1 68.065 0.983 3.278E-02 1.619E-01 74.337 0.393 2.976E-01 5.654E-01 ENSG00000169193 CCDC126 34.679 1.006 3.290E-02 1.622E-01 20.447 0.651 1.837E-01 4.307E-01 ENSG00000101608 MYL12A 843.392 0.568 3.305E-02 1.627E-01 643.654 -0.086 7.354E-01 8.806E-01 ENSG00000227036 LINC00511 150.657 0.673 3.309E-02 1.628E-01 155.799 0.368 2.281E-01 4.879E-01 ENSG00000198482 ZNF808 37.586 1.007 3.317E-02 1.631E-01 39.296 -0.008 9.858E-01 9.929E-01 ENSG00000099219 ERMP1 246.616 0.587 3.322E-02 1.632E-01 219.049 0.024 9.341E-01 9.733E-01 ENSG00000113595 TRIM23 114.063 0.756 3.340E-02 1.636E-01 87.477 0.477 2.428E-01 5.062E-01 ENSG00000206562 METTL6 71.530 0.829 3.348E-02 1.639E-01 60.046 0.302 4.428E-01 6.960E-01 ENSG00000196646 ZNF136 39.849 1.032 3.364E-02 1.643E-01 39.725 0.279 5.368E-01 7.619E-01 ENSG00000146232 NFKBIE 81.258 0.814 3.396E-02 1.655E-01 79.564 0.431 2.545E-01 5.194E-01 ENSG00000115128 SF3B6 497.837 0.593 3.401E-02 1.656E-01 403.308 -0.100 7.134E-01 8.683E-01 ENSG00000213995 NAXD 123.847 0.715 3.411E-02 1.658E-01 101.111 -0.098 7.824E-01 9.062E-01 ENSG00000247077 PGAM5 323.892 0.581 3.423E-02 1.664E-01 232.470 0.392 1.544E-01 3.895E-01 ENSG00000142867 BCL10 59.288 0.926 3.434E-02 1.667E-01 58.178 0.238 5.695E-01 7.855E-01 ENSG00000162909 CAPN2 146.554 0.695 3.449E-02 1.671E-01 123.199 -0.211 5.129E-01 7.451E-01 ENSG00000158480 SPATA2 229.119 0.730 3.452E-02 1.671E-01 198.105 -0.103 7.480E-01 8.868E-01 ENSG00000213380 COG8 407.741 -0.488 3.473E-02 1.675E-01 421.010 -0.857 2.162E-04 3.069E-03 ENSG00000066651 TRMT11 210.048 0.581 3.491E-02 1.682E-01 234.795 0.402 1.431E-01 3.712E-01 ENSG00000172354 GNB2 242.562 0.777 3.511E-02 1.688E-01 182.981 0.286 4.497E-01 7.013E-01 ENSG00000011198 ABHD5 35.623 0.990 3.516E-02 1.690E-01 30.817 -0.427 3.646E-01 6.317E-01 ENSG00000049283 EPN3 78.598 0.821 3.579E-02 1.710E-01 79.146 0.215 5.778E-01 7.905E-01 ENSG00000127922 SEM1 1385.474 0.532 3.591E-02 1.714E-01 1185.498 -0.099 6.481E-01 8.311E-01 ENSG00000144035 NAT8 35.702 1.016 3.625E-02 1.724E-01 50.992 0.386 3.590E-01 6.273E-01 ENSG00000128534 LSM8 207.008 0.692 3.664E-02 1.734E-01 196.000 -0.360 3.026E-01 5.704E-01 ENSG00000172432 GTPBP2 47.643 1.018 3.681E-02 1.739E-01 13.716 -0.181 7.120E-01 8.676E-01 ENSG00000198862 LTN1 331.188 0.537 3.688E-02 1.742E-01 343.797 0.112 6.051E-01 8.071E-01 ENSG00000118242 MREG 87.594 0.830 3.694E-02 1.743E-01 68.709 0.323 3.817E-01 6.469E-01 ENSG00000132256 TRIM5 75.033 0.797 3.704E-02 1.743E-01 56.364 0.118 7.775E-01 9.031E-01 ENSG00000183726 TMEM50A 246.559 0.705 3.703E-02 1.743E-01 196.217 -0.011 9.709E-01 9.873E-01 ENSG00000141646 SMAD4 211.658 0.568 3.700E-02 1.743E-01 209.142 0.320 2.197E-01 4.792E-01 ENSG00000148950 IMMP1L 232.135 0.595 3.711E-02 1.745E-01 192.771 -0.539 6.997E-02 2.323E-01 ENSG00000175354 PTPN2 282.664 0.575 3.731E-02 1.753E-01 286.819 0.299 2.000E-01 4.527E-01 ENSG00000102221 JADE3 77.299 0.838 3.795E-02 1.775E-01 90.228 0.292 4.137E-01 6.729E-01 ENSG00000119537 KDSR 201.068 0.605 3.807E-02 1.779E-01 207.539 0.295 2.721E-01 5.390E-01 ENSG00000229659 RPL26P6 33.865 0.980 3.808E-02 1.779E-01 19.651 -0.074 8.783E-01 9.504E-01 ENSG00000240344 PPIL3 139.785 0.798 3.813E-02 1.780E-01 121.270 0.461 2.272E-01 4.872E-01 ENSG00000173166 RAPH1 91.196 0.811 3.844E-02 1.791E-01 86.680 -0.158 6.876E-01 8.546E-01 ENSG00000120992 LYPLA1 319.607 0.607 3.842E-02 1.791E-01 324.737 0.099 6.808E-01 8.508E-01 ENSG00000105707 HPN 326.545 -0.492 3.880E-02 1.800E-01 257.928 -0.627 1.028E-02 6.210E-02 ENSG00000085788 DDHD2 169.861 0.607 3.886E-02 1.802E-01 160.887 -0.109 7.308E-01 8.778E-01 ENSG00000230177 AL080317.1 16.345 -1.011 3.896E-02 1.805E-01 31.156 -1.044 2.856E-02 1.267E-01 ENSG00000127955 GNAI1 37.118 0.987 3.918E-02 1.813E-01 27.551 0.393 4.112E-01 6.715E-01 ENSG00000243147 MRPL33 1163.889 0.507 4.011E-02 1.842E-01 863.117 0.081 6.940E-01 8.588E-01 ENSG00000129128 SPCS3 828.555 -0.443 4.024E-02 1.846E-01 803.037 -0.811 1.036E-04 1.677E-03 ENSG00000248049 UBA6-AS1 78.682 0.852 4.038E-02 1.850E-01 81.017 0.264 4.900E-01 7.296E-01 ENSG00000205302 SNX2 347.655 0.571 4.045E-02 1.851E-01 295.096 0.473 7.204E-02 2.370E-01 ENSG00000107537 PHYH 209.194 0.570 4.041E-02 1.851E-01 185.234 -0.122 6.470E-01 8.303E-01 ENSG00000133935 ERG28 326.209 -0.497 4.049E-02 1.851E-01 282.771 -0.718 7.269E-03 4.849E-02 ENSG00000128000 ZNF780B 24.544 -1.004 4.053E-02 1.852E-01 32.119 -1.295 7.897E-03 5.143E-02 ENSG00000142949 PTPRF 1377.883 -0.378 4.083E-02 1.862E-01 1302.974 -0.608 1.450E-03 1.407E-02 ENSG00000141543 EIF4A3 1086.012 0.435 4.095E-02 1.866E-01 905.956 -0.554 3.221E-02 1.378E-01 ENSG00000197857 ZNF44 112.610 0.721 4.097E-02 1.866E-01 82.834 0.454 1.930E-01 4.424E-01 ENSG00000182372 CLN8 124.975 0.700 4.170E-02 1.891E-01 141.385 0.420 2.151E-01 4.729E-01 ENSG00000119673 ACOT2 244.791 0.557 4.206E-02 1.902E-01 208.262 0.076 7.967E-01 9.128E-01 ENSG00000197147 LRRC8B 164.483 0.585 4.210E-02 1.902E-01 139.618 0.308 3.134E-01 5.815E-01 ENSG00000145414 NAF1 107.536 0.744 4.214E-02 1.902E-01 117.294 0.416 1.800E-01 4.265E-01 ENSG00000198146 ZNF770 555.613 -0.416 4.224E-02 1.905E-01 460.646 -0.527 2.326E-02 1.093E-01 ENSG00000115904 SOS1 427.182 -0.443 4.328E-02 1.943E-01 388.609 -0.770 1.651E-03 1.560E-02 ENSG00000150527 CTAGE5 517.864 0.576 4.378E-02 1.959E-01 472.440 0.486 2.557E-02 1.173E-01 ENSG00000088766 CRLS1 819.031 0.577 4.392E-02 1.964E-01 710.684 -0.147 7.251E-01 8.744E-01 ENSG00000118369 USP35 42.267 0.958 4.398E-02 1.965E-01 39.903 0.348 4.200E-01 6.787E-01 ENSG00000067057 PFKP 44.720 0.945 4.397E-02 1.965E-01 38.461 0.364 3.988E-01 6.616E-01 ENSG00000251685 UGT2B27P 23.925 -0.980 4.404E-02 1.966E-01 33.068 -1.507 1.571E-03 1.499E-02 ENSG00000135919 SERPINE2 524.455 0.509 4.423E-02 1.974E-01 428.304 0.396 7.627E-02 2.463E-01 ENSG00000049860 HEXB 397.661 0.609 4.429E-02 1.975E-01 336.502 0.205 4.213E-01 6.798E-01 ENSG00000196387 ZNF140 38.623 0.919 4.446E-02 1.982E-01 28.071 0.298 5.277E-01 7.553E-01 ENSG00000111711 GOLT1B 202.350 0.593 4.451E-02 1.983E-01 150.743 -0.051 8.777E-01 9.501E-01 ENSG00000100612 DHRS7 157.288 0.670 4.455E-02 1.984E-01 150.826 0.437 2.247E-01 4.842E-01 ENSG00000100902 PSMA6 87.876 0.795 4.479E-02 1.992E-01 69.006 0.097 8.232E-01 9.275E-01 ENSG00000139197 PEX5 90.284 0.864 4.482E-02 1.993E-01 58.764 0.153 7.387E-01 8.825E-01 ENSG00000123595 RAB9A 50.075 0.947 4.499E-02 1.998E-01 42.925 0.320 4.708E-01 7.158E-01 ENSG00000175110 MRPS22 238.480 0.769 4.542E-02 2.010E-01 231.508 0.221 4.826E-01 7.246E-01 ENSG00000163032 VSNL1 349.529 -0.497 4.556E-02 2.013E-01 328.114 -0.592 1.067E-02 6.368E-02 ENSG00000106537 TSPAN13 41.478 0.887 4.620E-02 2.030E-01 52.535 -0.169 6.904E-01 8.565E-01 ENSG00000111912 NCOA7 261.070 0.529 4.670E-02 2.045E-01 237.605 0.205 4.381E-01 6.932E-01 ENSG00000173531 MST1 468.269 0.504 4.684E-02 2.048E-01 485.770 0.408 8.475E-02 2.639E-01 ENSG00000122884 P4HA1 662.343 -0.393 4.692E-02 2.051E-01 668.012 -0.750 1.226E-04 1.942E-03 ENSG00000054965 FAM168A 51.242 0.923 4.701E-02 2.052E-01 58.599 0.377 3.509E-01 6.181E-01 ENSG00000118418 HMGN3 649.330 -0.403 4.705E-02 2.052E-01 611.137 -0.501 1.453E-02 7.949E-02 ENSG00000112234 FBXL4 98.026 0.796 4.717E-02 2.055E-01 64.281 -0.097 8.049E-01 9.173E-01 ENSG00000153485 TMEM251 49.974 0.952 4.737E-02 2.061E-01 31.001 -0.188 6.949E-01 8.593E-01 ENSG00000160050 CCDC28B 39.248 0.919 4.742E-02 2.062E-01 36.535 0.454 3.363E-01 6.046E-01 ENSG00000116954 RRAGC 34.133 0.918 4.755E-02 2.065E-01 39.709 -0.314 4.874E-01 7.278E-01 ENSG00000161956 SENP3 147.074 0.656 4.778E-02 2.071E-01 114.089 0.420 2.445E-01 5.075E-01 ENSG00000130699 TAF4 129.628 0.690 4.798E-02 2.075E-01 118.998 0.205 5.858E-01 7.957E-01 ENSG00000257727 CNPY2 641.864 -0.428 4.822E-02 2.081E-01 625.379 -0.682 1.295E-03 1.293E-02 ENSG00000163428 LRRC58 728.044 -0.393 4.905E-02 2.103E-01 636.528 -0.558 6.665E-03 4.544E-02 ENSG00000168394 TAP1 206.196 0.665 4.940E-02 2.112E-01 187.437 0.235 3.901E-01 6.539E-01 ENSG00000169926 KLF13 248.054 0.568 4.953E-02 2.114E-01 250.378 0.394 9.557E-02 2.847E-01 ENSG00000133678 TMEM254 92.942 0.741 5.001E-02 2.129E-01 78.319 0.129 7.205E-01 8.713E-01 ENSG00000100625 SIX4 48.898 0.880 5.091E-02 2.156E-01 30.314 0.313 5.005E-01 7.375E-01 ENSG00000116213 WRAP73 159.552 0.783 5.130E-02 2.164E-01 135.252 -0.664 8.466E-02 2.638E-01 ENSG00000130787 HIP1R 43.384 0.886 5.196E-02 2.182E-01 52.418 0.447 2.910E-01 5.584E-01 ENSG00000075643 MOCOS 273.309 0.510 5.209E-02 2.185E-01 286.645 0.299 2.822E-01 5.493E-01 ENSG00000106554 CHCHD3 191.356 0.715 5.212E-02 2.185E-01 165.035 0.032 9.276E-01 9.717E-01 ENSG00000146083 RNF44 264.577 0.560 5.231E-02 2.191E-01 258.210 -0.110 6.476E-01 8.307E-01 ENSG00000096717 SIRT1 129.444 0.703 5.258E-02 2.197E-01 107.769 0.233 5.242E-01 7.533E-01 ENSG00000187522 HSPA14 164.886 0.649 5.283E-02 2.202E-01 152.755 -0.124 6.860E-01 8.537E-01 ENSG00000107281 NPDC1 50.510 0.851 5.294E-02 2.205E-01 80.396 -0.045 9.164E-01 9.673E-01 ENSG00000164168 TMEM184C 107.154 0.786 5.326E-02 2.215E-01 85.019 -0.393 2.878E-01 5.549E-01 ENSG00000164305 CASP3 223.289 0.645 5.337E-02 2.219E-01 279.313 0.049 8.376E-01 9.338E-01 ENSG00000165832 TRUB1 231.784 0.549 5.355E-02 2.224E-01 201.783 -0.456 1.380E-01 3.621E-01 ENSG00000052723 SIKE1 143.411 0.675 5.401E-02 2.234E-01 126.299 0.023 9.419E-01 9.760E-01 ENSG00000141446 ESCO1 277.165 0.562 5.412E-02 2.238E-01 301.087 0.302 2.286E-01 4.882E-01 ENSG00000197885 NKIRAS1 45.945 0.861 5.451E-02 2.250E-01 49.220 0.210 6.197E-01 8.151E-01 ENSG00000163864 NMNAT3 43.772 0.874 5.456E-02 2.251E-01 34.271 0.099 8.332E-01 9.319E-01 ENSG00000035681 NSMAF 151.382 0.601 5.499E-02 2.263E-01 120.272 -0.410 2.035E-01 4.568E-01 ENSG00000103671 TRIP4 136.111 0.611 5.512E-02 2.266E-01 129.759 0.344 2.635E-01 5.294E-01 ENSG00000090382 LYZ 1337.691 -0.411 5.536E-02 2.273E-01 1278.851 -0.879 6.914E-06 1.670E-04 ENSG00000175832 ETV4 704.004 -0.474 5.559E-02 2.280E-01 570.935 -0.560 5.696E-03 4.052E-02 ENSG00000139597 N4BP2L1 96.264 0.692 5.563E-02 2.281E-01 60.594 -0.345 4.253E-01 6.830E-01 ENSG00000126746 ZNF384 58.464 0.817 5.572E-02 2.281E-01 40.495 0.231 6.235E-01 8.172E-01 ENSG00000088305 DNMT3B 247.634 0.522 5.587E-02 2.284E-01 193.876 -0.006 9.808E-01 9.912E-01 ENSG00000156508 EEF1A1 702.194 0.502 5.608E-02 2.290E-01 825.657 0.170 3.504E-01 6.175E-01 ENSG00000159216 RUNX1 82.879 0.846 5.649E-02 2.299E-01 58.009 0.184 6.365E-01 8.244E-01 ENSG00000113719 ERGIC1 1092.214 -0.373 5.661E-02 2.301E-01 933.200 -0.599 3.071E-03 2.522E-02 ENSG00000255529 POLR2M 138.307 0.806 5.676E-02 2.303E-01 134.313 0.230 5.019E-01 7.383E-01 ENSG00000145287 PLAC8 87.772 0.729 5.670E-02 2.303E-01 80.626 -0.139 7.175E-01 8.695E-01 ENSG00000112699 GMDS 683.704 -0.384 5.689E-02 2.306E-01 634.992 -0.635 4.262E-04 5.339E-03 ENSG00000079739 PGM1 353.377 -0.489 5.693E-02 2.307E-01 267.122 -0.593 2.131E-02 1.032E-01 ENSG00000164758 MED30 67.966 0.872 5.732E-02 2.316E-01 53.556 0.195 6.235E-01 8.172E-01 ENSG00000136932 TRMO 95.077 0.765 5.766E-02 2.320E-01 73.861 0.231 5.175E-01 7.487E-01 ENSG00000120756 PLS1 78.481 0.715 5.765E-02 2.320E-01 77.635 -0.067 8.525E-01 9.390E-01 ENSG00000198839 ZNF277 118.248 0.675 5.768E-02 2.320E-01 86.999 -0.168 7.108E-01 8.668E-01 ENSG00000173848 NET1 530.258 0.538 5.777E-02 2.323E-01 480.544 0.277 2.303E-01 4.908E-01 ENSG00000081181 ARG2 116.073 0.671 5.809E-02 2.331E-01 113.303 -0.547 9.935E-02 2.927E-01 ENSG00000161800 RACGAP1 89.332 0.717 5.824E-02 2.336E-01 86.681 -0.354 3.178E-01 5.858E-01 ENSG00000156171 DRAM2 93.376 0.794 5.842E-02 2.340E-01 66.448 -0.410 3.197E-01 5.877E-01 ENSG00000171735 CAMTA1 263.038 0.533 5.968E-02 2.381E-01 232.760 0.110 6.821E-01 8.518E-01 ENSG00000162601 MYSM1 145.699 0.586 5.983E-02 2.383E-01 134.652 0.021 9.418E-01 9.760E-01 ENSG00000204611 ZNF616 41.579 0.852 6.049E-02 2.401E-01 30.896 -1.285 5.655E-03 4.033E-02 ENSG00000126249 PDCD2L 184.016 0.764 6.065E-02 2.404E-01 147.600 0.384 3.235E-01 5.915E-01 ENSG00000117519 CNN3 547.437 0.617 6.072E-02 2.405E-01 369.774 -0.161 6.321E-01 8.221E-01 ENSG00000240429 LRRFIP1P1 40.777 0.839 6.096E-02 2.408E-01 24.539 1.149 1.540E-02 8.276E-02 ENSG00000065600 TMEM206 30.404 0.893 6.153E-02 2.424E-01 46.044 0.357 4.200E-01 6.787E-01 ENSG00000108375 RNF43 582.831 -0.488 6.174E-02 2.431E-01 552.828 -0.663 1.730E-03 1.621E-02 ENSG00000237550 RPL9P9 133.211 0.743 6.229E-02 2.446E-01 74.685 0.239 5.906E-01 7.986E-01 ENSG00000159753 CARMIL2 34.128 0.881 6.270E-02 2.457E-01 32.151 0.379 4.222E-01 6.805E-01 ENSG00000066855 MTFR1 185.180 0.619 6.306E-02 2.466E-01 176.667 -0.190 5.769E-01 7.902E-01 ENSG00000133641 C12orf29 80.337 0.822 6.310E-02 2.466E-01 62.841 -0.061 8.820E-01 9.523E-01 ENSG00000104626 ERI1 129.636 0.639 6.319E-02 2.467E-01 106.198 0.468 1.671E-01 4.099E-01 ENSG00000273611 ZNHIT3 274.101 0.590 6.318E-02 2.467E-01 239.299 0.009 9.721E-01 9.878E-01 ENSG00000101138 CSTF1 314.118 -0.470 6.330E-02 2.469E-01 261.350 -0.615 1.647E-02 8.665E-02 ENSG00000165304 MELK 178.518 0.557 6.403E-02 2.490E-01 126.821 -0.698 8.458E-02 2.638E-01 ENSG00000196151 WDSUB1 34.442 0.892 6.462E-02 2.502E-01 29.193 -0.298 5.280E-01 7.555E-01 ENSG00000047634 SCML1 164.831 0.687 6.467E-02 2.502E-01 144.880 -0.519 1.124E-01 3.173E-01 ENSG00000197019 SERTAD1 107.019 0.639 6.451E-02 2.502E-01 98.608 -0.085 8.094E-01 9.197E-01 ENSG00000173273 TNKS 194.384 0.604 6.463E-02 2.502E-01 182.888 0.241 4.530E-01 7.035E-01 ENSG00000119185 ITGB1BP1 338.749 -0.449 6.461E-02 2.502E-01 308.633 -0.545 2.502E-02 1.154E-01 ENSG00000100105 PATZ1 368.595 -0.480 6.467E-02 2.502E-01 317.466 -0.618 6.163E-03 4.278E-02 ENSG00000114378 HYAL1 378.013 -0.478 6.444E-02 2.502E-01 409.067 -0.859 4.198E-04 5.277E-03 ENSG00000139990 DCAF5 293.781 0.509 6.560E-02 2.522E-01 265.543 -0.157 5.900E-01 7.982E-01 ENSG00000158402 CDC25C 292.321 -0.486 6.568E-02 2.524E-01 324.224 -0.712 2.170E-03 1.906E-02 ENSG00000163867 ZMYM6 48.825 0.850 6.592E-02 2.530E-01 46.854 -0.534 2.077E-01 4.632E-01 ENSG00000136379 ABHD17C 356.871 -0.462 6.616E-02 2.534E-01 307.782 -0.502 3.153E-02 1.357E-01 ENSG00000259758 lnc-AGO2-1 289.597 0.573 6.618E-02 2.534E-01 217.997 -0.129 6.538E-01 8.341E-01 ENSG00000014164 ZC3H3 45.218 0.819 6.705E-02 2.555E-01 38.188 0.041 9.256E-01 9.708E-01 ENSG00000215154 AC141586.1 61.177 0.733 6.728E-02 2.560E-01 51.528 0.346 4.251E-01 6.829E-01 ENSG00000111215 PRR4 26.861 -0.895 6.780E-02 2.572E-01 33.021 -1.704 2.593E-04 3.590E-03 ENSG00000092871 RFFL 200.481 0.547 6.819E-02 2.579E-01 197.907 0.355 2.575E-01 5.228E-01 ENSG00000145016 RUBCN 96.131 0.656 6.844E-02 2.585E-01 78.623 -0.006 9.878E-01 9.936E-01 ENSG00000121879 PIK3CA 149.144 0.580 6.878E-02 2.590E-01 132.636 0.482 1.114E-01 3.157E-01 ENSG00000139618 BRCA2 326.537 -0.458 6.877E-02 2.590E-01 305.692 -0.509 6.203E-02 2.156E-01 ENSG00000213024 NUP62 607.540 -0.387 6.928E-02 2.599E-01 554.710 -0.644 9.274E-04 9.949E-03 ENSG00000175220 ARHGAP1 412.962 -0.475 6.936E-02 2.601E-01 314.635 -0.649 8.173E-03 5.258E-02 ENSG00000224597 SVIL-AS1 195.218 0.517 6.960E-02 2.607E-01 183.319 0.378 1.708E-01 4.145E-01 ENSG00000213281 NRAS 323.407 0.502 7.016E-02 2.621E-01 284.417 -0.089 7.568E-01 8.920E-01 ENSG00000148218 ALAD 162.035 0.590 7.025E-02 2.623E-01 170.279 0.297 3.283E-01 5.962E-01 ENSG00000148660 CAMK2G 144.395 0.654 7.076E-02 2.635E-01 95.651 0.378 3.016E-01 5.693E-01 ENSG00000100836 PABPN1 901.503 -0.397 7.086E-02 2.637E-01 745.507 -0.598 5.464E-03 3.926E-02 ENSG00000178338 ZNF354B 36.188 0.839 7.089E-02 2.638E-01 29.697 0.836 8.483E-02 2.639E-01 ENSG00000196284 SUPT3H 81.289 0.703 7.155E-02 2.656E-01 98.286 0.482 1.487E-01 3.807E-01 ENSG00000153391 INO80C 83.540 0.692 7.171E-02 2.661E-01 58.413 0.160 7.022E-01 8.626E-01 ENSG00000197045 GMFB 253.873 0.549 7.363E-02 2.711E-01 238.183 -0.128 6.086E-01 8.086E-01 ENSG00000137814 HAUS2 245.115 0.572 7.369E-02 2.711E-01 254.857 0.388 1.424E-01 3.703E-01 ENSG00000128654 MTX2 169.367 0.715 7.382E-02 2.714E-01 129.572 -0.460 1.981E-01 4.500E-01 ENSG00000119787 ATL2 332.416 0.554 7.385E-02 2.714E-01 260.213 -0.096 7.271E-01 8.755E-01 ENSG00000113597 TRAPPC13 34.030 0.850 7.410E-02 2.719E-01 31.704 -0.552 2.409E-01 5.034E-01 ENSG00000029639 TFB1M 934.883 -0.373 7.416E-02 2.720E-01 896.309 -0.625 2.213E-04 3.132E-03 ENSG00000168944 CEP120 170.539 0.530 7.452E-02 2.729E-01 172.719 0.061 8.448E-01 9.365E-01 ENSG00000023228 NDUFS1 622.872 -0.400 7.579E-02 2.757E-01 609.891 -0.698 2.733E-04 3.738E-03 ENSG00000138413 IDH1 1010.340 -0.471 7.623E-02 2.769E-01 921.263 -1.093 5.153E-07 1.689E-05 ENSG00000083457 ITGAE 164.256 0.594 7.642E-02 2.771E-01 129.890 -0.160 6.530E-01 8.337E-01 ENSG00000138614 INTS14 141.890 0.697 7.647E-02 2.773E-01 104.785 -0.784 6.144E-02 2.144E-01 ENSG00000091127 PUS7 168.302 0.535 7.674E-02 2.780E-01 150.033 0.213 4.847E-01 7.259E-01 ENSG00000105711 SCN1B 108.673 0.635 7.681E-02 2.781E-01 79.486 -0.056 8.865E-01 9.547E-01 ENSG00000154582 ELOC 473.343 0.588 7.746E-02 2.793E-01 333.533 0.354 2.083E-01 4.642E-01 ENSG00000061987 MON2 117.605 0.651 7.760E-02 2.798E-01 107.046 -0.434 2.157E-01 4.737E-01 ENSG00000134077 THUMPD3 216.836 0.543 7.781E-02 2.804E-01 227.442 -0.133 6.181E-01 8.146E-01 ENSG00000122550 KLHL7 51.883 0.815 7.787E-02 2.805E-01 38.331 0.007 9.880E-01 9.936E-01 ENSG00000141682 PMAIP1 45.446 0.795 7.790E-02 2.805E-01 36.966 0.325 4.799E-01 7.222E-01 ENSG00000121350 PYROXD1 39.740 0.837 7.815E-02 2.809E-01 42.670 0.308 4.885E-01 7.282E-01 ENSG00000159399 HK2 205.743 0.651 7.838E-02 2.810E-01 180.995 -0.016 9.556E-01 9.811E-01 ENSG00000162729 IGSF8 87.038 0.649 7.838E-02 2.810E-01 77.954 -0.094 7.999E-01 9.150E-01 ENSG00000149313 AASDHPPT 286.322 0.501 7.832E-02 2.810E-01 344.340 0.135 5.888E-01 7.977E-01 ENSG00000142197 DOPEY2 51.593 0.767 7.873E-02 2.816E-01 39.484 -0.018 9.675E-01 9.863E-01 ENSG00000148468 FAM171A1 358.294 -0.451 7.929E-02 2.828E-01 304.471 -0.810 5.888E-04 6.900E-03 ENSG00000077235 GTF3C1 493.272 -0.484 7.969E-02 2.837E-01 412.887 -0.738 4.248E-03 3.226E-02 ENSG00000139496 NUP58 210.896 0.547 8.061E-02 2.853E-01 190.235 -0.087 7.533E-01 8.903E-01 ENSG00000169299 PGM2 120.107 0.632 8.088E-02 2.860E-01 85.893 -0.145 6.959E-01 8.597E-01 ENSG00000148291 SURF2 126.561 0.594 8.097E-02 2.862E-01 144.194 0.188 5.265E-01 7.549E-01 ENSG00000160271 RALGDS 172.722 0.703 8.199E-02 2.885E-01 161.523 0.486 1.447E-01 3.741E-01 ENSG00000103187 COTL1 297.566 -0.484 8.233E-02 2.888E-01 207.029 -0.506 6.400E-02 2.200E-01 ENSG00000137714 FDX1 220.728 0.559 8.282E-02 2.895E-01 210.263 -0.255 4.055E-01 6.670E-01 ENSG00000186020 ZNF529 49.914 0.746 8.305E-02 2.900E-01 47.115 0.446 3.150E-01 5.830E-01 ENSG00000034693 PEX3 98.299 0.596 8.306E-02 2.900E-01 103.866 0.065 8.448E-01 9.365E-01 ENSG00000278845 MRPL45 725.408 -0.435 8.330E-02 2.905E-01 606.310 -0.737 2.297E-03 1.987E-02 ENSG00000038274 MAT2B 194.676 0.657 8.343E-02 2.906E-01 164.772 0.063 8.415E-01 9.359E-01 ENSG00000147044 CASK 158.717 0.587 8.377E-02 2.909E-01 126.262 0.364 3.069E-01 5.742E-01 ENSG00000164983 TMEM65 62.254 0.801 8.444E-02 2.925E-01 52.123 -0.025 9.532E-01 9.800E-01 ENSG00000136560 TANK 141.972 0.544 8.461E-02 2.928E-01 120.792 0.081 8.045E-01 9.170E-01 ENSG00000205213 LGR4 275.484 -0.460 8.537E-02 2.944E-01 301.297 -0.988 2.174E-05 4.476E-04 ENSG00000134996 OSTF1 73.490 0.662 8.564E-02 2.949E-01 67.681 0.496 2.113E-01 4.681E-01 ENSG00000071243 ING3 235.641 0.504 8.565E-02 2.949E-01 190.598 0.468 8.541E-02 2.650E-01 ENSG00000119723 COQ6 114.901 0.694 8.587E-02 2.953E-01 110.020 -0.181 5.855E-01 7.956E-01 ENSG00000126858 RHOT1 117.277 0.598 8.608E-02 2.955E-01 106.514 -0.104 7.702E-01 8.988E-01 ENSG00000196367 TRRAP 52.955 0.755 8.628E-02 2.958E-01 45.210 0.491 2.503E-01 5.141E-01 ENSG00000173889 PHC3 195.587 0.585 8.651E-02 2.965E-01 153.492 0.086 8.312E-01 9.313E-01 ENSG00000049883 PTCD2 92.284 0.643 8.689E-02 2.973E-01 75.691 -0.490 1.810E-01 4.272E-01 ENSG00000111665 CDCA3 315.693 -0.448 8.718E-02 2.978E-01 285.245 -0.813 1.211E-03 1.224E-02 ENSG00000167674 HDGFL2 261.822 0.561 8.730E-02 2.979E-01 302.019 -0.145 5.847E-01 7.951E-01 ENSG00000122126 OCRL 136.799 0.595 8.778E-02 2.991E-01 124.764 -0.217 5.317E-01 7.582E-01 ENSG00000121691 CAT 502.806 -0.379 8.820E-02 2.998E-01 471.658 -0.960 6.632E-06 1.605E-04 ENSG00000119711 ALDH6A1 290.834 -0.499 8.861E-02 3.006E-01 274.200 -1.121 1.920E-05 4.058E-04 ENSG00000147679 UTP23 154.068 0.641 8.882E-02 3.009E-01 174.458 0.357 2.599E-01 5.255E-01 ENSG00000109458 GAB1 104.808 0.599 8.909E-02 3.013E-01 84.213 0.108 7.582E-01 8.920E-01 ENSG00000136478 TEX2 220.440 -0.446 8.923E-02 3.014E-01 215.589 -0.657 2.969E-02 1.301E-01 ENSG00000130529 TRPM4 41.828 0.758 8.935E-02 3.018E-01 28.251 0.678 1.496E-01 3.818E-01 ENSG00000076321 KLHL20 146.426 0.542 8.964E-02 3.024E-01 126.969 0.396 2.886E-01 5.554E-01 ENSG00000182973 CNOT10 167.295 0.520 8.973E-02 3.026E-01 161.811 0.002 9.936E-01 9.964E-01 ENSG00000185324 CDK10 35.729 0.798 8.984E-02 3.027E-01 26.230 0.206 6.733E-01 8.472E-01 ENSG00000100209 HSCB 52.551 0.753 8.982E-02 3.027E-01 53.663 0.034 9.386E-01 9.751E-01 ENSG00000164045 CDC25A 321.269 -0.414 9.024E-02 3.035E-01 315.219 -0.548 3.805E-02 1.543E-01 ENSG00000213064 SFT2D2 348.421 -0.386 9.073E-02 3.046E-01 288.781 -0.907 2.936E-04 3.963E-03 ENSG00000007384 RHBDF1 83.854 0.668 9.088E-02 3.049E-01 73.998 0.473 2.526E-01 5.172E-01 ENSG00000164253 WDR41 130.503 0.526 9.145E-02 3.058E-01 134.094 0.290 3.472E-01 6.151E-01 ENSG00000163904 SENP2 221.809 -0.497 9.187E-02 3.067E-01 163.916 -0.726 2.046E-02 1.003E-01 ENSG00000128578 STRIP2 34.243 0.773 9.247E-02 3.077E-01 29.434 -0.235 6.136E-01 8.116E-01 ENSG00000081026 MAGI3 152.947 0.530 9.295E-02 3.088E-01 114.791 0.284 4.015E-01 6.644E-01 ENSG00000174652 ZNF266 40.317 0.769 9.330E-02 3.096E-01 33.955 0.341 4.654E-01 7.120E-01 ENSG00000100083 GGA1 307.991 -0.421 9.366E-02 3.104E-01 292.288 -0.526 6.601E-02 2.238E-01 ENSG00000090316 MAEA 320.784 -0.457 9.371E-02 3.104E-01 260.556 -0.596 2.568E-02 1.178E-01 ENSG00000168411 RFWD3 639.259 -0.354 9.470E-02 3.130E-01 528.995 -0.875 4.503E-06 1.151E-04 ENSG00000138663 COPS4 114.680 0.575 9.507E-02 3.137E-01 93.475 0.196 5.494E-01 7.700E-01 ENSG00000132854 KANK4 310.747 -0.437 9.523E-02 3.138E-01 261.763 -0.757 1.514E-03 1.456E-02 ENSG00000166478 ZNF143 80.342 0.660 9.561E-02 3.146E-01 60.404 -0.047 9.137E-01 9.664E-01 ENSG00000140632 GLYR1 224.541 -0.490 9.598E-02 3.153E-01 210.997 -0.819 4.633E-03 3.450E-02 ENSG00000109911 ELP4 62.272 0.703 9.633E-02 3.158E-01 44.907 -0.595 1.707E-01 4.145E-01 ENSG00000214595 EML6 248.783 -0.460 9.656E-02 3.160E-01 194.335 -0.722 1.785E-02 9.141E-02 ENSG00000197223 C1D 106.019 0.594 9.690E-02 3.168E-01 95.620 0.387 2.949E-01 5.629E-01 ENSG00000145781 COMMD10 86.755 0.601 9.728E-02 3.176E-01 75.125 0.388 3.264E-01 5.947E-01 ENSG00000178974 FBXO34 61.531 0.705 9.733E-02 3.176E-01 32.472 -0.361 4.552E-01 7.049E-01 [Document text truncated for crawler view.]