Identification of a Novel miR-122-5p/CDC25A Axis and Potential Therapeutic Targets for Chronic Myeloid Leukemia

Academic Editor: Paulina Gil-Kulik Received: 3 October 2025 Revised: 13 November 2025 Accepted: 18 November 2025 Published: 25 November 2025 Citation: Ozer Yaman, S.; Petrovi´c, N.; Yaman, S.; Akidan, O.; Cimbek, A.; Baycelebi, G.; Srdi´c-Raji´c, T.; Šami, A.; Misir, S. Identification of a Novel miR-122-5p/CDC25A Axis and Potential Therapeutic Targets for Chronic Myeloid Leukemia. Int. J. Mol. Sci. 2025,26, 11401. https:// doi.org/10.3390/ijms262311401 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Identification of a Novel miR-122-5p/CDC25A Axis and Potential Therapeutic Targets for Chronic Myeloid Leukemia Serap Ozer Yaman 1, * , Nina Petrovi´c 2,3 , Selcuk Yaman 1 , Osman Akidan 4 , Ahmet Cimbek 5 , Gulsah Baycelebi 5 , Tatjana Srdi´c-Raji´c 3, Ahmad Šami 6,7 and Sema Misir 8,* 1Department of Medical Biochemistry, Trabzon Kanuni Training and Research Hospital, Faculty of Medicine, Trabzon University, 61030 Trabzon, Turkey 2Laboratory for Radiobiology and Molecular Genetics, “VIN ˇ CA” Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, 11000 Belgrade, Serbia 3Department of Experimental Oncology, Institute for Oncology and Radiology of Serbia, 11000 Belgrade, Serbia; [email protected] 4Department of Hematology, Mengücek Gazi Education and Research Hospital, 24100 Erzincan, Turkey 5Department of Internal Medicine, Trabzon Kanuni Training and Research Hospital, Faculty of Medicine, Trabzon University, 61030 Trabzon, Turkey 6 Cellular and Molecular Radiation Oncology Laboratory, Department of Radiation Oncology, Universitaetsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany 7DKFZ-Hector Cancer Institute, University Medicine Mannheim, 68167 Mannheim, Germany 8Department of Biochemistry, Faculty of Pharmacy, Sivas Cumhuriyet University, 58140 Sivas, Turkey *Correspondence: [email protected] (S.O.Y.); [email protected] (S.M.) Abstract Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by uncontrolled proliferation of myeloid cells. MicroRNAs (miRNAs), small noncoding RNAs, regulate post-transcriptional gene expression by degrading target mRNAs or repressing translation. Dysregulated miRNA expression has been implicated in various malignancies, including CML, where they can function as oncogenes or tumor suppressors. This study aimed to investigate the relationship between miR-122-5p and cell division cycle 25A (CDC25A) in CML and to elucidate the regulatory mechanisms of miR-122-5p. This study integrates bioinformatics analysis with in vitro RT-qPCR validation in K562 chronic myeloid leukemia cells to explore the potential regulatory relationship between miR-122-5p and CDC25A. mRNA expression profiles were retrieved from the GSE100026 dataset in the Gene Expression Omnibus (GEO), and differentially expressed genes were identified using GEO2R. Quantitative real-time PCR (RT-qPCR) was performed to measure miR-122-5p, CDC25A, and cyclin-dependent kinase 4 (CDK4) expression levels. Bioinformatics analyses (miRNeT, miRDIP, TargetScan, BioGPS, GeneMANIA, STRING) were applied to predict molecular interactions and functional pathways. Public RNA-seq datasets and in silico tools were used to prioritize candidates; RT-qPCR in a single CML cell line (K562) provided in vitro expression validation. In K562 cells, miR-122-5p expression was significantly reduced, while CDC25A and CDK4 were markedly upregulated. BioinformaticstoolsconfirmedCDC25Aasa potential miR-122-5ptarget. Functionalenrichment indicated CDC25A involvement in cell cycle regulation and apoptosis. These findings suggest that miR-122-5p functions as a tumor suppressor in CML by targeting CDC25A. Modulating the miR-122-5p/CDC25A axis may provide potential molecular targets for inhibiting CML progression through regulation of cell cycle pathways. Findings are exploratory and based on bioinformatics with limited in vitro expression confirmation; functional studies are required to establish causality. Keywords: chronic myeloid leukemia; miR-122-5p; CDC25A; CDK4 Int. J. Mol. Sci. 2025,26, 11401 https://doi.org/10.3390/ijms262311401 Int. J. Mol. Sci. 2025,26, 11401 2 of 20 1. Introduction Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm originating from hematopoietic stem cells [ 1 ]. The genetic hallmark of CML is the presence of the Philadelphia chromosome (Ph) and the formation of a fusion oncogene known as BCR::ABL1 [ 2 ]. The BCR-ABL oncogene plays a role in the development of CML by leading to increased proliferation and inhibition of apoptosis through tyrosine kinase activation [ 3 ]. CML accounts for approximately 15% of leukemias and is most commonly observed between CML accounts for approximately 15% of leukemias and is most commonly observed between the ages of 40 and 60 [ 4 ]. Although tyrosine kinase inhibitors (TKIs, e.g., imatinib mesylate (IM)) have represented a significant advancement in the treatment of the disease, relapse [ 5 ] and TKI resistance remain significant challenges [ 6 ]. Therefore, a better understanding of the molecular pathology of CML and the mechanisms underlying emerging drug resistance is needed. Therefore, a better understanding of the molecular pathology of CML and the mechanisms underlying emerging drug resistance is needed to identify potential molecular target. Recent studies have shown that microRNAs (miRNAs) play a role in CML progression and TKI resistance development based on their significant regulatory functions in cellular homeostasis [ 7 ]. miRNAs are small, noncoding RNA molecules, approximately 22 nucleotides long, critical in regulating gene expression [ 8 ]. They are involved in various biological processes, including development, differentiation, proliferation, and apoptosis. miRNAs exert their effects by binding to complementary sequences in target mRNAs, thereby regulating gene expression post-transcriptionally [ 9 ]. Accumulating evidence suggests that miRNAs play crucial roles in the development of CML. Depending on the regulated target gene, these miRNAs can function as tumor suppressors or oncogenes [ 10 ]. Therefore, identifying miRNAs and their target genes in CML is critical for understanding their roles in tumor formation and progression. Although many studies have explored the role of miRNAs, the biological functions of several miRNAs remain unclear [11]. miR-122 has the potential to act as an oncogene or tumor suppressor by targeting different genes in various cancer types. The aberrant expression of miR-122 has been reported in several cancers, including breast, lung, leukemia, and liver [ 12 ]. However, there is limited data on the expression, functions, and targets of miR-122-5p in CML. Cell division cycle 25 A (CDC25A), a member of the CDC25 family, is a dual-specific protein phosphatase. CDC25A activates cyclin-cyclin-dependent kinase (CDK) complexes, which are critical for the transition between the G1/S and G2/M phases and the DNA damage response. Additionally, CDC25A plays significant roles in apoptosis, cell metabolism, and tumor cell metastasis [ 13 ]. Known for its oncogenic properties, CDC25A has been frequently observed in various cancer types, including lung cancer [ 14 ], breast cancer [ 15 ], and acute myeloid leukemia (AML) [ 16 ], and is closely associated with poor patient prognosis [ 17 ]. In recent years, CDC25A has garnered exceptional interest due to its identified overexpression in various cancer types [ 16 ]. However, the mechanisms underlying CDC25A overexpression remain highly complex, necessitating further research [18]. Although miR-122-5p and CDC25A have been studied in several malignancies such as hepatocellular carcinoma and acute myeloid leukemia, their coordinated regulatory relationship within the molecular context of BCR::ABL1-positive chronic myeloid leukemia has not been previously characterized. This study uniquely integrates bioinformatic prediction with in vitro expression validation to propose a disease-specific miR-122-5p/CDC25A regulatory axis potentially involved in CML pathogenesis. This study aims to determine the expression changes of miR-122-5p and CDC25A in CML, investigate their roles in its development, and explore the potential underlying mechanisms. Additionally, using in silico tools, we examined the potential role of miR-122-5p in regulating CDC25A Int. J. Mol. Sci. 2025,26, 11401 3 of 20 and other CDC25A-associated genes in CML pathogenesis. Therefore, the miR-1225p/CDC25A axis is expected to provide further insights into potential treatments for CML and improve prognosis. 2. Results 2.1. miR-122-5p Was Underexpressed in K562 Cells To investigate the role of miR-122-5p in CML, miR-122-5p expression in CML cells was evaluated by RT-qPCR and compared with normal control cells. The results showed that miR-122-5p expression was significantly lower in K562 cells than in HaCaT cells ( p= 0.0001 ) (Figure 1). Figure 1. Relative miR-122-5p levels in K562 and HaCaT cells. RNU6 was used for the normalization of miRNAs. *** Represents significant data (p= 0.0001), compared to HaCaT cells (n:10). 2.2. CDC25A Is a Direct Target of miR-122-5p miRNAs function primarily through base pairing with sequences complementary to the seed region. To better understand the biological roles of this miR-122-5p in CML, potential target genes were predicted by miRNET and mirDIP databases. The complementary sequences of CDC25A 3 ′ UTR and miR-122-5p were determined by TargetScan (Figure 2A). 2053 and 226 target genes were determined for miR-122-5p in miRNET and mirDIP, respectively (Supplementary S1). One hundred eighteen common genes from both databases were determined and visualized with Cytoscape (version number: 3.10.4) (Figure 2B). We identified genes targeted by miR-122-5p that were common between the varying mRNA profiles in CML and selected CDC25A. 2.3. Expression Level of CDC25A and CDK4 The tissue-specific pattern of mRNA expression can give important clues about gene functions. The changed mRNA profiles between the CML and the control groups are given in Supplementary S2. Among these changed genes is CDC25A, which is also targeted by miR-122-5p. The expression of CDC25A was compared between various cancer cell lines and tissues and normal tissues using BioGPS (Supplementary S3). CDC25A expression level was high in K-562 cells. Analysis of changes in CDC25A and CDK4 gene expression in K562 and HaCaT cells revealed much higher levels of these genes in K-562 cells (Figure 3A). According to correlation analysis, a negative correlation was found between miR-122-5p expression and CDC25A expression, and a positive correlation was found between CDC25A and CDK4 (Figure 3B). Int. J. Mol. Sci. 2025,26, 11401 4 of 20 Figure 2. Targeting relationship between miR-122-5p and CDC25A. (A) The complementary sequences of CDC25A 3 ′ UTR and miR-122-5p were presented by TargetScan. (B) Target genes of miR-122-5p were identified by miRNET (green colored area) and mirDIP (yellow colored area) tools. 118 overlapping genes were identified from mirNET and mirDIP tools. The miR-122-5p-targets visualization network contains 118 identified common targets. CDC25A was one of the overlapping genes in the databases selected for further analysis. Figure 3. (A) CDC25A and CDK4 gene expression by RT-qPCR analysis in K562 and HaCaT cells. All gene expression data are presented as fold change relative to HaCaT cells. GAPDH was used for the normalization of all genes ***: (p= 0.0001, respectively), compared to HACAT cells. (B) Correlation analysis between miR-122-5p-CDC25A (a) and CDC25-CDK4 (b) expression (n:10). Int. J. Mol. Sci. 2025,26, 11401 5 of 20 2.4. CDC25A Expression and Functions in Chronic Myeloproliferative Disorder 2.4.1. Peripheral Blood The PVCA suggested that CDC25A gene expression accounts for 28.4% of gene expression profile variances between the samples, while the type of diagnosed leukemia accounts for 7% of the variance. The residual factors accounted for a 64.6% variance ( Supplementary S4a ). Correlation heatmap for PB cohort indicated that samples in low and high tertiles had a higher correlation in gene expression profile with the samples within the same group and with the samples from medium tertile than between each other within the same gene cluster (Supplementary S4b). The DGE analysis of the PB samples cohort showed the highest number of differentially expressed genes (DEGs) when comparing high and low tertiles (n = 12,614). Comparing the median and low tertiles resulted in n = 7577 differentially expressed genes, while comparing high and medium tertiles resulted in the lowest number of DEGs (n = 2581) (Supplementary S4c). Cluster pathway analysis suggested that samples in the high tertile compared to the samples from low tertile have overrepresented pathways related to the cell-cycle regulation and DNA repair processes while having underrepresented pathways associated with the immune system and signal transductions (Figure 4A), as well as when comparing high vs. median tertiles (Figure 4B) and when comparing median and low tertiles (Figure 4C). These results suggest that the higher the expression of CDC25A is, the more highly upregulated cell-cycle regulation and DNA repair pathways are, and the more downregulated immune system and signal transduction pathways are, on the other hand, which was also shown in Figure 5A–C (Supplementary S6). Reactome pathway enrichment analysis visualized the top 20 upand down-regulated pathways ranked by the normalized enrichment score (NES). Positive NES values (shown in red) indicate pathways upregulated in samples with higher CDC25A expression, whereas negative NES values (shown in blue) indicate downregulated pathways. The intensity of the color represents the magnitude of enrichment, with darker shades denoting stronger NES values. Most significantly enriched pathways were related to cell-cycle control, DNA replication, and checkpoint regulation, consistent with the functional role of CDC25A in proliferation. 2.4.2. Bone Marrow Results from the analysis of the BM samples are overwhelmingly in line with the results described for the PB samples. The PVCA showed that CDC25A gene expression accounts for 35.3% of gene expression profile variances between the samples, while the type of diagnosed leukemia accounts for 13% of the variance. The residual factors accounted for 52.1% of the variance (Supplementary S5a). The same was not observed for bone marrow sample cohort where low, medium and high tertile samples were not separated into different clusters (Supplementary S5b). According to the DGE analysis of bone marrow samples, the highest number of DEGs was detected when median and low tertiles of CDC25A expression were compared (n = 767), followed by 695 differentially expressed genes between high and low tertiles, while high and medium tertiles resulted in the lowest number of DEGs (n = 13) (Supplementary S5c). These results indicate that in bone marrow samples, in a group with relatively high CDC25A expression (high and mid), not many genes and pathways may not be significantly changed, unlike between high and low and mid and low groups. In pathway cluster analysis for bone marrow sample datasets, when we compare high and low tertiles of the CDC25A gene, cell cycle, and DNA repair are most significant, while underrepresented ones are mostly associated with the immune system. When high and mid tertiles were compared, the highest underrepresented pathway was related to the metabolism of proteins, while highly overrepresented pathways were Int. J. Mol. Sci. 2025,26, 11401 6 of 20 associated with the cell cycle. In mid-low comparison, cell cycle and DNA repair pathways were shown to be overrepresented, while immune system and signal transduction pathways were highly underrepresented pathways (Figures 6A–C and 7A–C, Supplementary S6). Figure 4. (A–C). Cluster pathway analysis including the most significant pathways for each comparison—high, medium (mid) and low CDC25A expression level tertiles for peripheral blood datasets. Int. J. Mol. Sci. 2025,26, 11401 7 of 20 Figure 5. (A–C). shows pathway networks, including the most significant pathways for each comparison—high, medium (mid) and low CDC25A expression level tertiles for peripheral blood datasets. Int. J. Mol. Sci. 2025,26, 11401 8 of 20 Figure 6. (A–C) Cluster pathway analysis, including the most significant pathways for each comparison of high, medium (mid), and low CDC25A expression level tertiles for bone marrow datasets. Taking all into account, higher expression CDC25A groups (mid and high, both) show similar patterns in differential gene expression and signaling pathways. Furthermore, PB and BM samples also show similar patterns, indicating that sample type, in this case, may not influence pathway and DEG analysis. Int. J. Mol. Sci. 2025,26, 11401 9 of 20 Figure 7. (A–C) Pathway networks, including the most significant pathways for each comparison of high, medium (mid), and low CDC25A expression level tertiles for bone marrow datasets. Int. J. Mol. Sci. 2025,26, 11401 16 of 20 manufacturer specifications, cDNA was synthesized using (High Capacity) (A.B.T., Cat: C03-01-05, Ankara, Türkiye). Target-specific pre-amplification used diluted cDNA (1:4) with miScript primer (miR-122-5p) and miScript PreAMP PCR Kit (Qiagen, Cat: 331452, Hilden, Germany). U6 snRNA served as the internal control. For RT-qPCR analysis, GAPDH was used as the internal reference for mRNA quantification, and U6 snRNA served as the endogenous control for miRNA analysis. Relative gene expression levels were calculated using the 2 −∆∆Ct method. Each reaction was run in technical triplicates, and mean Ct values were used for statistical analysis. 5 µ L of cDNA template were mixed with SYBER Green Master Mix (Qiagen, Cat: 218073, Hilden, Germany) and with miScript primer assays (Qiagen, Cat: 218300 Hilden, Germany) to make a 20 µ L mixture. This was then added to a custom 96-well miScript miRNA PCR plate that had forward and reverse miRNA-specific primer for miR-122-5p. LightCycler 480 system (Roche, Basel, Switzerland) was used to conduct real-time PCR procedures. The conditions for real-time PCR were as follows: 95 ◦ C for 15 min, succeeded by 40 cycles of 94 ◦ C for 15 s, 55 ◦ C for 30 s, and 70 ◦ C for 34 s, 1 cycle at 95 ◦ C for 1 s, 60 ◦ C for 1 min and 1 cycle (cooling) 95 ◦ C. The cycles needed for the fluorescence signal to exceed the threshold (background noise level) were computed to ascertain the cycle threshold (CT) in real-time PCR. The CT values of SNORD61 were subtracted from the CT values of the target miRNAs to ascertain the ∆ Ct values of the miRNAs. ∆ Ct values are inversely correlated with miRNA expression levels. Consequently, reduced ∆ Ct values correlate with elevated miRNA expression. Each sample was analyzed in triplicate. Using the comparative threshold cycle 2 −∆∆Cq method, miRNA expression levels were calculated after being normalized to the external reference miR-1225p and the internal reference U6 snRNA (U6 snRNA-F-5 ′ -CTCGCTTCGGCAGCACA-3 ′ , U6 snRNA-R-AACGCTTCACGAATTTGCGT-3′), [60]. 4.8. Statistical Analysis Statistical analyses were performed using IBM SPSS Statistics for Windows (version 23.0; IBM Corp., Armonk, NY, USA). The conformity of variables to normal distribution was determined using the Kolmogorov–Smirnov test. Differences in the expression of miR-122-5p, CDC25A, and CDK4 genes between K562 and HaCaT cells were evaluated using the independent samples t-test. In light of the skewness of the data distribution, Pearson correlation analysis was applied to assess the relationships between miR-122-5p and CDC25A genes. In K562 cells, Pearson correlation analysis was evaluated separately between miR-122-5p-CDC25A and CDC25A-CDK4 expression results. Statistical significance was determined as p< 0.05. All experiments were performed in 10 repetitions. 5. Conclusions In this study, we successfully constructed a miRNA-mRNA regulatory network related to CML. Our findings suggest that miR-122-5p may regulate CDC25A expression through complementary base pairing. By reducing the expression of CDC25A, miR-1225p could potentially control the cell cycle and restrict cellular proliferation. Although further experimental and clinical validation is required, these insights could contribute to a deeper understanding of the molecular mechanisms underlying CML and highlight potential therapeutic targets. In conclusion, the current findings should be interpreted as preliminary and correlative. Although miR-122-5p and CDC25A show opposing expression patterns in CML cells, direct mechanistic validation is required. Subsequent studies involving functional modulation of miR-122-5p and CDC25A will be necessary to confirm their causal relationship and biological significance in CML proliferation and survival. This exploratory study identifies a potential inverse association between miR-122-5p and CDC25A expression in chronic myeloid leukemia. These results suggest that miR-122-5p Int. J. Mol. Sci. 2025,26, 11401 17 of 20 may participate in pathways influencing cell-cycle regulation, but further functional and mechanistic validation is required to establish causality. Therefore, the findings should be viewed as hypothesis-generating and form a foundation for future studies exploring miR-122-5p/CDC25A axis dynamics in CML pathogenesis. Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijms262311401/s1. Author Contributions: Study design; S.O.Y., S.M. and N.P. Analysis; N.P., S.O.Y., S.M., O.A., A.C., G.B., A.Š. and T.S.-R. Literature search; S.O.Y., S.M., S.Y. and O.A. Wrote the manuscript; S.M., N.P. and S.O.Y. Edit the manuscript; N.P., S.O.Y., O.A., G.B., A.C., S.Y. and S.M. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external Funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data supporting this study’s findings are available on request from the corresponding author. Acknowledgments: The CML sequencing dataset was shared by The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, for which the authors are grateful. Conflicts of Interest: The authors declare no conflicts of interest. Abbreviations The following abbreviations are used in this manuscript: AML Acute myeloid leukemia CDC25A Cell division cycle 25A CML Chronic myeloid leukemia CDK cyclin-cyclin-dependent kinase CDK4 Cyclin-dependent kinase 4 CT Cycle threshold DGE Differential gene expression DMEM Dulbecco’s Modified Eagle Medium FBS Fetal bovine serum GEO Gene Expression Omnibus HaCaT Human keratinocyte cells IM Imatinib mesylate miRNAs MicroRNAs Ph Philadelphia chromosome PVCA Principal Variance Component Analysis RT-qPCR Quantitative real-time PCR STRING Search Tool for the Retrieval of Interacting Gene TKI tyrosine kinase inhibitors References 1. Yang, Y.; Zhong, F.; Jiang, J.; Li, M.; Yao, F.; Liu, J.; Cheng, Y.; Xu, S.; Chen, S.; Zhang, H.; et al. Bioinformatic analysis of the expression profile and identification of RhoGDI2 as a biomarker in imatinib-resistant K562 cells. Hematology 2023,28, 2244856. [CrossRef] [PubMed] 2. 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