Machine Learning Discoveries of METTL3-X Synergy in ETC-1922159 Treated Colorectal Cancer Cells

Machine learning discoveries of METTL3-X synergy in ETC-1922159 treated colorectal cancer cells shriprakash sinha Independent Researcher; Orcid ID : orcid.org/0000-0001-7027-5788 104-Madhurisha Heights Phase 1, Risali, Bhilai-490006, India Abstract Methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit (METTL3) is the most studied member of the METTL protein family and is located on the human chromosome 14q11.2. METTL3 belong to a sub-family of seven-beta-strand (7BS) methyltransferases which the function by the most prevalent and reversible internal methylation (i.e m6A modification) of their substrates like mRNA, tRNA, primRNA, lncRNA, snRNA, rRNA, miRNA. It has been found to be in elevated levels in various cancer types. In colorectal cancer (CRC) cells treated with ETC-1922159, METTL3 was found to be down regulated along with other genes. A recently developed search engine ranked combinations of METTL3-X (X, a particular gene/protein) at 2nd order level after drug administration. Some of these combinations have been tested in wet lab, however many have been pointed out by the search engine that are yet to be explored/tested. These rankings reveal which METTL3-X combinations might be working synergistically in CRC. In this research work, I cover combinations of METTL3 with members of NIMA (never in mitosis gene a)-related kinase (NEK), v-myc avian myelocytomatosis viral oncogene homolog (MYC), EpsteinBarr nuclear antigen (EBNA), enhancer of zeste homolog 2 (EHZ2), autophagy related (ATG), chromobox homolog (CBX), DEAD-box helicase (DDX), DNA methyltransferase (DNMT), E2F transcription factor (E2F), EpsteinBarr virus nuclear antigen (EBNA), F-box protein (FBX), high mobility group (HMG), heterogeneous nuclear ribonucleoprotein (HNRNP), homeobox (HOX), integrin subunits (ITG), interleukin (IL), kinesin family member (KIF), long intergenic non-protein coding RNA (LINC), poly(ADP-ribose) polymerase (PARP), RNA binding motif protein (RBM), solute carrier family 7 member (SLC7), small nucleolar RNA host gene (SNHG), transcription factor (TCF), transforming growth factor beta (TGFB), tripartite motif containing (TRIM), ubiquitin conjugating enzyme E2 (UBE2), ubiquitin specific peptidase (USP), zinc finger and BTB domain containing (ZBTB) and zinc finger protein (ZNF) family. IML dicoveries of METTL3-X synergy in ETC-1922159 treated CRC cells Email address: [email protected] (shriprakash sinha) 1Aspects of unpublished work were presented in a poster session at the first Wnt Gordon Research Conference, from 6-11 August 2017, held in Stowe, VT 05672, USA. Preprint submitted to Preprint February 7, 2025 Keywords: METTL3, Porcupine inhibitor ETC-1922159, Sensitivity analysis, Machine learning, Colorectal cancer. 1. Introduction 1.1. METTL3 Modified nucleosides are present in mRNA of all eukaryotes, though at much lower levels than in other RNA moieties such as rRNA, tRNA, and snRNA. Modification by methylation occurs on the terminal guanosine of the cap (N7-methylguanosine), and the first two encoded nucleosides (2’-O-methylnuculeosides) in most higher eukaryotes. Modification by methylation also occurs at internal adenosine residues in many species (N6-methyladenosine). Modification by deamination occurs at specific adenosine and cytidine residues in very specific cases leading to post-transcriptional editing. Studies have shown the importance of the cap N7-methylguanosine however the role of the 2’-O-methylnucleosides is not as well understood. In their review, Bokar [1] focused on the role of internal N6-methyladenosine residues. The formation of N6methyladenosine is catalyzed by a complex enzyme containing a subunit (MT-A70) that co-localizes with nuclear speckles and appears to be widely expressed in all higher eukaryotes. Jia et al. [2] indicate that the discovery of at least two m6A demethylases FTO (Jia et al. [3]) and ALKBH5 (Zheng et al. [4]) proteins, point that this modification is reversible and regulated, thus playing a role biological regulation. Methyltransferase-like (METTL) family of proteins play critical roles in this RNA modification, thus methylating various types of RNAs. They consist of a unique 7BS domain, which binds to the methyl donor SAM to catalyze methyl transfer. In a recent review, Qi et al. [5] provide a detailed survey of the METTL family including expression of METTLs in human cancer, their mechanisms of up/down regulation in cancer, their roles in proliferation, invasion, metastasis, reprogramming of tumor cell metabolism, tumor immune response, tumor chemotherapy, their diagnostic value and prognosis evaluation in cancer and the recent developments of molecular inhibitors of METTLs. Liu et al. [6] discovered methyltransferse METTL14 that forms a stable heterodimer with METTL3 that performs m6A deposition/modification on nuclear RNA inside mammalian cells. Further, WTAP interacts with the METTL3-14 complex to affect the cellular m6A deposition. They provide a schematic illustration for the reversible methylation of N6-adenosine in RNA through METTL3-14 complex and the m6A RNA demethylases. Zeng et al. [7] summarize current understanding regarding the oncogenic and tumorsuppressive functions of METTL3, as well as the underlying molecular mechanisms. They also discuss the protein structure of the METTL3-14 heterodimer that provides the basis for potential therapeutic targeting. In a later review Jin et al. [8], discuss factors that regulate METTL3 expression and explores the specific mechanisms by which METTL3 affects multiple tumor biological behaviors, with the aim to provide fundamental support for tumor diagnosis and treatment and offer new ideas for the development of tumor-targeting drugs. 2 In an observational study, Li et al. [9] showed that METTL3 expression level was significantly upregulated in CRC tissues, and its high expression was closely related to a variety of adverse clinico-pathological features of CRC. In CRC cells treated with ETC-1922159, METTL3 was found to be down regulated along with other genes. Some combinations of METTL3 have been confirmed in wet lab, however, many of the combinations have not been explored/tested or are known. To reveal these combinations, I use a modification of a recently published machine learning based search engine, details of which are given in the next section. 1.2. Combinatorial search problem and a possible solution In a recently published work Sinha [10], a frame work of a search engine was developed which can rank combinations of factors (genes/proteins) in a signaling pathway. Readers are requested to go through the adaptation of the above mentioned work for gaining deeper insight into the working of the pipeline and its use of published data set generated after administration of ETC-1922159, Sinha [11]. The work uses SVM package by Joachims [12] in https://www.cs.cornell.edu/people/tj/svm_light/ svm_rank.html. I use the adaptation to rank 2nd order gene combinations. 2. Results & Discussion 2.1. METTL3 related synergies 2.1.1. METTL3 - NEK / MYC / EBNA / EZH2 In cervical cancer (CC), Guo et al. [13] observed upregulation of METTL3 and identified NEK2 as a target of METTL3 in CC cells. Their analysis showed that METTL3 regulated NEK2 expression through m6A modification and mediated the malignant phenotype of CC cells. Similarly, Ma et al. [14] showed that knockdown of METTL3 reduced CC cell proliferation and regulated expression of MYC by identifying m6Amodified MYC. EpsteinBarr virus (EBV) infects a human B lymphocyte and Zheng et al. [15] found that EBV EBNA2 was highly m6A-modified upon EBV infection. Knockdown of METTL3 decreased EBNA2 expression levels, thus showing mechnistic connection between METTL3 and EBNA2. In lung cancer tissues, Chen et al. [16] found that METTL3 and EZH2 levels were upregulated. Their levels, as well as cell proliferative and metastatic abilities, were dose-dependently inhibited in Simvastatininduced A549 cells. They observed that METTL3 positively regulated EZH2 level, and m6A modification on its mRNA. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these inidividual members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these individual members along with METTL3. Table 1 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 2 generated from analysis of the ranks in table 1. The table 1 shows rankings of these individual members w.r.t METTL3. NEK2 - METTL3 shows low ranking of 171 (linear) and 202 (rbf). MYC - METTL3 shows low ranking 3 of 823 (linear) and 1469 (rbf). EBNA1BP2 - METTL3 shows low ranking of 715 (laplace) and 1260 (rbf). EZH2 - METTL3 shows low ranking of 1339 (laplace), 1374 (linear) and 1094 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. RANKING INDIVIDUAL MEMBERS VS METTL3 RANKING OF INDIVIDUAL MEMBERS W.R.TMETTL3 laplace linear rbf NEK2 - METTL3 2171 171 202 MYC - METTL3 2651 823 1469 EBNA1BP2 - METTL3 715 2155 1260 EZH2 - METTL3 1339 1374 1094 Table 1: 2nd order interaction ranking between METTL3 VS Individual members. One can also interpret the results of the table 1 graphically, with the following influences - •individual members w.r.t METTL3 with METTL3 −>NEK2 / MYC / EBNA1BP2 / EZH2. UNEXPLORED COMBINATORIAL HYPOTHESES Individual members w.r.t METTL3 NEK2 METTL3 MYC METTL3 EBNA1BP2 METTL3 EZH2 METTL3 Table 2: 2nd order combinatorial hypotheses between METTL3 and individual members. 2.1.2. METTL3 - ATG Ischemia/reperfusion (I/R) injury is a severe brain disorder and Yu et al. [17] utilized a middle cerebral artery occlusion (MCAO) rat model and SH-SY5Y cells subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) to assess m6A levels and investigate the impact of METTL3 overexpression on long non-coding RNA (lncRNA) CRNDE expression. METTL3 overexpression inhibited lncRNA CRNDE expression which mitigated OGD/R-induced apoptosis and inflammation in SH-SY5Y cells, while 4 enhancing autophagy and stabilizing ATG10 mRNA. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these ATG members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these ATG members along with METTL3. Table 3 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 4 generated from analysis of the ranks in table 3. The table 3 shows rankings of ATG members w.r.t METTL3. ATG3 - METTL3 shows low ranking of 172 (laplace) and 1065 (rbf). ATG10 - METTL3 shows low ranking of 381 (laplace), 1491 (linear) and 726 (rbf). ATG4C - METTL3 shows low ranking of 404 (laplace), 268 (linear) and 304 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. RANKING ATG MEMBERS VS METTL3 RANKING OF ATG MEMBERS W.R.TMETTL3 laplace linear rbf ATG3 - METTL3 172 2205 1065 ATG10 - METTL3 381 1491 726 ATG4C - METTL3 404 268 304 Table 3: 2nd order interaction ranking between METTL3 VS ATG members. One can also interpret the results of the table 3 graphically, with the following influences - •ATG members w.r.t METTL3 with METTL3 −>ATG-3/10/4C. UNEXPLORED COMBINATORIAL HYPOTHESES ATG members w.r.t METTL3 ATG-3/10/4C METTL3 Table 4: 2nd order combinatorial hypotheses between METTL3 and ATG members. 2.1.3. METTL3 - CBX In osteosarcoma metastasis, Huo et al. [18] found that METTL3 binds to the mRNA of regulatory protein CBX4 and regulates the mRNA and protein expression of CBX4. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, 5 these CBX members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these CBX members along with METTL3. Table 5 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 6 generated from analysis of the ranks in table 5. The table 5 shows rankings of CBX members w.r.t METTL3. CBX3 - METTL3 shows low ranking of 887 (laplace) and 782 (rbf). CBX5 - METTL3 shows low ranking of 1542 (laplace), 1138 (linear) and 221 (rbf). CBX2 - METTL3 shows low ranking of 145 (linear) and 42 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, CBX1 showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING CBX MEMBERS VS METTL3 RANKING OF CBX MEMBERS W.R.TMETTL3 laplace linear rbf CBX3 - METTL3 887 1797 782 CBX5 - METTL3 1542 1138 221 CBX1 - METTL3 1952 1344 2325 CBX2 - METTL3 2097 145 42 Table 5: 2nd order interaction ranking between METTL3 VS CBX members. One can also interpret the results of the table 5 graphically, with the following influences - •CBX members w.r.t METTL3 with METTL3 −>CBX-3/5/2. UNEXPLORED COMBINATORIAL HYPOTHESES CBX members w.r.t METTL3 CBX-3/5/2 METTL3 Table 6: 2nd order combinatorial hypotheses between METTL3 and CBX members. 2.1.4. METTL3 - DDX Zhao et al. [19] found that human DDX5 promotes replication of influenza virus in A549 cells. Mechanistically, DDX5 was found to downregulate the antiviral transcripts via the METTL3-METTL14/YTHDF2 axis. These experimental studies confirm the 6 existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these DDX members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these DDX members along with METTL3. Table 7 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 8 generated from analysis of the ranks in table 7. The table 7 shows rankings of DDX members w.r.t METTL3. DDX31 - METTL3 shows low ranking of 195 (laplace), 1247 (linear) and 289 (rbf). DDX21 - METTL3 shows low ranking of 326 (laplace) and 1296 (rbf). DDX55 - METTL3 shows low ranking of 1032 (laplace), 882 (linear) and 614 (rbf). DDX46 - METTL3 shows low ranking of 1119 (laplace), 460 (linear) and 566 (rbf). DDX56 - METTL3 shows low ranking of 1157 (laplace), 875 (linear) and 867 (rbf). DDX11 - METTL3 shows low ranking of 1203 (laplace), 765 (linear) and 396 (rbf). DDX20 - METTL3 shows low ranking of 1250 (laplace), 1039 (linear) and 1159 (rbf). DDX51 - METTL3 shows low ranking of 1390 (laplace), 1516 (linear) and 1146 (rbf). DDX12P - METTL3 shows low ranking of 242 (linear) and 140 (rbf). DDX27 - METTL3 shows low ranking of 1254 (linear) and 467 (rbf). DDX10 - METTL3 shows low ranking of 641 (linear) and 762 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, DDX28, DDX19A, DDX18 and DDX54 showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING DDX MEMBERS VS METTL3 RANKING OF DDX MEMBERS W.R.TMETTL3 laplace linear rbf laplace linear rbf DDX31 - METTL3 195 1247 289 DDX21 - METTL3 326 2516 1296 DDX28 - METTL3 632 1683 2002 DDX19A - METTL3 880 1648 1921 DDX55 - METTL3 1032 882 614 DDX46 - METTL3 1119 460 566 DDX56 - METTL3 1157 875 867 DDX11 - METTL3 1203 765 396 DDX20 - METTL3 1250 1039 1159 DDX51 - METTL3 1390 1516 1146 DDX18 - METTL3 1862 1512 2477 DDX12P - METTL3 2156 242 140 DDX27 - METTL3 2450 1254 467 DDX10 - METTL3 2585 641 762 DDX54 - METTL3 2733 1951 713 Table 7: 2nd order interaction ranking between METTL3 VS DDX members. One can also interpret the results of the table 7 graphically, with the following influences - •DDX members w.r.t METTL3 with METTL3 −>DDX-31/21/55/46/56/11/20/51/12P/27/10. UNEXPLORED COMBINATORIAL HYPOTHESES DDX members w.r.t METTL3 DDX-31/21/55/46/56/11/20/51/12P/27/10 METTL3 Table 8: 2nd order combinatorial hypotheses between METTL3 and DDX members. 7 2.1.5. METTL3 - DNMT Tang et al. [20] revealed that m6A modification of IGFBP7-OT promoted osteoarthritis (OA) progression by regulating the DNMT1/DNMT3A-IGFBP7 axis. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these DNMT members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these DNMT members along with METTL3. Table 9 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 10 generated from analysis of the ranks in table 9. The table 9 shows rankings of DNMT members w.r.t METTL3. DNMT3A - METTL3 shows low ranking of 1198 (laplace), 863 (linear) and 757 (rbf). DNMT1 - METTL3 shows low ranking of 621 (linear) and 412 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, DNMT3B showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING DNMT MEMBERS VS METTL3 RANKING OF DNMT MEMBERS W.R.TMETTL3 laplace linear rbf DNMT3A - METTL3 1198 863 757 DNMT3B - METTL3 2244 2031 2622 DNMT1 - METTL3 2504 621 412 Table 9: 2nd order interaction ranking between METTL3 VS DNMT members. One can also interpret the results of the table 9 graphically, with the following influences - •DNMT members w.r.t METTL3 with METTL3 −>DNMT-3A/1. UNEXPLORED COMBINATORIAL HYPOTHESES DNMT members w.r.t METTL3 DNMT-3A/1 METTL3 Table 10: 2nd order combinatorial hypotheses between METTL3 and DNMT members. 8 2.1.6. METTL3 - E2F Tang et al. [21] found that METTL3 was highly expressed in pancreatic cancer and E2F5 was found to be positively regulated by METTL3. Downregulation of METTL3 restrained the viability, migration and invasion of pancreatic cancer cells and silencing METTL3 resulted in the decreased stability of E2F5 by methylating E2F5. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these E2F members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these E2F members along with METTL3. Table 11 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 12 generated from analysis of the ranks in table 11. The table 11 shows rankings of E2F members w.r.t METTL3. E2F8 - METTL3 shows low ranking of 1147 (laplace), 280 (linear) and 677(rbf). E2F5 - METTL3 shows low ranking of 1438 (laplace) and 1309 (rbf). E2F7 - METTL3 shows low ranking of 603 (linear) and 600 (rbf). E2F1 - METTL3 shows low ranking of 551 (linear) and 577 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, E2F2 showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING E2F MEMBERS VS METTL3 RANKING OF E2F MEMBERS W.R.TMETTL3 laplace linear rbf E2F8 - METTL3 1147 280 677 E2F5 - METTL3 1438 1850 1309 E2F2 - METTL3 1455 2415 2052 E2F7 - METTL3 2183 603 600 E2F1 - METTL3 2564 551 577 Table 11: 2nd order interaction ranking between METTL3 VS E2F members. One can also interpret the results of the table 11 graphically, with the following influences - •E2F members w.r.t METTL3 with METTL3 −>E2F-8/5/7/1. 2.1.7. METTL3 -FBX In pancreatic cancer (PC) patients, Chen et al. [22] found that FBXO31 was overexpressed, leading to promotion of tumor growth. Mechanistically, SIRT2 was a target of 9 RANKING IL MEMBERS VS METTL3 RANKING OF IL MEMBERS W.R.TMETTL3 laplace linear rbf IL17RD - METTL3 407 1569 1307 IL17D - METTL3 645 445 183 IL1RL2 - METTL3 1602 1808 2197 IL17RB - METTL3 1852 1183 269 Table 21: 2nd order interaction ranking between METTL3 VS IL members. UNEXPLORED COMBINATORIAL HYPOTHESES IL members w.r.t METTL3 IL-17RD/17D/17RB METTL3 Table 22: 2nd order combinatorial hypotheses between METTL3 and IL members. 1922159, these KIF members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these KIF members along with METTL3. Table 23 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 24 generated from analysis of the ranks in table 23. The table 23 shows rankings of KIF members w.r.t METTL3. KIF9 - METTL3 shows low ranking of 1302 (laplace), 1111 (linear) and 98 (rbf). KIF22 - METTL3 shows low ranking of 1465 (laplace), 415 (linear) and 188 (rbf). KIF14 - METTL3 shows low ranking of 94 (linear) and 149 (rbf). KIF18B - METTL3 shows low ranking of 213 (linear) and 476 (rbf). KIF20B - METTL3 shows low ranking of 275 (linear) and 339 (rbf). KIF13A - METTL3 shows low ranking of 1142 (linear) and1256 (rbf). KIF20A - METTL3 shows low ranking of 65 (linear) and 159 (rbf). KIFC1 - METTL3 shows low ranking of 292 (linear) and 89 (rbf). KIF2C - METTL3 shows low ranking of 114 (linear) and 135 (rbf). KIF4A - METTL3 shows low ranking of 111 (linear) and 454 (rbf). KIF15 - METTL3 shows low ranking of 37 (linear) and 44 (rbf). KIF23 - METTL3 shows low ranking of 3 (linear) and 333 (rbf). KIF18A - METTL3 shows low ranking of 265 (linear) and 83 (rbf). KIF11 - METTL3 shows low ranking of 60 (linear) and 139 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, KIF27 and KIF7 showed high ranking and might not be synergistically working with METTL3, before treatment. 16 RANKING KIF MEMBERS VS METTL3 RANKING OF KIF MEMBERS W.R.TMETTL3 laplace linear rbf laplace linear rbf KIF27 - METTL3 654 2020 1642 KIF7 - METTL3 856 2648 2518 KIF9 - METTL3 1302 1111 98 KIF22 - METTL3 1465 415 188 KIF14 - METTL3 1671 94 149 KIF18B - METTL3 1737 213 476 KIF20B - METTL3 1859 275 339 KIF13A - METTL3 1873 1142 1256 KIF20A - METTL3 1956 65 159 KIFC1 - METTL3 1970 292 89 KIF2C - METTL3 2025 114 135 KIF4A - METTL3 2371 111 454 KIF15 - METTL3 2410 37 44 KIF23 - METTL3 2492 3 333 KIF18A - METTL3 2573 265 83 KIF11 - METTL3 2677 60 139 Table 23: 2nd order interaction ranking between METTL3 VS KIF members. One can also interpret the results of the table 23 graphically, with the following influences - •KIF members w.r.t METTL3 with METTL3 −>KIF-9/22/14/18B/20B/13A/20A/C1/2C/4A/15/23/18A/11. UNEXPLORED COMBINATORIAL HYPOTHESES KIF members w.r.t METTL3 KIF-9/22/14/18B/20B/13A/20A ... /C1/2C/4A/15/23/18A/11 METTL3 Table 24: 2nd order combinatorial hypotheses between METTL3 and KIF members. 2.1.13. METTL3 - LINC Yan et al. [28] found that LINC00475 was overexpressed in gliomas. Mechanistically, METTL3 induced the generation of LINC00475-S by splicing LINC00475 through m6A modification and subsequently promotes mitochondrial fission in glioma cells by inhibiting the expression of MIF. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these LINC members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these LINC members along with METTL3. Table 25 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 26 generated from analysis of the ranks in table 25. The table 25 shows rankings of LINC members w.r.t METTL3. LINC00261 - METTL3 shows low ranking of 204 (linear) and 117 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, LINC01106, LINC00338, LINC00888, LINC00858, LINC00242 and LINC01123 showed high ranking and might not be synergistically working with METTL3, before 17 treatment. RANKING LINC MEMBERS VS METTL3 RANKING OF LINC MEMBERS W.R.TMETTL3 laplace linear rbf LINC01106 - METTL3 377 2443 2200 LINC00338 - METTL3 1435 1810 1923 LINC00888 - METTL3 1526 2639 2637 LINC00261 - METTL3 2048 204 117 LINC00858 - METTL3 2052 2730 2313 LINC00242 - METTL3 2227 2064 2732 LINC01123 - METTL3 2422 1978 2054 Table 25: 2nd order interaction ranking between METTL3 VS LINC members. One can also interpret the results of the table 25 graphically, with the following influences - •LINC members w.r.t METTL3 with METTL3 −>LINC00261. UNEXPLORED COMBINATORIAL HYPOTHESES LINC members w.r.t METTL3 LINC-00261 METTL3 Table 26: 2nd order combinatorial hypotheses between METTL3 and LINC members. 2.1.14. METTL3 - PARP Chromatin remodeling and m6A modification are two layers that control gene expression and DNA damage signaling in most eukaryotic bio-processes. Sun et al. [29] report that PARP1 controls the chromatin accessibility of METTL3 to regulate its transcription and subsequent m6A methylation of poly(A)+RNA in response to DNA damage induced by radiation. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these PARP members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these PARP members along with METTL3. 18 Table 27 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 28 generated from analysis of the ranks in table 27. The table 27 shows rankings of PARP members w.r.t METTL3. PARP16 - METTL3 shows low ranking of 533 (laplace) and 1018 (rbf). PARP1 - METTL3 shows low ranking of 1415 (laplace), 431 (linear) and 288 (rbf). PARP2 - METTL3 shows low ranking of 1092 (linear) and 806 (rbf). PARPBP - METTL3 shows low ranking of 131 (linear) and 120 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. RANKING PARP MEMBERS VS METTL3 RANKING OF PARP MEMBERS W.R.TMETTL3 laplace linear rbf PARP16 - METTL3 533 2371 1018 PARP1 - METTL3 1415 431 288 PARP2 - METTL3 2165 1092 806 PARPBP - METTL3 2426 131 120 Table 27: 2nd order interaction ranking between METTL3 VS PARP members. One can also interpret the results of the table 27 graphically, with the following influences - •PARP members w.r.t METTL3 with METTL3 −>PARP-16/1/2/BP. UNEXPLORED COMBINATORIAL HYPOTHESES PARP members w.r.t METTL3 PARP-16/1/2/BP METTL3 Table 28: 2nd order combinatorial hypotheses between METTL3 and PARP members. 2.1.15. METTL3 - RBM X chromosome inactivation in mammals is regulated by the non-coding (nc) RNA, XIST, which represses the chromosome from which it is transcribed. High levels of m6A RNA modification occur within XIST exon I, and in XIST exon VII. This m6A modification is catalysed by the METTL-3/14 complex that is directed to specific targets, by RBM-15/15B. m6A modification of XIST RNA has been reported to be important for XISTmediated gene silencing. Coker et al. [30] show that in mouse embryonic stem cells (mESCs), RBM15 interacts with the m6A complex, the SETD1B histone 19 modifying complex, and several proteins linked to RNA metabolism. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these RBM members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these RBM members along with METTL3. Table 29 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 30 generated from analysis of the ranks in table 29. The table 29 shows rankings of RBM members w.r.t METTL3. RBM28 - METTL3 shows low ranking of 201 (laplace), 857 (linear) and 1247 (rbf). RBMX - METTL3 shows low ranking of 562 (laplace), 688 (linear) and 633 (rbf). RBM26 - METTL3 shows low ranking of 1251 (laplace), 1060 (linear) and 1080 (rbf). RBM19 - METTL3 shows low ranking of 1349 (laplace), 736 (linear) and 862 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. RANKING RBM MEMBERS VS METTL3 RANKING OF RBM MEMBERS W.R.TMETTL3 laplace linear rbf RBM28 - METTL3 201 857 1247 RBMX - METTL3 562 688 633 RBM26 - METTL3 1251 1060 1080 RBM19 - METTL3 1349 736 862 Table 29: 2nd order interaction ranking between METTL3 VS RBM members. One can also interpret the results of the table 29 graphically, with the following influences - •RBM members w.r.t METTL3 with METTL3 −>RBM-28/X/26/19. UNEXPLORED COMBINATORIAL HYPOTHESES RBM members w.r.t METTL3 RBM-28/X/26/19 METTL3 Table 30: 2nd order combinatorial hypotheses between METTL3 and RBM members. 2.1.16. METTL3 - SLC7 Xu et al. [31] showed that the m6A and METTL3 were both elevated in lung adenocar20 cinoma (LUAD) patients and lung cancer cells. They found that METTL3 could lead to proliferation and inhibit ferroptosis in different LUAD cell models, while METTL3 knockdown suppressed LUAD growth. Further, SLC7A11 (the subunit of system Xc−), was identified as the direct target of METTL3 by mRNA-seq and MeRIP-seq. METTL3-mediated m6A modification stabilized SLC7A11 mRNA and promote its translation, thus promoting LUAD cell proliferation and inhibiting cell ferroptosis. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these SLC7 members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these SLC7 members along with METTL3. Table 31 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 32 generated from analysis of the ranks in table 31. The table 31 shows rankings of SLC7 members w.r.t METTL3. SLC7A8 - METTL3 shows low ranking of 1357 (linear) and 1014 (rbf). SLC7A2 - METTL3 shows low ranking of 138 (linear) and 318 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. RANKING SLC7 MEMBERS VS METTL3 RANKING OF SLC7 MEMBERS W.R.TMETTL3 laplace linear rbf SLC7A8 - METTL3 2400 1357 1014 SLC7A2 - METTL3 2217 138 318 Table 31: 2nd order interaction ranking between METTL3 VS SLC7 members. One can also interpret the results of the table 31 graphically, with the following influences - •SLC7 members w.r.t METTL3 with METTL3 −>SLC7-A8/A2. UNEXPLORED COMBINATORIAL HYPOTHESES SLC7 members w.r.t METTL3 SLC7-A8/A2 METTL3 Table 32: 2nd order combinatorial hypotheses between METTL3 and SLC7 members. 2.1.17. METTL3 - SNHG Jian et al. [32] demonstrated that in MNNG-induced gastric cancer (GC) tumorigenesis, METTL3 facilitated cellular epithelial-mesenchymal transition and biological 21 functions through the m6A modification of downstream target SNHG7. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these SNHG members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these SNHG members along with METTL3. Table 33 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 34 generated from analysis of the ranks in table 33. The table 33 shows rankings of SNHG members w.r.t METTL3. SNHG6 - METTL3 shows low ranking of 585 (laplace), 876 (linear) and 834 (rbf). SNHG5 - METTL3 shows low ranking of 665 (laplace), 665 (linear) and 471 (rbf). SNHG18 - METTL3 shows low ranking of 781 (laplace) and 1237 (linear). SNHG16 - METTL3 shows low ranking of 821 (laplace), 762 (linear) and 610 (rbf). SNHG10 - METTL3 shows low ranking of 1024 (laplace), 880 (linear) and 635 (rbf). SNHG15 - METTL3 shows low ranking of 1605 (laplace), 1091 (linear) and 822 (rbf). SNHG1 - METTL3 shows low ranking of 1185 (linear) and 1154 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, SNHG17, SNHG7, SNHG8 and SNHG3 showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING SNHG MEMBERS VS METTL3 RANKING OF SNHG MEMBERS W.R.TMETTL3 laplace linear rbf SNHG17 - METTL3 146 1722 1972 SNHG7 - METTL3 149 1950 1695 SNHG6 - METTL3 585 876 834 SNHG5 - METTL3 665 665 471 SNHG18 - METTL3 781 1237 1632 SNHG16 - METTL3 821 762 610 SNHG8 - METTL3 862 1642 1564 SNHG10 - METTL3 1024 880 635 SNHG3 - METTL3 1591 1630 769 SNHG15 - METTL3 1605 1091 822 SNHG1 - METTL3 2493 1185 1154 Table 33: 2nd order interaction ranking between METTL3 VS SNHG members. 22 One can also interpret the results of the table 33 graphically, with the following influences - •SNHG members w.r.t METTL3 with METTL3 −>SNHG-6/5/18/16/10/15/1. UNEXPLORED COMBINATORIAL HYPOTHESES SNHG members w.r.t METTL3 SNHG-6/5/18/16/10/15/1 METTL3 Table 34: 2nd order combinatorial hypotheses between METTL3 and SNHG members. 2.1.18. METTL3 - TCF Wang et al. [33] show that upregulated METTL3 promotes the progression of thyroid carcinoma through m6A methylation on TCF1 mRNA. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these TCF members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these TCF members along with METTL3. Table 35 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 36 generated from analysis of the ranks in table 35. The table 35 shows rankings of TCF members w.r.t METTL3. TCF3 - METTL3 shows low ranking of 116 (laplace), 1430 (linear) and 1056 (rbf). TCF19 - METTL3 shows low ranking of 722 (laplace) and 1207 (linear) TCF7 - METTL3 shows low ranking of 1500 (laplace) and 529 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, TCFL5 showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING TCF MEMBERS VS METTL3 RANKING OF TCF MEMBERS W.R.TMETTL3 laplace linear rbf TCF3 - METTL3 116 1430 1056 TCF19 - METTL3 722 1207 1875 TCF7 - METTL3 1500 1621 529 TCFL5 - METTL3 2132 1744 2008 Table 35: 2nd order interaction ranking between METTL3 VS TCF members. 23 One can also interpret the results of the table 35 graphically, with the following influences - •TCF members w.r.t METTL3 with METTL3 −>TCF-6/5/18/16/10/15/1. UNEXPLORED COMBINATORIAL HYPOTHESES TCF members w.r.t METTL3 TCF-6/5/18/16/10/15/1 METTL3 Table 36: 2nd order combinatorial hypotheses between METTL3 and TCF members. 2.1.19. METTL3 - TGFB In gastric cancer (GC), Yuan et al. [34] found that METTL3 could combine with pSMAD3 to regulate the transcription of downstream target genes. TGF-β/B)/SMAD signaling is a complex regulatory network that both inhibits and promotes tumorigenesis. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these TGFB members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these TGFB members along with METTL3. Table 37 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 38 generated from analysis of the ranks in table 37. The table 37 shows rankings of TGFB members w.r.t METTL3. TGFB1 - METTL3 shows low ranking of 349 (laplace), 461 (linear) and 1126 (rbf). TGFBRAP1 - METTL3 shows low ranking of 318 (linear) and 689 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, TGFBR3 showed high ranking and might not be synergistically working with METTL3, before treatment. RANKING TGFB MEMBERS VS METTL3 RANKING OF TGFB MEMBERS W.R.TMETTL3 laplace linear rbf TGFB1 - METTL3 349 461 1126 TGFBR3 - METTL3 913 2169 2414 TGFBRAP1 - METTL3 2336 318 689 Table 37: 2nd order interaction ranking between METTL3 VS TGFB members. 24 One can also interpret the results of the table 37 graphically, with the following influences - •TGFB members w.r.t METTL3 with METTL3 −>TGFB-1/RAP1. UNEXPLORED COMBINATORIAL HYPOTHESES TGFB members w.r.t METTL3 TGFB-1/RAP1 METTL3 Table 38: 2nd order combinatorial hypotheses between METTL3 and TGFB members. 2.1.20. METTL3 - TRIM In osteosarcoma tissues, Zhou et al. [35] found TRIM7 expression to be upregulated which led to osteosarcoma cell migration and invasion through ubiquitination of breast cancer metastasis suppressor 1 (BRMS1). They also observed loss of TRIM7 m6A modification and reported that METTL3 and YTHDF2 were the main factors involved in the aberrant m6A modification of TRIM7. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. In colorectal cancer cells treated with ETC-1922159, these TRIM members, and METTL3, were found to be down regulated and their regulation was recorded independently. I was able to rank 2nd order combination of these TRIM members along with METTL3. Table 39 shows rankings of these combinations. Followed by this is the unexplored combinatorial hypotheses in table 40 generated from analysis of the ranks in table 39. The table 39 shows rankings of TRIM members w.r.t METTL3. TRIM7 - METTL3 shows low ranking of 108 (laplace), 1100 (linear) and 1128 (rbf). TRIM65 - METTL3 shows low ranking of 235 (laplace) and 853 (linear). TRIM32 - METTL3 shows low ranking of 346 (laplace), 1428 (linear) and 952 (rbf). TRIM59 - METTL3 shows low ranking of 549 (laplace), 897 (linear) and 528 (rbf). These rankings point to the synergy existing between the two components, which have been down regulated after the drug treatment. Further, TRIM28 showed high ranking and might not be synergistically working with METTL3, before treatment. One can also interpret the results of the table 39 graphically, with the following influences - •TRIM members w.r.t METTL3 with METTL3 −>TRIM-7/65/32/59. 2.1.21. METTL3 - UBE2 In human pan-cancer analysis, Jiang et al. [36] found that UBE2C was elevated and its expression was markedly associated with tumor mutation burden (TMB), microsatellite instability (MSI), immune cell infiltration, and diverse drug sensitivities. They showed that the METTL3/SNHG1/miRNA-140-3p axis could potentially regulate UBE2C expression. These experimental studies confirm the existence of synergy between the above involved factors with METTL3. 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