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

Machine learning discoveries of NFκB-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 Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combinations of factors/genes/proteins that might be affecting the pathway under certain conditions. In colorectal cancer (CRC) cells treated with ETC-1922159, many genes were found up and down regulated, individually. A recently developed search engine ranked combinations of Nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB)-X (X, a particular gene/protein) at 2nd order level after drug administration. These rankings reveal which NFκB-X combinations might be working synergistically in CRC. If found true, oncologists can further test the combination of interest in wet lab and determine the mechanism of functioning between the NFκB and X. In this research work, we cover combinations of caspase (CASP) with receptor interacting serine/threonine kinase (RIPK) family, mucin (MUC) family with RIPK, tumor necrosis factor (TNF) with NF-κB family and NF-κB-Inhibitor (NF-κB-I), NFκB-2/I with STAT family, IκB kinase ε (IKBKE) with STAT family, IKBKE with conjugal transfer protein (TRAF), ATPbinding cassette (ABC) domain transporters with NFκB, IKBKE with ubiquitination modifier enzyme and ubiquitination conjugating enzymes (UBA/UBE) and REL-A/B with NFκB . Keywords: NFκB, Porcupine inhibitor ETC-1922159, Sensitivity analysis, Colorectal cancer. 1. Introduction In the unpublished preprint Sinha [1], a frame work of a search engine was developed which can rank combinations of factors (genes/proteins) in a signaling pathway. Such combinations are of import due to the vast search space in which they exist and the IML dicoveries of NFκB-X synergy in ETC-1922159 treated CRC cells Email address: [email protected] (shriprakash sinha) 1Aspects of unpublished work were presented in a poster session at (1) the recently concluded first ever Wnt Gordon Conference, from 6-11 August 2017, held in Stowe, VT 05672, USA. Preprint submitted to Preprint August 29, 2024 difficulty to find them. The search engine facilitates in prioritizing the combinations5 as ranked biological hypotheses which the biologists might want to test in wet lab, to know if a synergistic combination is prevalent in a signaling pathway, in a direct or indirect manner. Interested readers are advised to go through unpublished preprints Sinha [1] and Sinha [2] for details regarding the search engine and the discoveries mentioned in there.10 2. Materials and Methods 2.1. Combinatorial search problem and a possible solution The issue of combinatorial search problem and a possible solution has been addressed in Sinha [3] and Sinha [2]. The details of the methodology of this manuscript have been explained in great detail in Sinha [3] & its application in Sinha [2]. Readers15 are requested to go through the same for gaining deeper insight into the working of the pipeline and its use of published data set generated after administration of ETC1922159. In order to understand the significance of the solution proposed to the problem of combinatorial search that the biologists face in revealing unknown biological search problem, these works are of importance.20 Briefly, from Sinha [2], the pipleline works by computing sensitivity indicies for each of these unique combinations and then vectorising these indices to connote and form discriminative feature vector for each combination. Since each combination is unique, the training and the test data are same. In the training data, the combinations are arranged and ranks from 1 to n are assigned. The ranking algorithm then learns25 the patterns from these combinations/sensitivity index vectors. Next the learned model is used to rank the test data by generating the ranking score for each of the unique combination. Sorting these shuffled scores of test data leads to prioritization of the combinations. Joachims [4] show an example of applying learned model to training data (same as the test data) in https://www.cs.cornell.edu/people/tj/svm_30 light/svm_rank.html. Note that these combinations are now ranked and give the biologists a chance to narrow down their focus on crucial biological hypotheses in the form of combinations which the biologists might want to test. Analogous to the webpage search engine, where the click of a button for a few key-words leads to a ranked list of web links, the pipeline uses sensitivity indices as an indicator of the strength of35 the influence of factors or their combinations, as a criteria to rank the combinations. 3. Results & Discussion 3.1. NF-κB related synergies 3.1.1. CASP - RIPK cross family analysis The caspase - receptor interacting protein kinases (RIPK) has an intricate mechanism40 which has not yet been discovered and many views exist about their synergistic interaction. Green et al. [5] presents a review of RIPK-dependent necrosis and its regula2 RANKING CASP FAMILY W.R.TRIPK FAMILY RANKING OF CASP4 W.R.TRIPK FAMILY RANKING OF CASP5 FAMILY W.R.TRIPK laplace linear rbf laplace linear rbf CASP4 - RIPK1 1154 1259 147 CASP5 - RIPK1 490 152 1818 CASP4 - RIPK2 559 2147 434 CASP5 - RIPK2 1274 2485 608 CASP4 - RIPK3 111 131 41 CASP5 - RIPK3 523 1047 317 CASP4 - RIPK4 187 1048 1039 CASP5 - RIPK4 7 1176 2361 1292 RANKING OF CASP7 W.R.TRIPK FAMILY RANKING OF CASP9 FAMILY W.R.TRIPK laplace linear rbf laplace linear rbf CASP7 - RIPK1 2445 1289 1253 CASP9 - RIPK1 1726 1304 1480 CASP7 - RIPK2 1584 406 155 CASP9 - RIPK2 2079 291 1647 CASP7 - RIPK3 1406 1057 2091 CASP9 - RIPK3 2133 2030 2295 CASP7 - RIPK4 1739 231 2332 CASP9 - RIPK4 2037 1627 363 RANKING OF CASP10 W.R.TRIPK FAMILY RANKING OF CASP16 FAMILY W.R.TRIPK laplace linear rbf laplace linear rbf CASP10 - RIPK1 758 846 1405 CASP16 - RIPK1 73 1046 1887 CASP10 - RIPK2 1535 2312 884 CASP16 - RIPK2 20 932 1189 CASP10 - RIPK3 1530 250 2181 CASP16 - RIPK3 30 359 717 CASP10 - RIPK4 954 415 1547 CASP16 - RIPK4 493 2507 519 Table 1: 2nd order interaction ranking between CASP w.r.t RIPK family members. tion by CASPs. Furthermore, Lin et al. [6] show that cleavage of the death domain RIPK by CASP-8 prompts TNF-induced apoptosis. RIPK1 is known to promote death receptor-independent CASP-8 mediated apoptosis under unresolved ER stress condi-45 tions, as shown by Estornes et al. [7]. Weng et al. [8] show that CASP-8 and RIPK regulate bacteria-induced innate immune responses and cell death. Also, Moriwaki et al. [9] show that RIPK3-CASP8 complex mediates atypical pro-IL-1βprocessing. Recent work by Declercq et al. [10] shows RIPK importance in cell death and survival along with CASP influence. These interactions point to a definite synergy between50 the CASP - RIPK. Chaudhary et al. [11] showed activation of NF-κB pathway via Caspase-8 (CASP-8) and its homologs. Additionally, Caspase-8 was found to interact with Receptor-interacting serine/threonine-protein kinase 1 (RIPK1). Family members belonging to each of the factors like CASP, RIPK etc, might be involved synergistically in pathological case or otherwise. CASP and RIPK members were found to be up55 regulated after the treatment of ETC-1922159 in colorectal cancer cells. Tables 1 and 2 show the rankings of CASP family w.r.t RIPK and vice versa, respectively. Followed by this is the derived influences between CASP and RIPK via two way analysis of majority voting of rankings in the two foregoing tables. These influences are tabulated in table 3. In table 1, only CASP9 - RIPK3 combination showed60 up regulation with rankings of 2133 (laplace), 2030 (linear) and 2295 (rbf). In table 2, RIPK1 showed up regulation with CASP-4/10 with rankings of 2363 (laplace) and 1805 (rbf) for CASP4 - RIPK1; and 2438 (laplace) and 1915 (linear) for CASP10 - RIPK1, respectively. RIPK2 showed up regulation with CASP-5/9/16 with rankings of 1776 (linear) and 2247 (rbf) for CASP5 - RIPK2; 2000 (laplace), 2476 (linear) and65 2138 (rbf) for CASP9 - RIPK2; and 2006 (linear) and 2046 (rbf) for CASP16 - RIPK2; Finally, RIPK4 showed up regulation with CASP-16 with rankings of 2273 (laplace) 3 RANKING RIPK FAMILY W.R.TCASP FAMILY RANKING OF RIPK FAMILY W.R.TCASP4 RANKING OF RIPK FAMILY W.R.TCASP5 laplace linear rbf laplace linear rbf CASP4 - RIPK1 2363 1374 1805 CASP5 - RIPK1 7 82 131 CASP4 - RIPK2 1713 2349 1261 CASP5 - RIPK2 1577 1776 2247 CASP4 - RIPK3 1397 768 1008 CASP5 - RIPK3 574 14 30 CASP4 - RIPK4 2215 1334 1425 CASP5 - RIPK4 2448 1178 810 RANKING OF RIPK FAMILY W.R.TCASP7 RANKING OF RIPK FAMILY W.R.TCASP9 laplace linear rbf laplace linear rbf CASP7 - RIPK1 1341 2005 1131 CASP9 - RIPK1 820 140 611 CASP7 - RIPK2 1287 727 1143 CASP9 - RIPK2 2000 2476 2138 CASP7 - RIPK3 579 595 775 CASP9 - RIPK3 1550 430 97 CASP7 - RIPK4 852 1586 595 CASP9 - RIPK4 1565 862 209 RANKING OF RIPK FAMILY W.R.TCASP10 RANKING OF RIPK FAMILY W.R.TCASP16 laplace linear rbf laplace linear rbf CASP10 - RIPK1 2438 1915 1039 CASP16 - RIPK1 924 686 587 CASP10 - RIPK2 1526 1800 1228 CASP16 - RIPK2 1613 2006 2046 CASP10 - RIPK3 419 1481 2001 CASP16 - RIPK3 827 494 328 CASP10 - RIPK4 1303 947 785 CASP16 - RIPK4 2273 2023 1698 Table 2: 2nd order interaction ranking between RIPK w.r.t CASP family members. UNEXPLORED COMBINATORIAL HYPOTHESES CASP w.r.t RIKP family CASP9 RIPK3 RIPK w.r.t CASP family RIPK1 CASP4/CASP10 RIPK2 CASP5/CASP9/CASP16 RIPK4 CASP16 Table 3: 2nd order combinatorial hypotheses between CASP and RIPK. and 2023 (linear) for CASP16 - RIPK4. One can also interpret the results of the table 3 graphically, with the following influences - •CASP w.r.t RIKP family with CASP9 <−RIPK3 and •RIPK w.r.t70 CASP family with RIPK1 <−CASP-4/10; RIPK2 <−CASP-5/9/16 and RIPK4 <−CASP16. 3.1.2. MUC - RIPK cross family analysis In a recent work Sheng et al. [12] show that MUC13 promoted tumor necrosis factro (TNF)-induced NF-κB activation by interacting with TNFR1 and the E3 ligase,75 4 RANKING MUC FAMILY W.R.TRIPK FAMILY RANKING OF MUC1 W.R.TRIPK FAMILY RANKING OF MUCA3 W.R.TMUC3A laplace linear rbf laplace linear rbf MUC1 - RIPK1 2027 2249 218 MUC3A - RIPK1 945 186 1508 MUC1 - RIPK2 248 1802 389 MUC3A - RIPK2 840 2390 1653 MUC1 - RIPK3 342 410 342 MUC3A - RIPK3 2208 2017 689 MUC1 - RIPK4 176 162 853 MUC3A - RIPK4 714 1494 797 RANKING OF MUC4 W.R.TRIPK FAMILY RANKING OF MUC12 W.R.TRIPK FAMILY laplace linear rbf laplace linear rbf MUC4 - RIPK1 358 2384 690 MUC12 - RIPK1 317 2437 167 MUC4 - RIPK2 371 500 408 MUC12 - RIPK2 286 2178 76 MUC4 - RIPK3 809 371 1096 MUC12 - RIPK3 747 366 136 MUC4 - RIPK4 652 1863 1248 MUC12 - RIPK4 176 2249 2130 RANKING OF MUC13 W.R.TRIPK FAMILY RANKING OF MUC17 W.R.TRIPK FAMILY laplace linear rbf laplace linear rbf MUC13 - RIPK1 379 2241 227 MUC17 - RIPK1 858 932 1503 MUC13 - RIPK2 824 2483 227 MUC17 - RIPK2 248 934 37 MUC13 - RIPK3 1687 19 24 MUC17 - RIPK3 342 64 329 MUC13 - RIPK4 562 532 184 MUC17 - RIPK4 209 2335 1080 RANKING OF MUC20 W.R.TRIPK FAMILY laplace linear rbf MUC20 - RIPK1 1419 760 1794 MUC20 - RIPK2 948 2482 137 MUC20 - RIPK3 2192 2288 1796 MUC20 - RIPK4 1564 1619 2179 Table 4: 2nd order interaction ranking between MUC w.r.t RIPK family members. cIAP1, to increase ubiquitination of Receptor-interacting serine/threonine-protein kinase 1 (RIPK1). Family members belonging to each of the factors like MUC, RIPK etc, might be involved synergistically in pathological case or otherwise. MUC and RIPK members were found to be up regulated after the treatment of ETC-1922159 in colorectal cancer cells.80 Tables 4 and 5 show the rankings of MUC family w.r.t RIPK family and vice versa, respectively. Followed by this is the derived influences between MUC and RIPK. In table 4, MUC1 was found to be highly upregulated with RIPK1. This is reflected in the rankings of 2027 (linear) and 2249 (rbf) for MUC1 - RIPK1. MUC3A was found to be highly upregulated with RIPK3. This is reflected in the rankings of 2208 (laplace)85 and 2017 (rbf) for MUC3A - RIPK3. MUC12 was found to be highly upregulated with RIPK4. This is reflected in the rankings of 2249 (linear) and 2130 (rbf), for MUC12 - RIPK4. MUC20 was found to be highly upregulated with RIPK3. This is reflected in the rankings of 2192 (laplace), 2288 (linear) and 1796 (rbf) for MUC20 - RIPK3. In table 5, RIPK-1/2 was found to be highly upregulated with MUC1. This is90 reflected in the rankings of 1839 (laplace) and 2421 (rbf) for MUC1 - RIPK1; and 1913 (laplace) and 2091 (linear) for MUC1 - RIPK2. RIPK4 was found to be highly upregulated with MUC4. This is reflected in the rankings of 1981 (laplace), 1949 (linear) and 2028 for MUC4 - RIPK4. RIPK4 was found to be highly up regulated with 5 RANKING RIPK FAMILY W.R.TMUC FAMILY RANKING OF RIPK FAMILY W.R.TMUC1 RANKING OF RIPK FAMILY W.R.TMUC3A laplace linear rbf laplace linear rbf MUC1 - RIPK1 1839 58 2421 MUC3A - RIPK1 783 1668 1842 MUC1 - RIPK2 1913 2091 954 MUC3A - RIPK2 758 2301 459 MUC1 - RIPK3 1038 268 295 MUC3A - RIPK3 268 1595 1893 MUC1 - RIPK4 1385 2246 1298 MUC3A - RIPK4 1770 1109 1461 RANKING OF RIPK FAMILY W.R.TMUC4 RANKING OF RIPK FAMILY W.R.TMUC12 laplace linear rbf laplace linear rbf MUC4 - RIPK1 562 1621 2216 MUC12 - RIPK1 1462 682 2351 MUC4 - RIPK2 383 924 494 MUC12 - RIPK2 989 597 1798 MUC4 - RIPK3 541 43 129 MUC12 - RIPK3 2158 1286 1636 MUC4 - RIPK4 1981 1949 2028 MUC12 - RIPK4 1577 975 976 RANKING OF RIPK FAMILY W.R.TMUC13 RANKING OF RIPK FAMILY W.R.TMUC17 laplace linear rbf laplace linear rbf MUC13 - RIPK1 1961 1535 32 MUC17 - RIPK1 260 446 260 MUC13 - RIPK2 784 494 1467 MUC17 - RIPK2 1021 1114 2355 MUC13 - RIPK3 860 1514 1425 MUC17 - RIPK3 427 223 128 MUC13 - RIPK4 107 1387 1972 MUC17 - RIPK4 1567 2225 2048 RANKING OF RIPK FAMILY W.R.TMUC20 laplace linear rbf MUC20 - RIPK1 514 2042 420 MUC20 - RIPK2 1039 1751 1950 MUC20 - RIPK3 303 2504 280 MUC20 - RIPK4 794 1193 989 Table 5: 2nd order interaction ranking between RIPK w.r.t MUC family members. MUC17. This is reflected in the rankings of 2225 (linear) and 2048 (rbf) for MUC17 -95 RIPK4. RIPK2 was found to be highly up regulated with MUC20. This is reflected in the rankings of 1751 (linear) and 1950 (rbf) for MUC20 - RIPK2. One can also interpret the results of the table 6 graphically, with the following influences - •MUC w.r.t RIKP family with MUC1 <−RIPK1; MUC3A <−RIPK3; MUC12 <−RIPK4; MUC20 <−RIPK3 and •RIPK w.r.t MUC family with MUC1100 −>RIPK-1/2; MUC4 −>RIPK4; MUC17 −>RIPK4; MUC20 −>RIPK2. 3.1.3. TNF - NF-κB-2/I cross family analysis The NF-κB family and NF-κB-Inhibitor i.e NF-κB-I play a significant role in immune response to infection. Problems in its functioning leads to cancer, infections, inflammatory and autoimmune diseases. The discovery and seminal work by Sen and Baltimore105 [13] on NF-κB lead to range of research on immune responses and study of related pathological cases. Tanaka and Nakano [14] have shown that NF-κB2 limits TNF-α induced osteoclastogenesis. Recently, in Japanese population, Imamura et al. [15] show that the impaired NF-κBIE gene function decreases cellular uptake of methotrexate by down-regulating SLC19A1 expression in a human rheumatoid arthritis cell line. They110 postulate that NF-κBIE could be closely related to NF-κB activity. Also, Lee et al. [16] show through deep study of fold-change analysis of the inter-relation between 6 UNEXPLORED COMBINATORIAL HYPOTHESES MUC w.r.t RIKP family MUC1 RIPK1 MUC3A RIPK3 MUC12 RIPK4 MUC20 RIPK3 RIPK w.r.t MUC family MUC1 RIPK1/RIPK2 MUC4 RIPK4 MUC17 RIPK4 MUC20 RIPK2 Table 6: 2nd order combinatorial hypotheses between MUC and RIPK. NF-κB and TNFs. However, the synergy between these members has yet not been explored completely. We found some interesting combinations that were allocated high numerical ranking (in silico) to indicate synergistic up regulation in CRC cells after115 ETC-1922159 treatment, apart from the individual up regulation that was observed in wet experiements. Tables 7 and 8 depict the rankings of TNF family w.r.t to NF-κB-2/I and vice versa, respectively. Followed by this is table 9 that contains the derived influences via majority voting of the rankings in the tables containing two-way cross family rankings.120 In table 7 we find TNF-RSF10A/RSF12A up regulated with NFkB2. These are reflected in rankings of 2095 (laplace) and 2509 (rbf) for NFkB2 - TNFRSF10A; and 1813 (laplace) and 1893 (rbf) for NFkB2 - TNFRSF12A. TNF-AIP1/RSF10A/RSF10D/RSF14/SF10 were found to be up regulated with NFkBI-A. These are reflected in rankings of 1779 (laplace) and 1904 (linear) for NFkBI-A - TNF-AIP1; 2499 (laplace) and 2191 (rbf) for125 NFkBI-A - TNFRSF10A; 2498 (laplace), 2344 (linear) and 2501 (rbf) for NFkBI-A - TNFRSF10D; 1974 (laplace) and 2045 (linear) for NFkBI-A - TNFRSF14; and 2185 (laplace) and 2316 (rbf) for NFkBI-A - TNFSF10, respectively. TNF-AIP2/RSF14 were found to be up regulated with NFkBI-E. These are reflected in rankings of 2347 (laplace) and 1863 (linear) for NFkBI-E - TNFAIP2; and 1877 (laplace) and 2282 (lin-130 ear) for NFkBI-E - TNFRSF14, respectively. Finally, TNF-RSF10B/RSF10D/RSF12A were found to be up regulated with NFkBI-Z. These are reflected in rankings of 2204 (laplace) and 1991 (rbf) for NFkBI-Z - TNFRSF10B; 2214 (laplace), 2033 (linear) and 2514 (rbf) for NFkBI-Z - TNFRSF10D; and 2370 (linear) and 1841 (rbf) for NFkBIZ - TNFRSF12A, respectively. In table 8 we find NFkB-2 to be up regulated along135 7 RANKING TNF FAMILY W.R.TNFKB-2/I FAMILY RANKING OF TNF FAMILY W.R.TNFKB2 RANKING OF TNF FAMILY W.R.TNFKBI-A laplace linear rbf laplace linear rbf NFkB2 - TNF 1620 615 1897 NFkBI-A - TNF 820 1495 1109 NFkB2 - TNF-AIP1 324 649 1387 NFkBI-A - TNF-AIP1 1779 1904 1400 NFkB2 - TNF-AIP2 1437 715 1986 NFkBI-A - TNF-AIP2 1247 217 766 NFkB2 - TNF-AIP3 1272 1574 441 NFkBI-A - TNF-AIP3 776 981 212 NFkB2 - TNF-RSF1A 30 2465 575 NFkBI-A - TNF-RSF1A 1580 1422 43 NFkB2 - TNF-RSF10A 2095 817 2509 NFkBI-A - TNF-RSF10A 2499 1438 2191 NFkB2 - TNF-RSF10B 37 1411 250 NFkBI-A - TNF-RSF10B 2075 1555 1401 NFkB2 - TNF-RSF10D 2473 12 1499 NFkBI-A - TNF-RSF10D 2498 2344 2501 NFkB2 - TNF-RSF12A 1813 824 1893 NFkBI-A - TNF-RSF12A 2337 1101 1491 NFkB2 - TNF-RSF14 1799 834 302 NFkBI-A - TNF-RSF14 1974 2045 1136 NFkB2 - TNF-RSF21 332 1973 1719 NFkBI-A - TNF-RSF21 1119 951 903 NFkB2 - TNF-SF10 1627 1614 1299 NFkBI-A - TNF-SF10 2185 499 2316 NFkB2 - TNF-SF15 564 2437 1064 NFkBI-A - TNF-SF15 564 1684 1473 RANKING OF TNF FAMILY W.R.TNFKBI-E RANKING OF TNF FAMILY W.R.TNFKBI-Z laplace linear rbf laplace linear rbf NFkBI-E - TNF 2443 925 228 NFkBI-Z - TNF 851 776 850 NFkBI-E - TNF-AIP1 1720 685 971 NFkBI-Z - TNF-AIP1 153 397 621 NFkBI-E - TNF-AIP2 2347 1863 964 NFkBI-Z - TNF-AIP2 2188 432 566 NFkBI-E - TNF-AIP3 559 1663 280 NFkBI-Z - TNF-AIP3 775 10 2362 NFkBI-E - TNF-RSF1A 846 1624 176 NFkBI-Z - TNF-RSF1A 399 2006 93 NFkBI-E - TNF-RSF10A 840 359 952 NFkBI-Z - TNF-RSF10A 1380 2004 1540 NFkBI-E - TNF-RSF10B 835 2257 1294 NFkBI-Z - TNF-RSF10B 2204 1438 1991 NFkBI-E - TNF-RSF10D 2454 1018 1566 NFkBI-Z - TNF-RSF10D 2214 2033 2514 NFkBI-E - TNF-RSF12A 383 166 1464 NFkBI-Z - TNF-RSF12A 1638 2370 1841 NFkBI-E - TNF-RSF14 1877 2282 1426 NFkBI-Z - TNF-RSF14 1120 1505 1899 NFkBI-E - TNF-RSF21 2129 1293 831 NFkBI-Z - TNF-RSF21 207 804 344 NFkBI-E - TNF-SF10 890 1096 1816 NFkBI-Z - TNF-SF10 609 1088 1344 NFkBI-E - TNF-SF15 523 1957 32 NFkBI-Z - TNF-SF15 1237 1375 2196 Table 7: 2nd order interaction ranking between TNF w.r.t NFkB-2/I family members. with TNF-AIP1/AIP2/AIP3. These are reflected in rankings of 2027 (linear) and 1807 (rbf) for NFkB2 - TNFAIP1; 2077 (laplace) and 2224 (rbf) for NFkB2 - TNFAIP2; and 2336 (linear) and 2130 (rbf) for NFkB2 - TNFAIP3, respectively. Finally, NFkBI-E was found to be up regulated with TNFRSF10D. These are reflected in rankings of 2136 (laplace) and 1811 (rbf) for NFkBI-E - TNFRSF10D.140 One can also interpret the results of the table 9 graphically, with the following influences - •TNF w.r.t NFkB family with NFkB2 −>TNF-RSF10A/RSF12A; NFkBIA−>TNF-AIP1/RSF10A/RSF10D/RSF14/SF10; NFkBI-E −>TNF-AIP2/RSF14; NFkBI-Z −>TNF-RSF10B/RSF10D/RSF12A; and •NFkB w.r.t TNF family with NFkB-2 <−TNF-AIP1/AIP2/AIP3 and NFkBI-E <−TNF-RSF10D.145 3.1.4. NFκB-2/I - STAT cross family analysis Grivennikov and Karin [17] show the potent collaboration and cross talk of STAT3 and NF-κB in cancer. In chronic lymphocytic leukemia cells, Liu et al. [18] observe that STAT-3 activates NF-κB. Co-opertion between STAT3 and NF-κB pathways has been observed in subtypes of diffuse large B Cell Lymphoma by Lam et al. [19]. Lee et al.150 8 RANKING NFKB-2/I FAMILY W.R.TTNF FAMILY RANKING OF NFKB-2/I FAMILY W.R.TTNF RANKING OF NFKB-2/I FAMILY W.R.TTNF-AIP1 laplace linear rbf laplace linear rbf NFkB-2 - TNF 1632 989 1453 NFkB-2 - TNF-AIP1 2027 1807 1140 NFkBI-A - TNF 904 561 658 NFkBI-A - TNF-AIP1 2072 349 1218 NFkBI-E - TNF 2116 1247 803 NFkBI-E - TNF-AIP1 56 420 1551 NFkBI-Z - TNF 691 51 265 NFkBI-Z - TNF-AIP1 499 1648 646 RANKING OF NFKB-2/I FAMILY W.R.TTNF-AIP2 RANKING OF NFKB-2/I FAMILY W.R.TTNF-AIP3 laplace linear rbf laplace linear rbf NFkB-2 - TNF-AIP2 2077 1027 2224 NFkB-2 - TNF-AIP3 1042 2336 2130 NFkBI-A - TNF-AIP2 499 22 1192 NFkBI-A - TNF-AIP3 1452 411 637 NFkBI-E - TNF-AIP2 526 1755 338 NFkBI-E - TNF-AIP3 711 1686 2041 NFkBI-Z - TNF-AIP2 452 988 1617 NFkBI-Z - TNF-AIP3 1979 886 278 RANKING OF NFKB-2/I FAMILY W.R.TTNF-RSF1A RANKING OF NFKB-2/I FAMILY W.R.TTNF-RSF10A laplace linear rbf laplace linear rbf NFkB-2 - TNF-RSF1A 648 164 990 NFkB-2 - TNF-RSF10A 611 1007 454 NFkBI-A - TNF-RSF1A 435 1454 130 NFkBI-A - TNF-RSF10A 458 190 1412 NFkBI-E - TNF-RSF1A 431 980 1417 NFkBI-E - TNF-RSF10A 1719 263 374 NFkBI-Z - TNF-RSF1A 550 2213 1447 NFkBI-Z - TNF-RSF10A 342 742 732 RANKING OF NFKB-2/I W.R.TTNF-RSF10B RANKING OF NFKB-2/I W.R.TTNF-RSF10D laplace linear rbf laplace linear rbf NFkB-2 - TNF-RSF10B 713 1408 2397 NFkB-2 - TNF-RSF10D 123 1939 543 NFkBI-A - TNF-RSF10B 1237 1054 562 NFkBI-A - TNF-RSF10D 371 948 584 NFkBI-E - TNF-RSF10B 1352 931 2142 NFkBI-E - TNF-RSF10D 2136 621 1811 NFkBI-Z - TNF-RSF10B 165 2407 361 NFkBI-Z - TNF-RSF10D 259 400 1341 RANKING OF NFKB-2/I FAMILY W.R.TTNF-RSF12A RANKING OF NFKB-2/I FAMILY W.R.TTNF-RSF14 laplace linear rbf laplace linear rbf NFkB-2 - TNF-RSF12A 250 341 1232 NFkB-2 - TNF-RSF14 299 1253 543 NFkBI-A - TNF-RSF12A 689 2225 17 NFkBI-A - TNF-RSF14 280 1126 277 NFkBI-E - TNF-RSF12A 1188 1133 765 NFkBI-E - TNF-RSF14 278 2025 1557 NFkBI-Z - TNF-RSF12A 973 1590 2298 NFkBI-Z - TNF-RSF14 131 893 1953 RANKING OF NFKB-2/I FAMILY W.R.TTNF-RSF21 RANKING OF NFKB-2/I FAMILY W.R.TTNF-SF10 laplace linear rbf laplace linear rbf NFkB-2 - TNF-RSF21 250 341 1232 NFkB-2 - TNF-SF10 1643 496 743 NFkBI-A - TNF-RSF21 689 2225 17 NFkBI-A - TNF-SF10 262 1238 1352 NFkBI-E - TNF-RSF21 1188 1133 765 NFkBI-E - TNF-SF10 985 1090 158 NFkBI-Z - TNF-RSF21 973 1590 2298 NFkBI-Z - TNF-SF10 537 1557 2104 RANKING OF NFKB-2/I FAMILY W.R.TTNF-SF15 laplace linear rbf NFkB-2 - TNF-SF15 1521 786 1211 NFkBI-A - TNF-SF15 2367 325 1079 NFkBI-E - TNF-SF15 97 1868 1195 NFkBI-Z - TNF-SF15 774 407 372 Table 8: 2nd order interaction ranking between NFkB-2/I family w.r.t TNF family members. [20] also shows a signal network involving coactivated NF-κB and STAT3 and altered p53 modulates BAX/BCL-XL expression and promotes cell survival of head and neck squamous cell carcinomas. These observations show a definite, concommitent functioning of the two pathways and we further found that some of them were up regulated synergistically in CRC cells after ETC-1922159 treatment, via in silico ranking of the155 combinations. Tables 10 and 11 show ranking of STAT family w.r.t NFkB-2/I and vice versa, respectively. Followed by this is the derived influences from majority voting of rankings in the two foregoing tables, which is shown in table 12. Tables 10 and 11 show the rankings of STAT family w.r.t NFkB-2/I and vice versa, respectively. Followed by this is the influence between the components in table 12, via160 9 RANKING UBA/E2 FAMILY VS IKBKE RANKING OF UBA/E2 FAMILY W.R.TIKBKE RANKING OF IKBKE W.R.TUBA/E2 FAMILY laplace linear rbf laplace linear rbf IKBKE - UBA-1 1752 785 966 UBA-1 - IKBKE 2327 1807 2066 IKBKE - UBA-7 2189 2271 1335 IKBKE - UBA-7 1134 2326 2456 IKBKE - UBA-P1 2262 1901 2341 IKBKE - UBA-P1 2162 1817 1407 IKBKE - UBA-LD2 2034 1773 1409 IKBKE - UBA-LD2 1381 1647 556 IKBKE - UBE2-A 2293 2319 2396 IKBKE - UBE2-A 2422 536 2328 IKBKE - UBE2-B 2129 1516 1795 IKBKE - UBE2-B 680 2367 2427 IKBKE - UBE2-F 2494 2233 1896 IKBKE - UBE2-F 2309 181 24 IKBKE - UBE2-H 1265 1666 1257 IKBKE - UBE2-H 385 710 746 IKBKE - UBE2-J1 905 1936 1046 IKBKE - UBE2-J1 903 1729 2215 IKBKE - UBE2-Z 2016 2103 481 IKBKE - UBE2-Z 783 2366 1909 Table 20: 2nd order interaction ranking between UBA/E2 family w.r.t IKBKE. UNEXPLORED COMBINATORIAL HYPOTHESES UBA/E2 w.r.t IKBKE IKBKE UBA-1/7/P1 IKBKE UBE2-A/B/Z IKBKE w.r.t UBE/A2 IKBKE UBA-7/P1/LD2 IKBKE UBE2-A/B/F/Z Table 21: 2nd order combinatorial hypotheses between NFkB-2/I and TNF RANKING NFKB-2/I VS REL-A RANKING OF NFKB-2/I FAMILY W.R.TREL-A RANKING OF REL-A W.R.TNFKB-2/I FAMILY laplace linear rbf laplace linear rbf NFkB2 - RELA 664 420 271 NFkB2 - RELA 2454 794 2307 NFKBIA - RELA 198 205 190 NFKBIA - RELA 2106 2305 1153 NFKBIE - RELA 1503 2321 331 NFKBIE - RELA 1664 456 1926 NFKBIZ - RELA 323 1714 619 NFKBIZ - RELA 1924 1687 1584 Table 22: 2nd order interaction ranking between NFkB-2/I VS REL-A family members. 3.1.9. REL-A/B - NFκB cross family analysis255 REL-A is known to be associated with NF-κB and most deeply studied member of the NF-κB. Tian et al. [30] observe that the NFkB subunit RELA is a master transcriptional regulator of the committed epithelial-mesenchymal transition in airway epithelial cells. Ke et al. [31] observe that inactivation of NF-κB p65 (RelA) in liver improves insulin 16 RANKING REL-B VS NFKB-2/I FAMILY RANKING OF NFKB-2/I W.R.TREL-B RANKING OF REL-B W.R.TNFKB-2/I laplace linear rbf laplace linear rbf NFkB2 - RELB 503 2146 1788 NFkB2 - RELB 1156 1346 2184 NFKBIA - RELB 239 1576 924 NFKBIA - RELB 968 424 1725 NFKBIE - RELB 1203 714 2200 NFKBIE - RELB 1414 2228 800 NFKBIZ - RELB 1776 2244 1869 NFKBIZ - RELB 746 1281 1055 Table 23: 2nd order interaction ranking between NFkB-2/I VS REL-B family members. sensitivity and inhibits cAMP/PKA pathway. Weichert et al. [32] observe that high260 expression of RelA/p65 is associated with activation of NF-κB-dependent signaling in pancreatic cancer. These findings and many others not cited here show the deep interaction between REL and NF-κB members. Table 22 shows rankings of RELA w.r.t NFkB members and vice versa. Table 23 shows rankings of RELB w.r.t NFkB members and vice versa. Finally, table 24 shows the hypotheses generated from majority voting265 of the ranks. In table 22 we find RELA to be up regulated w.r.t NFKB2. This is reflected in rankings of 2454 (laplace) and 2307 (rbf) for NFkB2 - RELA. Similarly, NFKBIA was found to be up regulated w.r.t RELA. This is reflected in rankings of 2106 (laplace) and 2305 (linear) for NFKBIA - RELA. In table 23 we find NFkB2 to be up regulated RELB. This is reflected in 2146 (laplace) and 1788 (rbf) for NFkB2 - RELB. Similarly,270 we find NFKBIZ to be 1776 (laplace), 2244 (linear) and 1869 (rbf) for NFKBIZ - RELB. Table 24 shows the derived influences which can be represented graphically, with the following influences - •NFkB-2/I family w.r.t REL-B with NFkB2 <−RELB and NFKBIZ <−RELB and •REL-A w.r.t NFkB-2/I family with NFkB2 −> RELA and NFKBIA −>RELA.275 UNEXPLORED COMBINATORIAL HYPOTHESES NFkB-2/I family w.r.t REL-B NFkB2 RELB NFKBIZ RELB REL-A w.r.t NFkB-2/I family NFkB2 RELA NFKBIA RELA Table 24: 2nd order combinatorial hypotheses between NFkB-2/I and ABC 17 Conclusion Presented here are a range of multiple synergistic NFκB 2nd order combinations that were ranked via a search engine. Later, two way cross family analysis between components of these combinations were conducted. Via majority voting across the ranking methods, it was possible to find plausible unexplored synergistic combinations280 that might be prevalent in CRC cells after treatment with ETC-1922159 drug. The two-way cross family analysis also assists in deriving influences between components which serve as hypotheses for further tests. If found true, it paves way for biologists/oncologists to further investigate and understand the mechanism behind the synergy through wet experiments.285 Conflict of interest There are no conflicts to declare. Author’s contributions Concept, design, in silico implementation - SS. Analysis and interpretation of results - SS. Manuscript writing - SS. Manuscript revision - SS. Approval of manuscript - SS290 Acknowledgements Special thanks to Mrs. Rita Sinha and Mr. Prabhat Sinha for supporting the author financially, without which this work could not have been made possible. Source of Data Data used in this research work was released in a publication in Madan et al. [33]. 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