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Abstract
Cancer is one of the major causes of death worldwide and the development of multidrug resistance (MDR) in cancer cells is the principal cause of chemotherapy failure. To gain insights into the specific mechanisms of MDR in cancer cell lines, we developed a novel method for the combined analysis of recently published datasets on drug sensitivity and CRISPR loss-of-function screens for the same set of cancer cell lines. For our analysis, we first selected cell lines that consistently exhibit drug resistance across several classes of compounds. We then identified putative resistance genes for each class of compound and used inferred gene regulatory networks (GRNs) to study possible mechanisms underlying the development of MDR in the identified cancer cell lines. We show that the same method of analysis can also be used to identify cell lines that consistently exhibit resistance to the gene knockout effect of the CRISPR-Cas9 technique and to study the possible underlying mechanisms. In the GRN associated to the drug resistant cell lines, we identify genes previously associated with resistance (UHMK1, RALYL, MGST3, USP9X, and ESRG), genes for which an indirect association can be identified (SPINK13, LINC00664, MRPL38, and EMILIN3), and genes that are found to be overexpressed in non-resistant cancer cell lines (MRPL38, EMILIN3 and RALYL). In the GRNs associated to the CRISPR-Cas9 resistance mechanism, none of the identified genes has been previously reported in the admittedly sparse literature on the subject. However, some of these genes have a common role: APBB2, RUNX1T1, ZBTB7C, and ISX regulate transcription, while APBB2, BTG3, ZBTB7C, SZRD1 and LEF1 have a function in regulating proliferation, suggesting a role for these two pathways. While our results are specific for the lung cancer cell lines we selected for this work, our method of analysis can be applied to cell lines from other tissues and for which the required data is available.
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Details
1 University of Trento, CIBIO Department, Povo, Italy (GRID:grid.11696.39) (ISNI:0000 0004 1937 0351)
2 University of Trento, CIBIO Department, Povo, Italy (GRID:grid.11696.39) (ISNI:0000 0004 1937 0351); Fondazione Bruno Kessler, Povo, Italy (GRID:grid.11469.3b) (ISNI:0000 0000 9780 0901)
3 University of Trento, Department of Mathematics, Povo, Italy (GRID:grid.11696.39) (ISNI:0000 0004 1937 0351); Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Rovereto, Italy (GRID:grid.491181.4)