Strongly preserved modules between cancer tissue and cell line contribute to drug resistance analysis across multiple cancer types
Genomics. 2021 Feb 26:S0888-7543(21)00075-6. doi: 10.1016/j.ygeno.2021.02.015. Online ahead of print.ABSTRACTThe existence and emergence of drug resistance in tumor cells is the main burden of cancer treatment. Most cancer drug resistance analyses are based entirely on cell line data and ignore the discordance between human tumors and cell lines, leading to biased preclinical model transformation. Based on cancer tissue data in TCGA and cancer cell line data in CCLE, this study identified and excluded non-preserved module (NP module) between cancer tissue and cell lines. We used strongly preserved module (SP module) for clinically relevant drug resistance analysis and identified 2068 "cancer-drug-module" pairs of 7 cancer types and 212 drugs based on data in GDSC. Furthermore, we identified potentially ineffective combination therapy (PICT) from multiple perspectives. Finally, we found 1608 sets of predictors that can predict drug response. These results provide insights and clues for the clinical selection of effective chemotherapy drugs to overcome cancer resistance in a new perspective.PMID:33647440 | DOI:10.1016/j.ygeno.2021.02.015
Source: Genomics - Category: Genetics & Stem Cells Authors: Siyao Dong Chengyan Song Baocui Qi Xiaochen Jiang Lu Liu Yan Xu Source Type: research