Abstract
Abstract The identification of biomarkers of therapeutic response for different cancers presents significant challenges owing to the heterogeneity of these diseases. Whole-genome CRISPR gene knockout screening (DepMap) and large-scale drug dosing (e.g. PRISM, and Sanger GDSC) performed across large panels of cancer cell lines reveal a whole spectrum of cancer vulnerabilities and dependencies that can be used to identify potential biomarkers and perturbed pathways in subtypes of cancers. In this study, we identified tumor type-specific dependent genes with CRISPR screening data. Functional relationships among genes were systematically examined by clustering genes with pronounced dependencies based on established biological pathways and conducting a co-dependency analysis. We found that both tumor type and subtype-specific analysis allowed the classification of cell lines based on gene dependency. Next, we correlated gene dependency of the selected dependent genes with normalised drug sensitivity scores (AUC) to triangulate potential biomarkers of drug response. We first applied this method to several tumor types which are well-characterised by known cancer drivers, and successfully identified known biomarkers and targeted pathways. However, we also identified previously unknown gene-drug relationships which will be further explored. Subsequent analysis of rarer cancers, including soft tissue sarcoma, yielded promising gene targets. This analysis pipeline can be used extensively to mine DepMap data using any subset of cell lines of interest for biomarker discovery. Citation Format: Shen Yong Yeo, Wai Yee Wong, Jesslyn, Tan Boon Toh, Valerie Shiwen Yang, Xing Yi Woo. Utilizing Cancer Vulnerabilities and Dependencies to Explore Cancer Biomarkers by Triangulating Large-Scale Gene Knockout and Drug Response Data [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P58.
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