The Cancer Genome Atlas (TCGA) has yielded unprecedented genetic and molecular characterization of the cancer genome, yet the functional consequences and patient-relevance of many putative cancer drivers remain undefined. TCGADEPMAP is the first hybrid map of TCGA patient dependencies that was built from 6,581 expression-based predictive models of gene essentiality across 791 cancer cell models within the Cancer Dependency Map (DEPMAP). TCGADEPMAP captured well-known cancer lineage and sub-lineage dependencies (e.g., ESR1, ERBB2, etc.), genetic drivers (e.g., KRAS, BRAF, etc.), and synthetic lethalities (e.g., STAG1/2, SMARCA2/4, etc.), demonstrating the robustness of TCGADEPMAP as a translational dependency map. TCGADEPMAP also unveiled novel synthetic lethalities that were experimentally confirmed using multiplexed CRISPR screening across multiple cancer cell lines. Other map "extensions" were built to capture unique aspects of patient-relevant tumor dependencies, including translating gene essentiality to drug response in patient-derived xenograft (PDX) models (i.e., PDXEDEPMAP) and predicting gene tolerability within normal tissues (GTEXDEPMAP). Collectively, this study demonstrates how translational dependency maps can be used to leverage the rapidly expanding catalog of patient genomic datasets to identify and prioritize novel therapeutic targets with the best therapeutic indices. Competing Interest Statement All authors are employees of AbbVie. The design, study conduct, and financial support for this research were provided by AbbVie. AbbVie participated in the interpretation of data, review, and approval of the publication. Footnotes * https://figshare.com/s/b64384355cff5b6174e2 * https://figshare.com/s/ed79c828af703f840397...

TCGADEPMAP — Mapping Translational Dependencies and Synthetic Lethalities within The Cancer Genome Atlas

10.1101/2022.03.24.485544