Abstract

Abstract The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE) are the most widely used and deeply characterized resources for cancer research. Despite rich molecular and phenotypic data available for these cohorts, large-scale proteomic data across cancer lineages remain limited. Here we expanded our previous effort to generate high-quality protein expression data of 447 clinically relevant proteins for ~8,000 TCGA patient samples and ~900 CCLE cell line samples using reverse phase protein arrays. We show that the protein expression profiles provide deeper mechanistic insights into cancer dependency and serve as a sensitive functional readout for the fitness effect of somatic mutations, e.g., BRAF mutations. We develop a protein-centered strategy to identify synthetic lethality pairs with high confidence. We identify pro- and anti-metastasis protein markers and demonstrate their prognostic relevance in patient cohorts. Collectively, this dataset provides a valuable resource for elucidating cancer mechanisms, identifying protein biomarkers, and developing therapeutic strategies. Citation Format: Han Liang. An expanded quantitative protein expression atlas of human cancers. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5310.

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