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A protein expression atlas on tissue samples and cell lines from cancer patients provides insights into tumor heterogeneity and dependencies

  • Jun Li,
  • Wei Liu,
  • Kamalika Mojumdar,
  • Hong Kim,
  • Zhicheng Zhou,
  • Zhenlin Ju,
  • Shwetha V. Kumar,
  • Patrick Kwok-Shing Ng,
  • Han Chen,
  • Michael A. Davies,
  • Yiling Lu,
  • Rehan Akbani,
  • Gordon B. Mills,
  • Han Liang

摘要

The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) are foundational resources in cancer research, providing extensive molecular and phenotypic data. However, large-scale proteomic data across various cancer types for these cohorts remain limited. Here, we expand upon our previous work to generate high-quality protein expression data for approximately 8,000 TCGA patient samples and around 900 CCLE cell line samples, covering 447 clinically relevant proteins, using reverse-phase protein arrays. These protein expression profiles offer profound insights into intertumor heterogeneity and cancer dependency and serve as sensitive functional readouts for somatic alterations. We develop a systematic protein-centered strategy for identifying synthetic lethality pairs and experimentally validate an interaction between protein kinase A subunit α and epidermal growth factor receptor. We also identify metastasis-related protein markers with clinical relevance. This dataset represents a valuable resource for advancing our understanding of cancer mechanisms, discovering protein biomarkers and developing innovative therapeutic strategies.