A Protein Expression Atlas on Tissue Samples and Cell Lines From Cancer Patients Provides Insights Into Tumor Heterogeneity and Dependencies

Authors

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

Publication Date

10-1-2024

Journal

Nature Cancer

Abstract

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.

Keywords

Humans, Neoplasms, Cell Line, Tumor, Biomarkers, Tumor, Proteomics, Gene Expression Regulation, Neoplastic, ErbB Receptors

DOI

10.1038/s43018-024-00817-x

PMID

39227745

PMCID

PMC11999798

PubMedCentral® Posted Date

4-16-2025

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes