A Proteogenomics Data-Driven Knowledge Base of Human Cancer

Authors

Yuxing Liao
Sara R Savage
Yongchao Dou
Zhiao Shi
Xinpei Yi
Wen Jiang
Jonathan T Lei
Bing Zhang

Publication Date

9-20-2023

Journal

Cell Systems

DOI

10.1016/j.cels.2023.07.007

PMID

37619559

PMCID

PMC10530292

PubMedCentral® Posted Date

9-20-2024

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes

Keywords

Humans, Proteomics, Proteogenomics, Genomics, Neoplasms, Knowledge Bases, Proteogenomics, proteomics, phosphoproteomics, cancer, knowledge base, CPTAC, pan-cancer

Abstract

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.