Funding: U24CA210954 PI: Bing Zhang Subcontract Site PI: Xi Chen
Proteogenomic characterization of human tumors seeks to explain how complex genomic alterations drive the hallmarks of cancer through mass spectrometry based proteomic analysis. This application proposes an integrative proteogenomic data analysis center (iPGDAC) built on our established expertise and resources. The overarching goal of the iPGDAC is to analyze data generated by Clinical Proteomic Tumor Analysis Consortium (CPTAC) and related resources to better understand cancer biology and to improve cancer treatment.
To comprehensively exploit all CPTAC data, we propose three tiers of data analysis. Tier 1 analyses will integrate proteomic and genomic data generated from individual studies. These analyses will identify variant peptides and proteins as candidate biomarkers or therapeutic targets, will predict patient prognosis and response to therapy based on multi-omics data, and will reveal mechanisms of drug action and acquired drug resistance to drive rational drug combinations. Tier 2 analyses will integrate data between preclinical models and human tumors to enable effective translation of experimental findings to the clinic. Tier 3 analyses will integrate data across different cancer types to identify common and cancer type-specific protein signatures and networks. We will make our computational tools and analysis results publically available in two integrated proteogenomic data analysis systems, which will facilitate the collaborative identification of candidate biomarkers by all CPTAC investigators and will broaden the impact of the CPTAC program.