Project Summary Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide, and therapeutic options are limited. There is a pressing need to fully understand the molecular mechanisms underlying the disease in order to identify new effective biomarkers, drug targets, and therapeutic agents for the prognosis and treatment of HCC. Proteins are the functional molecules of the cell, and many clinically validated biomarkers and most drug targets are proteins; however, cancer omics studies have relied primarily on genomic platforms. By melding genomics with mass spectrometry (MS)-based proteomics, the new field of proteogenomics provides an opportunity to more completely understand how somatic genomes activate aberrant protein networks that drive cancer pathogenesis. A major National Cancer Institute (NCI)-funded initiative, the Clinical Proteomics Tumor Analysis Consortium (CPTAC), and the more recently established International Cancer Proteogenome Consortium (ICPC), are promoting an integrated proteogenomics approach that is postulated to produce sounder therapeutic hypotheses and a new generation of protein biomarkers. The central purpose of this application is to forge a collaboration between a CPTAC team in the US and an ICPC team in China to enable proteogenomics-driven therapeutic discoveries in hepatitis B virus-related (HBV+) HCC, which attributes to 85% of HCC cases in China. The two teams bring complementary expertise required for a successful proteogenomic study of HCC. The China team has already generated the most comprehensive multi-omics dataset yet produced for liver cancer by applying proteogenomic profiling to a Chinese HBV+ HCC cohort (CHCC-HBV) with 159 cases, and the data has been preliminarily analyzed through collaborative efforts between the two teams. In this application, the US team will perform deep computational analyses of the proteogenomics data to generate prognostic models and therapeutic hypotheses, which will be experimentally validated in cell lines, animal models, and clinical specimens by the China team. Our specific Aims are: Aim 1) To develop and validate a protein-based prognostic model; Aim 2) To identify and validate subtype-specific causal drivers and therapeutic strategies; and Aim 3) To characterize the immune landscape of HBV+ HCC. Successful completion of this project will lead to new knowledge on HCC biology as well as new prognostic and treatment strategies for HBV+ HCC. Meanwhile, experimentally validated computational methods developed in this project will have wide application to the study of other cancers and other non-cancer diseases.