# Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2022 · $199,920

## Abstract

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.

## Key facts

- **NIH application ID:** 10380646
- **Project number:** 5R01CA245903-03
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Bing Zhang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $199,920
- **Award type:** 5
- **Project period:** 2020-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10380646

## Citation

> US National Institutes of Health, RePORTER application 10380646, Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma (5R01CA245903-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10380646. Licensed CC0.

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