Integrated omics landscape of hepatocellular carcinoma suggests proteomic subtypes for precision therapy

Cell Rep Med. 2023 Dec 19;4(12):101315. doi: 10.1016/j.xcrm.2023.101315. Epub 2023 Dec 12.

Abstract

Patients with hepatocellular carcinoma (HCC) at the same clinical stage can have extremely different prognoses, and molecular subtyping provides an opportunity for individualized precision treatment. In this study, genomic, transcriptomic, proteomic, and phosphoproteomic profiling of primary tumor tissues and paired para-tumor tissues from HCC patients (N = 160) are integrated. Proteomic profiling identifies three HCC subtypes with different clinical prognosis, which are validated in three publicly available external validation sets. A simplified panel of nine proteins associated with metabolic reprogramming is further identified as a potential subtype-specific biomarker for clinical application. Multi-omics analysis further reveals that three proteomic subtypes have significant differences in genetic alterations, microenvironment dysregulation, kinase-substrate regulatory networks, and therapeutic responses. Patient-derived cell-based drug tests (N = 26) show personalized responses for sorafenib in three proteomic subtypes, which can be predicted by a machine-learning response prediction model. Overall, this study provides a valuable resource for better understanding of HCC subtypes for precision clinical therapy.

Keywords: Sorafenib; hepatocellular carcinoma; machine learning; multi-omics; precision therapy; proteomic subtypes; response prediction model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Carcinoma, Hepatocellular* / drug therapy
  • Carcinoma, Hepatocellular* / genetics
  • Humans
  • Liver Neoplasms* / drug therapy
  • Liver Neoplasms* / genetics
  • Liver Neoplasms* / pathology
  • Multiomics
  • Proteomics
  • Tumor Microenvironment / genetics

Substances

  • Biomarkers, Tumor