Abstract
BACKGROUND: Immunotherapies including immune checkpoint inhibitors and tumor antigen based vaccines have revolutionized cancer treatment. However, immune signatures of hepatocellular carcinoma (HCC) have not been thoroughly studied from a multiomics perspective. AIMS: In this study, we aimed to identify the potential tumor antigens and immune subtyping for HCC using multiomics data. METHODS AND RESULTS: The study included 159 HCC patients with genome, transcriptome, proteome, and phosphoproteome data. Two potential tumor antigens, ZNF831 and SYNE1, showed significant superior prognostic effects and positive correlations with antigen presenting cells, which provided promising candidates for the development of tumor antigen-based mRNA vaccine. A multiomics clustering using the most variable tumor antigen genes of transcriptome, proteome, and phosphoproteome was performed, resulting in two HCC subtypes with distinct clinical and molecular features. In order to further explore the complex tumor microenvironment, we implemented an immune subtyping using 30 most important immune-related features generated from the random forest algorithm. Four immune subtypes were constructed, which exhibited diverse molecular attributes including immune cell activities, angiogenesis, cell proliferation, and the expression of tumor antigen genes, immune checkpoints, and immunogenic cell death modulators. CONCLUSION: In summary, we found two potential tumor antigens, ZNF831 and SYNE1, and identified four immune subtypes of HCC with distinct molecular features. Our study provides novel insights into the development of cancer vaccine and precision medicine of immune oncology in HCC, which may benefit clinical practice in the future.