Discovery and Validation of Non-canonical Antigens for Hepatocellular Carcinoma Immunotherapy.

Authors

Stephen Li, Yujuan Dong, Jiaxun Liu, Shanglin Li, Dandan Pu, Yue Guo, Chun Kwok Wong, Nathalie Wong, Jason Wing Hon Wong

Published in

Genomics, proteomics & bioinformatics. Aug 13, 2026. Epub Aug 13, 2026.

Abstract

Hepatocellular carcinoma (HCC) is a highly prevalent and lethal form of liver cancer marked by high rates of tumor recurrence, posing substantial challenges to primary treatment options such as surgical resection and liver transplantation. Immunotherapy, which leverages T-cell-mediated recognition of tumor-specific antigens, has emerged as a promising alternative therapeutic strategy. While proteogenomics and ribosome profiling data across cancer types have provided growing evidence of active translation in non-canonical open reading frames (ncORFs), antigens derived from HCC-associated ncORFs remain largely unexplored. By integrating long-read and short-read RNA sequencing data with mass spectrometry, we have successfully identified twelve non-canonical peptides arising from cryptic translation of ncORFs. Enzyme-linked immunosorbent spot (ELISpot) assays confirmed cytokine release triggered by non-canonical peptides originating from distinct genomic loci. Subsequent RNA level analysis revealed four peptides with strong evidence of enriched expression in tumorigenesis. In-depth bioinformatics predictions indicate that these four peptides possess significant binding affinity for Major Histocompatibility Complex and T-Cell Receptor, with p2 emerging as the most promising candidate. Analysis using public datasets and experimental validation further highlighted the role of ribosome subunit recruitment and N6-Methyladenosine (m6A) modifications in enhancing translation initiation for tumor-enriched antigens. By addressing the existing shortage of knowledge in the HCC ncORF translation, this study identifies promising antigenic candidates for HCC immunotherapy, offering new avenues for effective treatment strategies and improved patient outcomes.

PMID:
42596573
Bibliographic data and abstract were imported from PubMed on 14 Aug 2026.

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