Decoding neoantigen-encoding tumor-specific transcripts unveils a shared target reservoir for immunotherapy in...

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Hepatocellular carcinoma (HCC) presents limited therapeutic options, with existing neoantigen vaccines hampered by low antigen availability.
• This study investigates transcriptome-derived neoantigens (neoTSTs) as a potential solution for HCC immunotherapy.

Purpose of the Study:

• To characterize the features, generation mechanisms, and therapeutic potential of neoTSTs in HCC.
• To compare neoTSTs with mutation-derived neoantigens (neoMuts) in terms of abundance, frequency, and immunotherapeutic efficacy.

Main Methods:

• Developed a computational pipeline to identify tumor-specific transcripts (TSTs) and predict neoTSTs from RNA-seq data of 1,013 HCC patients.
• Validated neoTSTs using proteomics, immunopeptidomics, and HLA-transgenic mouse models.
• Assessed neoTST tumor coverage and immunotherapeutic efficacy using single-cell RNA-seq and murine HCC models.

Main Results:

• Identified an average of 60 neoTSTs per patient, significantly more than neoMuts, with high population frequencies and validation via mass spectrometry.
• Discovered neoTST generation mechanisms including retained introns, transposable element activation, and alternative promoter usage.
• Demonstrated that neoTSTs cover >75% of tumor cells, are amplified by antigen-presenting cancer-associated fibroblasts, and outperform neoMuts in preclinical HCC models.

Conclusions:

• NeoTSTs represent a superior and more abundant neoantigen source in HCC compared to neoMuts.
• NeoTSTs hold dual potential as personalized immunotherapeutic targets and broadly applicable antigens for low-TMB tumors.
• These findings offer a transformative framework for advancing HCC immunotherapy.