{"database":"iProX","file_versions":[],"scores":null,"additional":{"omics_type":["Proteomics"],"submitter":["Xiaolong Liu"],"species":["Rattus Rattus"],"full_dataset_link":["http://www.iprox.org/page/project.html?id=IPX0010222000"],"submitter_email":["xiaolong.liu@gmail.com"],"submitter_affiliation":["The Liver Center of Fujian Province"],"sample_protocol":[""],"repository":["iProX"],"data_protocol":[""],"pubmed_abstract":["<h4>Background & aims</h4>Tumor neoantigens, especially cryptic antigens from non-canonical translation, are vital for cancer immunotherapy. Mass spectrometry (MS)-based de novo sequencing identifies candidates, but unverified immunogenicity and antitumor efficacy limit clinical applicability. This study aimed to identify novel non-canonical neoantigens in hepatocellular carcinoma (HCC) using MS-based de novo sequencing and rigorously validate their immunogenicity and antitumor efficacy.<h4>Methods</h4>Using a C57BL/6 subcutaneous HCC mouse model, immunopeptides were comprehensively profiled via MHC-I immunoprecipitation combined with MS-based de novo sequencing. Identified high-immunogenicity peptides predicted by deep learning were validated using ex vivo ELISpot assays. Endogenous peptide expression was confirmed using parallel reaction monitoring-targeted quantification. The antitumor efficacy of therapeutic peptide vaccines comprising the seven most immunogenic peptides combined with the adjuvant poly(I:C) was evaluated in vivo in the subcutaneous and orthotopic HCC models.<h4>Results</h4>We identified 5,576 immunopeptides, with sequence motifs consistent with prior reports. Remarkably, 95% of deep learning-predicted high-immunogenicity peptides were successfully validated by ELISpot (p <0.05). Parallel reaction monitoring confirmed endogenous expression of these peptides. Most significantly, the peptide vaccines (7 peptides + poly(I:C)) demonstrated potent antitumor efficacy in vivo compared to controls (p <0.05).<h4>Conclusions</h4>MS-based de novo sequencing combined with computational prioritization enables identification of non-canonical, immunogenic neoantigens in HCC. Selected peptides demonstrated endogenous presentation and measurable antitumor activity in preclinical models.<h4>Impact and implications</h4>This study provides robust experimental validation that mass spectrometry-based de novo sequencing effectively identifies novel, highly immunogenic non-canonical neoantigens in hepatocellular carcinoma, overcoming a key limitation of prior predictive methods and opening avenues for exploring this understudied neoantigen class in other cancers. The findings are critical for cancer immunologists and oncologists developing next-generation immunotherapies, demonstrating a viable discovery-to-validation pipeline for novel therapeutic targets. The validated neoantigens and successful peptide vaccine strategy offer a direct pathway towards developing personalized hepatocellular carcinoma immunotherapies, enabling clinicians to adopt similar integrated approaches for patient-specific neoantigen discovery; however, clinical translation beyond this preclinical murine model requires confirmation in human settings due to potential differences in HLA presentation and the tumor microenvironment."],"pubmed_title":["Mass spectrometry-based de novo sequencing reveals non-canonical neoantigens with antitumor efficacy in hepatocellular carcinoma."],"pubmed_authors":["Xing Xiaohua X, Liu Mingxin M, Ouyang Jiahe J, Tang Yaxin Y, Shan Baozhen B, Tang Ruijing R, Hu En E, Li Ming M, Liu Xiaolong X"],"additional_accession":[]},"is_claimable":false,"name":"Neoantigen Discovery and Validation in Hepatocellular Carcinoma: Unveiling Immunogenic Targets Through Mass Spectrometry","description":"The accurate identification of tumor neoantigens, particularly cryptic antigens from non-canonical translation, is crucial for developing effective cancer immunotherapies. However, the significance and action of cryptic antigens in anti-tumour immunity remain unclear. In this study, we utilized a highly sensitive mass spectrometry-based de novo sequencing approach to identify non-canonical MHC-binding immunopeptides and evaluate the anti-tumor immune effects of vaccines composed of these peptides in Hepatocellular carcinoma (HCC).","dates":{"publication":"Fri Jul 25 00:00:00 BST 2025"},"accession":"PXD079354","cross_references":{"TAXONOMY":["10117"],"pubmed":["41861674"]}}