双向蛋白质基因组学识别三阴性乳腺癌中肿瘤特异性、免疫可见的肽段用于免疫治疗开发

Introduction: Triple-negative breast cancer (TNBC) is an aggressive disease with limited treatment options. Despite its frequently inflamed tumor microenvironment, TNBC exhibits poor and inconsistent responses to immunotherapy, highlighting the need for alternative strategies, such as TCR-based therapy and cancer vaccines. These approaches depend on robust identification of HLA-presented, tumor-specific peptides that are visible to the immune system. To address this need, we applied immunopeptidomics together with a new proteogenomic integration framework to a panel of TNBC cell lines to establish a foundation for a comprehensive antigen resource to support peptide-based immunotherapy development. Methods: Five TNBC cell lines were profiled with and without IFN-gamma stimulation. Whole-genome sequencing, whole-exome sequencing, RNA-seq, Ribo-seq, and immunopeptidomic data were jointly analyzed using NeoFlow2, a next-generation two-way proteogenomics framework. In addition to the conventional forward approach, in which genomic and transcriptomic data inform proteogenomic database searches, NeoFlow2 introduces a reverse direction by mapping de novo-sequenced peptides back to the transcriptome to reveal unannotated translation events. NeoFlow2 further assesses tumor specificity using PepQueryMHC, which evaluates peptide-level transcript support in tumor versus normal RNA-seq data across TCGA and GTEx cohorts. Results: NeoFlow2 revealed a markedly expanded repertoire of both canonical and non-canonical peptides across the profiled TNBC cell lines, with IFN-gamma stimulation further enhancing antigen diversity. Among these, the pipeline identified hundreds of non-reference peptides arising from diverse genomic and transcriptomic origins, including missense mutations, frameshifts, alternative splicing, UTRs, intron retention, non-coding RNAs, and alternative ORFs. Leveraging TCGA and GTEx datasets, we prioritized peptides presented in TNBC tumors but absent from normal tissues, yielding a focused set of TNBC-specific antigens with strong immunotherapeutic potential. Conclusions: NeoFlow2 provides an effective framework for integrating multi-omics and immunopeptidomic data to systematically identify canonical and non-canonical tumor antigens. In TNBC cell lines, this framework revealed a set of TNBC-specific antigens with potential relevance for peptide-based cancer immunotherapy.