Transcriptomics and mutational analysis to screen immunogenic neoantigen peptides and Patient stratification based on immune subtypes for TNBC

Abstract Triple-negative breast cancer (TNBC) is a highly aggressive and heterogeneous subtype with limited therapeutic options. In this study, we performed an integrative analysis of TNBC genomics data, including gene expression, somatic mutations, copy number alterations, survival outcomes, immune profiling, and clustering, to identify potential neoantigens, patient populations suitable for vaccination, and biomarkers for evaluating vaccine efficacy. This Integrated analysis identified POSTN and CAP1 as tumor-specific antigens. Incorporation of TNBC-specific mutations into the screened wild-type antigens led to the identification of three neoantigenic peptides with high potential for vaccine development. Immune subtyping stratified TNBC patients into four distinct subtypes, among which IS1 and IS3 were characterized by poor immune infiltration, lower mutation burden, and unfavorable prognosis, whereas IS2 and IS4 exhibited enhanced immune activity and better clinical outcomes. A vaccine incorporating the identified neoantigen peptides may potentially remodel the immune landscape of immune-cold subtypes (IS1 and IS3), converting them into immune-enriched phenotypes through vaccine-induced immune stimulation. Furthermore, weighted gene co-expression network analysis identified ten immune-related biomarkers from the blue and gray modules that were significantly associated with improved survival in IS2 and IS4. Functional enrichment and protein–protein interaction analyses revealed that hub genes primarily involved in immunoglobulin kappa chains and cytokine/TNF signaling pathways may serve as valuable immune biomarkers for prognostic assessment and monitoring vaccine efficacy. Competing Interest Statement The authors have declared no competing interest. Data availability All data generated or analyzed during this study are included in this article and supplementary materials.