{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T07:01:24Z","timestamp":1775804484959,"version":"3.50.1"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:00:00Z","timestamp":1775779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Triple-negative breast cancer (TNBC) is an aggressive subtype with high malignancy and poor prognosis. Immunotherapy is a promising treatment for TNBC patient. Although T cell-mediated tumor killing related genes (TTKRGs) play critical roles in antitumor immunity, their prognostic value and potential function in TNBC is still unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Transcriptomic data from TCGA-BRCA and TTKRGs were curated to determine the prognostic genes in TNBC and a prognostic model was further established. GSE135565 dataset was used to validate the prognostic model. Furthermore, the differences between risk groups were compared through ESTIMATE, clinical correlation, drug sensitivity, immune checkpoint, tumor microenvironment. GSEA and GeneMANIA analysis were performed to explore the potential mechanism.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Intersection of 1,933 differentially expressed genes (DEGs) and 1,109 TTKRGs yielded 88 candidate genes, and PODN, SEMA7A, GPR34, and COCH were identified as prognostic genes for TNBC. A prognostic model was further successfully established and validated. The model exhibited good predictive performance in both training and validating sets with AUC values all above 0.6. Our studies confirmed the pathological stages were associated with risk scores and there were significant differences in the drug sensitivity, immune checkpoint expression, and tumor microenvironment among different risk groups. The two groups were enriched in pathways of cell cycle and immune regulation and the four prognostic genes were associated with transcription factors such as SP1, MYC, and CTCF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We constructed a robust prognostic model based on four T cell-mediated tumor killing (TTK)-related genes. Beyond predicting survival, this signature effectively decodes the immunosuppressive tumor microenvironment (TME) in TNBC, characterized by stromal activation, M2 macrophage polarization, and T cell exhaustion. These findings highlight novel immune evasion mechanisms and provide a theoretical foundation for targeting next-generation immune checkpoints and specific stromal-immune crosstalk in TNBC immunotherapy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1801004","type":"journal-article","created":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T06:06:17Z","timestamp":1775801177000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Comprehensive analysis of prognostic characteristics based on T cell-mediated tumor killing related genes in triple negative breast cancer"],"prefix":"10.3389","volume":"17","author":[{"given":"Chenyu","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Breast Surgery, Xinhua Hospital Affiliated of Shanghai Jiaotong University School of Medicine","place":["Shanghai, China"]},{"name":"Research Center of Breast Tumor Intelligent Diagnosis and 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