Evidence map›Paper›PMID 42039207›Full record

ArticleFrontiers in immunology2026

Comprehensive analysis of prognostic characteristics based on T cell-mediated tumor killing related genes in triple negative breast cancer.

Chenyu Zhang, Yanmin Hu, Yongming Han, Peipei Zhao, Baosan Han, Xingjie Hu

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Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Chenyu Zhang *Department of Breast Surgery, Xinhua Hospital Affiliated of Shanghai Jiaotong University School of Medicine, Shanghai, China.
Yanmin Hu *Department of Gerontology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yongming HanState Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Peipei ZhaoDepartment of Breast Surgery, Xinhua Hospital Affiliated of Shanghai Jiaotong University School of Medicine, Shanghai, China.
Baosan HanDepartment of Breast Surgery, Xinhua Hospital Affiliated of Shanghai Jiaotong University School of Medicine, Shanghai, China.
Xingjie HuDepartment of Breast Surgery, Xinhua Hospital Affiliated of Shanghai Jiaotong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Indexed as

Biomarkers, TumorT-LymphocytesTriple Negative Breast NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTranscriptomeTumor MicroenvironmentBiomarkers, Tumorgene set enrichment analysisimmune microenvironmentprognostic modelT cell-mediated tumor killingtriple-negative breast cancer

Identifiers

PMID42039207
PMCPMC13106453

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