ArticleMolecular biomedicine2025
Single-cell RNA sequencing identifies CD8Teff cell activation as a predictive biomarker in triple-negative breast cancer immunotherapy.
Article in Molecular biomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- The role of KIAA1467 in breast cancer: insights from pan-cancer and single-cell sequencing analysis.Translational cancer research · 2026Article
- The chemokine network in triple-negative breast cancer: its role in immune microenvironment regulation, and prospects for targeted therapy.Frontiers in immunology · 2026Review
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Authors and funding
16 authors.
Funding
Abstract
Immunotherapy has emerged as a promising treatment option for triple-negative breast cancer (TNBC); however, the pronounced heterogeneity of the tumor immune microenvironment significantly hinders the prediction of therapeutic efficacy, with effective biomarkers also remaining limited. This study utilizes single-cell RNA sequencing (scRNA-seq) and transcriptome analysis to dissect the immune landscapes of TNBC, emphasizing CD8 effector T cells (CD8Teff) as potential predictors of immune checkpoint inhibitors (ICIs) treatment response. Immune profiling revealed that CD8Teff cells were predominantly enriched in "hot" tumors strongly correlating with improved progression-free and overall survival. Notably, the cytokine C-X-C Motif Chemokine Ligand 13 (CXCL13) emerged as a key regulator, with its high expression marking an immune-active tumor microenvironment favorable to ICI efficacy. Comprehensive analysis uncovered critical interactions between CD8Teff cells and other immune and stromal components, supporting the formation of an immunologically active tumor microenvironment (TME) conducive to tumor control. Additionally, metabolic reprogramming of CD8Teff cells in responsive tumors highlighted pathways that may influence ICIs efficacy. CD8Teff cells significantly influence the TME and predict ICI success in TNBC, with CXCL13 as a pivotal modulator. A pathology-based artificial intelligence model for CD8Teff recognition was developed, achieving an area under the curve (AUC) of 0.823 in the training cohort and 0.805 in the validation cohort. This study provides an in-depth characterization of the TNBC immune microenvironment, identifying CD8Teff functionality, CXCL13 signaling, and immune-metabolic pathways as critical determinants of immunotherapy success. These findings support the development of personalized treatment strategies based on immune profiling to enhance therapeutic efficacy in TNBC.
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