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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. 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The research methodology was granted ethical approval by the ethics panel at Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China (No. SYSKY-2024\u2013750-01). Informed consent was obtained from all individual participants included in the study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"All authors declare that they have no competing interests. Authors Zehua Wang and Ruichong Lin are employed by UMedEVO and UMedREVO Artificial Intelligence Technology Co., respectively; however, they have no relevant financial or non-financial interests to disclose. The remaining authors declare no conflicts of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"66"}}