Identification and validation of synergistic drug strategies targeting macrophage polarization in triple-negative breast cancer via single-cell transcriptomics and deep learning.

ABSTRACT: Triple-negative breast cancer (TNBC) presents therapeutic challenges due to its immunosuppressive tumor microenvironment (TME) and limited targeted options. Analyzing scRNA-seq data from 24 TNBC patients using integrated transcriptomics, machine-learning, and pseudo-time trajectory mapping, we developed a macrophage differentiation-based classifier (MMDCSS) (CD93, CHI3L1, ZBTB20) with remarkable prognostic accuracy (C-index: 0.929, 3-year AUC: 0.907). Computational pharmacology identified finasteride as a ZBTB20 modulator (binding energy:7.7 kcal/mol) capable of reversing tumor-induced M2 macrophage polarization. Finasteride significantly enhanced doxorubicin efficacy ex vivo and in vivo by reprogramming the TME, reducing M2 macrophage infiltration while promoting an M1 phenotype. Mechanis

SUBMITTER: Qi Q 

PROVIDER: S-EPMC12268103 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature