The luminal androgen receptor (LAR) subtype of triple-negative breast cancer (TNBC) differentiation displays low proliferation yet strong metastatic potential and a poor chemotherapy response. This study aimed to define the molecular basis of the LAR subtype and identify actionable therapeutic targets.

Comprehensive multi-omic analyses were performed on the FUSCC-TNBC cohort, integrating whole-exome sequencing, RNA sequencing, and functional validation in vitro and in vivo. Somatic mutation profiling, gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA) were used to define genomic and transcriptomic signatures. A machine learning model using the Mime1 package was applied to derive a senescence-associated prognostic signature (LAR-S) and validation in external cohorts. Immune deconvolution was performed to decipher the tumor microenvironment. Functional assays, patient-derived organoids (PDOs), and TS/V mouse models were used to evaluate therapeutic responses to senescence-modulating agent and immunotherapy combinations.

The LAR subtype was enriched for PIK3CA, PTEN, and ERBB2 kinase domain mutations. Functional studies confirmed ERBB2 variants (e.g., V777L and E698_P699delinsA) as oncogenic drivers conferring sensitivity to neratinib. Transcriptomic analyses revealed a dominant cellular senescence program associated with immune suppression. The LAR-S signature stratified survival across cohorts and predicted immunotherapy resistance. Targeting cellular senescence inhibited LAR subtype organoid growth and when combined with anti-PD-1 therapy synergistically suppressed tumor growth in vivo.

The LAR subtype harbors two therapeutic vulnerabilities: ERBB2 mutation-driven kinase activation; and senescence-mediated immune evasion. The LAR-S signature enables precise patient stratification and supports senescence-targeted and immunotherapy combination strategies as promising approaches for this refractory TNBC subtype.