A prognostic model for basal-like breast cancer based on beta-alanine metabolism genes: EHHADH as a potential biomarker and target for drug screening.

Background: The high heterogeneity of basal-like breast cancer (BLBC) impedes early diagnosis and accurate prognosis. Beta-alanine, a non-essential amino acid involved in various metabolic pathways, accumulates in BLBC cells and may exacerbate tumor progression.

Objective: This study aimed to develop a prognostic model based on beta-alanine metabolism genes and investigate the clinical significance and therapeutic potential of EHHADH in BLBC.

Methods: We applied Least Absolute Shrinkage and Selection Operator regression to 22 beta-alanine metabolism genes to construct a prognostic model using transcriptomic data. Subsequent analyses included overall survival, mutation landscape, functional enrichment, drug sensitivity, and in vitro validation of EHHADH function. Structure-based virtual screening was conducted to identify potential EHHADH inhibitors.

Results: A beta-alanine metabolism-related prognostic signature was successfully developed. EHHADH was identified as a risk gene negatively associated with survival. High EHHADH expression correlated with increased sensitivity to chemotherapeutic agents, including docetaxel, doxorubicin, gemcitabine, paclitaxel, tamoxifen, and vinorelbine. Knockdown of EHHADH reduced BLBC cell proliferation and migration. Virtual screening revealed several candidate small molecules targeting EHHADH.

Conclusion: This study establishes a prognostic model based on beta-alanine metabolism in BLBC and identifies EHHADH as a potential biomarker and drug target, providing insights for precision therapy in metabolically reprogrammed breast cancer.