Bioinformatics-based analysis of amino acid metabolism-related features to predict clinical prognosis and immunotherapy response in triple-negative breast cancer

Abstract Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer associated with poor prognosis. In addition to the Warburg effect, amino acids and metabolites affect tumor development, are involved in modulating the tumor immune microenvironment (TME) and regulating the anti-tumor immune response. However, the relationship between amino acid metabolism and the clinical prognosis and immunotherapeutic response of triple negative breast cancer are still indistinct. We established a risk signature consisting of 12 genes by differential Analysis, univariate COX regression analysis and LASSO-COX analysis. The GEO cohort confirmed the validity of the risk signature. We used single-sample genomic enrichment analysis (ssGSEA), tumor mutation burden (TMB), and IC50 values of drugs to discover the relationship between the risk signature, immune status, and drug sensitivity in TNBC. We also verified the expression of the risk signature gene ALDH4A1 in tissues and cells by qPCR assay, and migration assay verified its role in TNBC cell invasion. Our study may provide new insights into amino acid metabolic therapy for the treatment of TNBC patients.