Aim: To develop an approach to characterize and classify triple-negative breast cancer (TNBC) tumors based upon their essential amino acid (EAA) metabolic activity. Methods: We performed bioinformatic analyses of genomic, transcriptomic and clinical data in an integrated cohort of 740 TNBC patients from public databases. Results: Based on EAA metabolism-related gene expression patterns, two TNBC subtypes were identified with distinct prognoses and genomic alterations. Patients exhibiting an upregulated EAA metabolism phenotype were more prone to chemoresistance but also expressed higher levels of immune checkpoint genes and may be better candidates for immune checkpoint inhibitor therapy. Conclusion: Metabolic classification based upon EAA profiles offers a novel biological insight into previously established TNBC subtypes and advances current understanding of TNBC’s metabolic heterogeneity.
Cadaverine, a metabolite of the microbiome, reduces breast cancer aggressiveness through trace amino acid receptors
