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.
Keywords: PD-1; TNBC; bioinformatics; chemoresistance; classification; epigenomics; essential amino acid; immunotherapy; metabolic heterogeneity; prognosis.
Lay abstract Breast cancer is the most common malignancy in women. Triple-negative breast cancer (TNBC) is a highly malignant subtype of breast cancer, accounting for about 12–17% of total breast cancer cases. This subtype is prone to liver and bone metastases, has a high risk of recurrence and carries a poor prognosis. In this study the authors explored the essential amino acid metabolism characteristics of TNBC tumors. They found that TNBC tumors exhibiting high essential amino acid metabolism were more malignant, associated with a worse prognosis and less sensitive to chemotherapy, but were also associated with better patient responses to immunotherapy. These results offer new insights into the precision treatment of TNBC. The results of the study are promising but require additional investigation.