Prediction of response to neoadjuvant chemotherapy for triple-negative breast cancer using nuclear magnetic resonance-based urine metabolomics and self-organizing maps

Abstract

Introduction: Breast cancer constitutes the most common invasive neoplasm among women, with triple-negative breast cancer (TNBC) representing 10-20% of all cases and lacking a standardized therapeutic approach. Chemotherapy remains the cornerstone of treatment for TNBC patients.

Objective: Our research aimed to identify urinary metabolomic biomarkers capable of discerning chemotherapeutic response variability.

Methods: In this study, we utilized a nuclear magnetic resonance (NMR)-based urinary metabolomics technique to evaluate the metabolic profiles of TNBC patients exhibiting diverse chemotherapeutic responses.

Results: We found that the relative abundance of urinary metabolites effectively differentiated TNBC patients based on chemosensitivity. Multivariate receiver operating characteristic curve analysis indicated potential biomarkers indicative of chemotherapy responsiveness across three patient cohorts. Pathway analysis suggested perturbations in aminoacyl-tRNA biosynthesis; arginine, aspartate, and glutamate metabolism; and valine, leucine, and isoleucine biosynthesis in the pCR subgroup, and in arginine and proline metabolism, aminoacyl-tRNA biosynthesis, and histidine metabolism in the pathological partial response subgroup.

Conclusion: Our NMR metabolomic data suggest that urinary metabolites hold potential as predictors of chemotherapy sensitivity in TNBC patients.

Keywords

Triple-negative breast cancer / Nuclear magnetic resonance / Neoadjuvant chemotherapy / Metabolic phenotype / Metabolomics

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