AccScience Publishing / EJMO / Online First / DOI: 10.36922/EJMO025480497
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ORIGINAL RESEARCH ARTICLE

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

Jinping Gu1 ,  Tingxiao Zou1 ,  Yao Gao1 ,  Ziyi Jiang1 ,  Feng Su1 ,  Xiangming He2*
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1 College of Pharmaceutical Sciences, Key Laboratory for Green Pharmaceutical Technologies and Related Equipment of Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang, China
2 Department of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
EJMO, 025480497 https://doi.org/10.36922/EJMO025480497
Received: 30 November 2025 | Revised: 10 March 2026 | Accepted: 6 May 2026 | Published online: 20 May 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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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.

Graphical abstract
Keywords
Triple-negative breast cancer
Nuclear magnetic resonance
Neoadjuvant chemotherapy
Metabolic phenotype
Metabolomics
Funding
This work was supported by the Zhejiang Provincial Medicine and Health Science Fund (2020KY482 and 2022KY632).
Conflict of interest
The authors declare no competing financial interest.
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Eurasian Journal of Medicine and Oncology, Electronic ISSN: 2587-196X Print ISSN: 2587-2400, Published by AccScience Publishing
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