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Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients

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Abstract

Introduction

Breast cancer is the most diagnosed tumor and the leading cause of cancer death in women worldwide. Metabolomics allows the quantification of the entire set of metabolites in blood samples, making it possible to study differential metabolomics patterns related to neoadjuvant treatment in the breast cancer neoadjuvant setting.

Objectives

Characterizing metabolic differences in breast cancer blood samples according to their response to neoadjuvant treatment.

Methods

One hundred and three plasma samples of breast cancer patients, before receiving neoadjuvant treatment, were analyzed through UPLC-MS/MS metabolomics. Then, metabolomics data were analyzed using probabilistic graphical models and biostatistics methods.

Results

Metabolomics data allowed the identification of differences between groups according to response to neoadjuvant treatment. These differences were specific to each breast cancer subtype. Patients with HER2+ tumors showed differences in metabolites related to amino acids and carbohydrates pathways between the two pathological response groups. However, patients with triple-negative tumors showed differences in metabolites related to the long-chain fatty acids pathway. Patients with Luminal B tumors showed differences in metabolites related to acylcarnitine pathways.

Conclusions

It is possible to identify differential metabolomics patterns between complete and partial responses to neoadjuvant therapy, being this metabolomic profile specific for each breast cancer subtype.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We are especially grateful to all the patients and their families who contributed the data that made this study possible.

Funding

This study was supported by Instituto de Salud Carlos III, Spanish Economy, and Competitiveness Ministry, Spain, and co-funded by the FEDER program, “Una forma de hacer Europa” (PI15/01310), Fundación Bancaria Unicaja. Grant Number: ONCOCHJ-UNICAJA-P1 and an unrestricted grant from Roche Farma. The funders had no role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript. AZ-M and MIL-H are supported by Consejería de Educación, Juventud y Deporte of Comunidad de Madrid (IND2018/BMD-9262). EL-C is supported by the Spanish Economy and Competitiveness Ministry (PTQ2018-009760).

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Authors and Affiliations

  1. Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain

    Andrea Zapater-Moros, Angelo Gámez-Pozo, Lucía Trilla-Fuertes, María Isabel Lumbreras-Herrera & Juan Ángel Fresno Vara

  2. Biomedica Molecular Medicine SL, C/Faraday 7, 28049, Madrid, Spain

    Andrea Zapater-Moros, Angelo Gámez-Pozo, Elena López-Camacho & Juan Ángel Fresno Vara

  3. Systems Biology Unit, Department of Experimental Biology, University of Jaén, Campus Las Lagunillas s/n, 23071, Jaén, Spain

    Leticia Díaz-Beltrán

  4. Medical Oncology Service, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain

    Enrique Espinosa & Pilar Zamora

  5. Medical Oncology Department, Hospital Universitario de Jaén, Av. del Ejército Español, 10, 23007, Jaén, Spain

    Leticia Díaz-Beltrán, Carmen González-Olmedo & Pedro Sánchez-Rovira

  6. Biomedical Research Networking Center On Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain

    Andrea Zapater-Moros, Enrique Espinosa, Pilar Zamora & Juan Ángel Fresno Vara

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  1. Andrea Zapater-Moros
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  2. Leticia Díaz-Beltrán
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Contributions

All the authors have directly participated in the preparation of this manuscript and have approved the final version submitted. LD-B carried out sampling management. LD-B and CG-O performed data curation. LT-F, AG-P, AZ-M, EL-C, and MIH-L performed the statistical analyses, the graphical model interpretation, and the ontology analyses. AZ-M, AG-P, JAFV, PZ, JAF and PSR conceived the study and participated in its design and interpretation. AZ-M drafted the manuscript. AG-P, JAFV, LD-B, and CG-O supported the manuscript drafting. JAFV, PZ and PS-R participated in funding acquisition and study supervision. AG-P and JAFV coordinated the study.

Corresponding author

Correspondence to Juan Ángel Fresno Vara.

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Conflict of interest

JAFV, EE, and AG-P are shareholders in Biomedica Molecular Medicine SL. AZ-M and EL-C are employees of Biomedica Molecular Medicine SL.

Ethical approval

The study was approved by the Institutional Review Board of the Clinical Research Ethics Committee of Jaén (protocol code: PI-0455-2016 and date of approval: 27 October 2016). Clinical research was conducted under the Declaration of Helsinki and the International Conference on Harmonisation-Good Clinical Practice (ICH-GCP) guidelines. Written informed consent for participation was obtained from all patients involved in the study before blood sampling.

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Zapater-Moros, A., Díaz-Beltrán, L., Gámez-Pozo, A. et al. Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients. Metabolomics 19, 60 (2023). https://doi.org/10.1007/s11306-023-02024-8

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