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Int. J. Mol. Sci. 2018, 19(2), 617; https://doi.org/10.3390/ijms19020617

A Metabolomic Approach to Predict Breast Cancer Behavior and Chemotherapy Response

1
Hospital da Mulher Prof. Dr. José Aristodemo Pinotti—Centro de Atenção Integral à Saúde da Mulher (CAISM), University of Campinas (UNICAMP), Campinas, São Paulo 13083-881, Brazil
2
Clinical Pharmacology and Gastroenterology Unit, São Francisco University, Bragança Paulista, São Paulo 13083-881, Brazil
*
Author to whom correspondence should be addressed.
Received: 30 November 2017 / Revised: 29 January 2018 / Accepted: 31 January 2018 / Published: 21 February 2018
(This article belongs to the Special Issue Tumor Microenvironment)
Full-Text   |   PDF [714 KB, uploaded 21 February 2018]   |  

Abstract

Although the classification of breast carcinomas into molecular or immunohistochemical subtypes has contributed to a better categorization of women into different therapeutic regimens, breast cancer nevertheless still progresses or recurs in a remarkable number of patients. Identifying women who would benefit from chemotherapy could potentially increase treatment effectiveness, which has important implications for long-term survival. Metabolomic analyses of fluids and tissues from cancer patients improve our knowledge of the reprogramming of metabolic pathways involved in resistance to chemotherapy. This review evaluates how recent metabolomic approaches have contributed to understanding the relationship between breast cancer and the acquisition of resistance. We focus on the advantages and challenges of cancer treatment and the use of new strategies in clinical care, which helps us comprehend drug resistance and predict responses to treatment. View Full-Text
Keywords: breast cancer; drug resistance; metabolomics breast cancer; drug resistance; metabolomics
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Cardoso, M.R.; Santos, J.C.; Ribeiro, M.L.; Talarico, M.C.R.; Viana, L.R.; Derchain, S.F.M. A Metabolomic Approach to Predict Breast Cancer Behavior and Chemotherapy Response. Int. J. Mol. Sci. 2018, 19, 617.

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