AUTHOR=He Xiangming , Gu Jinping , Zou Dehong , Yang Hongjian , Zhang Yongfang , Ding Yuqing , Teng Lisong 

TITLE=NMR-Based Metabolomics Analysis Predicts Response to Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 8 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2021.708052

DOI=10.3389/fmolb.2021.708052

ISSN=2296-889X

ABSTRACT=Triple-negative breast cancer (TNBC) is the most fatal breed in breast cancer (BC). Due to the lack of relevant targeted therapy targets, in addition to surgery, chemotherapy is still the most common treatment option for TNBC. TNBC is heterogeneous, and different patients have different sensitivity to chemotherapy. Only some patients will benefit from chemotherapy, so the neoadjuvant chemotherapy is controversial in the treatment of TNBC. Here, we performed nuclear magnetic resonance (NMR)-based metabolomics study to analyze the relationship between the patients’ metabolic phenotypes and chemotherapy sensitivity in the serum samples. Metabolic phenotypes from patients with pathological partial, complete response and pathological stable disease could be distinguished. Furthermore, we conducted metabolic pathway analysis based on identified significant metabolites, and revealed significantly disturbed metabolic pathways closely associated three groups of TNBC patients. We evaluated the discriminative ability of metabolites related to significantly disturbed metabolic pathways by using the multi-receiver operating characteristic (ROC) curve analysis. Three significantly disturbed metabolic pathways of glycine, serine and threonine metabolism, valine, leucine, and isoleucine biosynthesis and alanine, aspartate and glutamate metabolism could be used as potential predictive models to distinguish three types of TNBC patients. These results suggest that metabolic phenotype could be used in TNBC patients whether neoadjuvant chemotherapy. Metabolomics research could provide data support of metabolic phenotype for personalized treatment of TNBC.