Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer

Abstract

Keywords:Breast cancer Neoadjuvant chemotherapy Therapy response Metabolomics NMR LCeMS A B S T R A C TBreast cancer is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. As an example, only some women will benefit from chemotherapy. Identifying patients who will respond to chemotherapy and thereby improve their long-term survival has important implications to treatment protocols and outcomes, while identifying non responders may enable these patients to avail themselves of other investigational approaches or other potentially effective treatments. In this study, serum metabolite profiling was performed to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy for breast cancer. Metabolic profiles of serum from patients with complete (n ¼ 8), partial (n ¼ 14) and no response (n ¼ 6) to chemotherapy were studied using a combination of nuclear magnetic resonance (NMR) spectroscopy, liquid chromatographyemass spectrometry (LCeMS) and statistical analysis methods. The concentrations of four metabolites, three (threonine, isoleucine, glutamine) from NMR and one (linolenic acid) from LCeMS were significantly different when comparing response to chemotherapy. A prediction model developed by combining NMR and MS derived metabolites correctly identified 80% of the patients whose tumors did not show complete response to chemotherapy. These results show promise for larger studies that could result in more personalized treatment protocols for breast cancer patients.ª 2012 Federation of European Biochemical Societies.Published by Elsevier B.V. All rights reserved.Abbreviations: NMR, nuclear magnetic resonance; LCeMS, liquid chromatographyemass spectrometry; pCR, pathologic complete response; SD, stable disease; PR, partial response; PLS-DA, partial least squares discriminant analysis; ROC, receiver operating characteristic; CV, cross validation.

Metabolomics Biomarkers for Breast Cancer

“…This signature outperformed the diagnostic value of CA 27-29, for which data were available from the same samples. Another study from the same group [47] (Raftery and coworkers) analyzed a small set of 28 samples by NMR and LC-MS to predict responses of BC patients to NAC. The model predicts 80% of patients with tumors not showing response to chemotherapy and established four discriminatory metabolites: Thr, Ile, Glu and linolenic acid.…”

Exploring cancer metabolism using stable isotope-resolved metabolomics (SIRM)

“…For example, enhanced non-oxidative and oxidative PPP activity has been reported for pancreatic (23) and renal (40) cancers, respectively, using a [ novo serine biosynthesis may correlate with tumorigenic potential because the Glc to serine flux increases as cells become progressively more tumorigenic (41). Glc carbon may also be diverted from glycolysis for other anabolic purposes: dihydroxyacetone phosphate is a precursor for glycerol 3-phosphate used for glycerolipid synthesis (42), and fructose 6-phosphate (F6P) is the precursor for the hexosamine pathway critical for protein glycosylation and intracellular regulation (43,44). Collectively, these reactions indicate that in many proliferating cells the fraction of Glc consumed that is converted to lactate is much less than 100%.…”

Metabolomics for tumor marker discovery and identification based on chromatography–mass spectrometry

“…Three metabolites from NMR (threonine, iso leucine and glutamine) and one metabolite from LC-MS (linolenic acid) could classify 80% of the pathologic complete response patients [100]. These results are encouraging for the discovery of novel biomarkers to predict chemotherapeutic response and improve clinical treatments in the future.…”

“…In addition to clinical, gene and protein markers, metabolic biomarkers were also studied as predictors of pathologic complete response [100]. Three metabolites from NMR (threonine, iso leucine and glutamine) and one metabolite from LC-MS (linolenic acid) could classify 80% of the pathologic complete response patients [100].…”