EXCLI J EXCLI Journal 1611-2156 Leibniz Research Centre for Working Environment and Human Factors 2017-1045 10.17179/excli2017-1045 Doc1328 Editorial material Highlight report: Intratumoral metabolomic heterogeneity of breast cancer Stoeber Regina * 1 IfADo - Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund, Ardeystr. 67, D-44139 Dortmund, Germany *To whom correspondence should be addressed: Regina Stoeber, IfADo - Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund, Ardeystr. 67, D-44139 Dortmund, Germany, E-mail: stoeber@ifado.de 22 12 2017 2017 16 1328 1329 17 12 2017 21 12 2017 Copyright © 2017 Stoeber 2017

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/4.0/) You are free to copy, distribute and transmit the work, provided the original author and source are credited.

This article is available from http://www.excli.de/vol16/Stoeber_Editorial_22122017_proof.pdf


Recently, Mikheil Gogiashvili and colleagues from TU-Dortmund have published a study about the metabolomics heterogeneity of breast cancer (Gogiashvili et al., 2017[8]). The background of this study is the practically relevant question, whether measurement of a single biopsy is sufficient when analyzing tumors from a cohort of patients. In recent years metabolic profiling by high-resolution magic angle spinning nuclear magnetic resonance spectroscopy has been increasingly used to characterize the metabolome of breast cancer (Sitter et al., 2010[19]; Giskeodegard et al., 2012[7]; Cao et al., 2012[3]; Choi et al., 2012[4]; 2013[5]). However, so far only a single study has addressed the possible influence of metabolic heterogeneity within a single breast tumor (Park et al., 2016[17]). Therefore, the authors performed multi-core sampling of six small specimens from individual tumors and quantified 32 metabolites. Not unexpectedly, the intertumoral differences were larger compared to intratumoral differences (Gogiashvili et al., 2017[8]). More importantly, a random forest- classifier trained on a sample set of individual tumors correctly predicted tumor identity of an additional set of independent cores from the same tumors (Gogiashvili et al., 2017[8]). Therefore, the study shows that despite the intratumoral heterogeneity the analysis of only one or few replicates per tumor can be justified. This is of high relevance, when large cohorts of patients have to be analyzed.

Currently, the majority of prognostic studies with cancer patients has been performed based on mRNA (Grinberg et al., 2017[10]; 2015[9]; Marchan et al., 2017[15]; Cadenas et al., 2014[2]; Ghallab et al., 2015[6]; Lohr et al., 2015[14]; Hellwig et al., 2016[13]; Stock et al., 2015[20]; Hammad et al., 2016[11]) or immunostaining (Heimes et al., 2017[12]; Mattsson et al., 2015[16]; Schmidt et al., 2012[18]; Barone et al., 2016[1]). Studies with metabolic profiling by HR MAS 1H NMR are still relatively rare in breast cancer. Therefore, the present study of Gogiashvili and colleagues represents an important milestone in this field of research.

Barone E Corrado A Gemignani F Landi S Environmental risk factors for pancreatic cancer: an update Arch Toxicol 2016 90 2617 2642 Cadenas C van de Sandt L Edlund K Lohr M Hellwig B Marchan R Loss of circadian clock gene expression is associated with tumor progression in breast cancer Cell Cycle 2014 13 3282 3291 Cao MD Sitter B Bathen TF Bofin A Lønning PE Lundgren S Predicting long-term survival and treatment response in breast cancer patients receiving neoadjuvant chemotherapy by MR metabolic profiling NMR Biomed 2012 25 369 378 Choi JS Baek HM Kim S Kim MJ Youk JH Moon HJ HR-MAS MR spectroscopy of breast cancer tissue obtained with core needle biopsy: correlation with prognostic factors PLoS One 2012 7 e51712 Choi JS Baek HM Kim S Kim MJ Youk JH Moon HJ Magnetic resonance metabolic profiling of breast cancer tissue obtained with core needle biopsy for predicting pathologic response to neoadjuvant chemotherapy PLoS One 2013 8 e83866 Ghallab A Highlight report: Role of the circadian clock system in breast cancer EXCLI J 2015 14 540 541 Giskeødegård GF Lundgren S Sitter B Fjøsne HE Postma G Buydens LM Lactate and glycine-potential MR biomarkers of prognosis in estrogen receptor-positive breast cancers NMR Biomed 2012 25 1271 1279 Gogiashvili M Horsch S Marchan R Gianmoena K Cadenas C Tanner B Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high-resolution magic angle spinning 1H NMR spectroscopy NMR Biomed 2017 Epub ahead of print Grinberg M Highlight report: Erroneous sample annotation in a high fraction of publicly available genome-wide expression datasets EXCLI J 2015 14 1256 1258 Grinberg M Djureinovic D Brunnström HR Mattsson JS Edlund K Hengstler JG Reaching the limits of prognostication in non-small cell lung cancer: an optimized biomarker panel fails to outperform clinical parameters Mod Pathol 2017 30 964 977 Hammad S Osman GS Ezzeldien M Ahmed H Kotb AM Highlight report: Predicting late metastasis in breast cancer EXCLI J 2016 15 867 869 Heimes AS Madjar K Edlund K Battista MJ Almstedt K Gebhard S Prognostic significance of interferon regulating factor 4 (IRF4) in node-negative breast cancer J Cancer Res Clin Oncol 2017 143 1123 1131 Hellwig B Madjar K Edlund K Marchan R Cadenas C Heimes AS Epsin family member 3 and ribosome-related genes are associated with late metastasis in estrogen receptor-positive breast cancer and long-term survival in non-small cell lung cancer using a genome-wide identification and validation strategy PLoS One 2016 11 12 e0167585 Lohr M Hellwig B Edlund K Mattsson JS Botling J Schmidt M Identification of sample annotation errors in gene expression datasets Arch Toxicol 2015 89 2265 2272 Marchan R Büttner B Lambert J Edlund K Glaeser I Blaszkewicz M Glycerol-3-phosphate acyltransferase 1 promotes tumor cell migration and poor survival in ovarian carcinoma Cancer Res 2017 77 4589 4601 Mattsson JS Bergman B Grinberg M Edlund K Marincevic M Jirström K Prognostic impact of COX-2 in non-small cell lung cancer: a comprehensive compartment-specific evaluation of tumor and stromal cell expression Cancer Lett 2015 356 837 845 Park VY Yoon D Koo JS Kim EK Kim SI Choi JS Intratumoral agreement of high-resolution magic angle spinning magnetic resonance spectroscopic profiles in the metabolic characterization of breast cancer Medicine (Baltimore) 2016 95 e3398 Schmidt M Hellwig B Hammad S Othman A Lohr M Chen Z A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin κ C as a compatible prognostic marker in human solid tumors Clin Cancer Res 2012 18 2695 2703 Sitter B Bathen TF Singstad TE Fjøsne HE Lundgren S Halgunset J Quatification of metabolites in breast cancer patients with different clinical prognosis using HR MAS MR spectroscopy NMR Biomed 2010 23 424 431 Stock AM Klee F Edlund K Grinberg M Hammad S Marchan R Gelsolin is associated with longer metastasis-free survival and reduced cell migration in estrogen receptor-positive breast cancer Anticancer Res 2015 35 5277 5285