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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Oncol. | doi: 10.3389/fonc.2019.00328


  • 1Department of Neurosurgery, University Hospital La Paz, Spain
  • 2Institute of Biomedical Research Alberto Sols, Faculty of Medicine, Autonomous University of Madrid, Spain
  • 3Spanish National Research Council (CSIC), Spain
  • 4Hospital Universitario Reina Sofía, Spain
  • 5Department of Neurosurgery and Clinical Neurophysiology, Reina Sofía University Hospital, Spain

Objective: We assess the efficacy of the metabolomic profile of the tumor in providing estimates of postsurgical Overall Survival in glioma patients.

Methods: Tumor biopsies from 46 patients bearing gliomas, obtained neurosurgically in the period 1992-1998, were analyzed by high resolution 1H magnetic resonance spectroscopy (HR- 1H MRS) and histopathology, following retrospectively individual postsurgical Overall Survival up to 720 weeks.

Results: The Overall Survival profile could be resolved in three groups; Short (shorter than 52 weeks, n=19), Intermediate (between 53 and 364 weeks, n=19) or Long (longer than 365 weeks, n=8), respectively. Classical histopathological analysis assigned WHO grades II-IV to every biopsy but notably, some patients with low grade glioma depicted unexpectedly Short Overall Survival, while some patients with high grade glioma, presented unpredictably Long Overall Survival. To explore the reasons underlying this response, we analyzed HR- 1H MRS spectra from acid extracts of the same biopsies, to identify the metabolite patterns associated to OS predictions. Poor prognosis was found in biopsies with higher contents of alanine, acetate, glutamate, total choline, phosphorylcholine and glycine, while more favorable prognosis was achieved in biopsies with larger contents of total creatine, glycerol-phosphorylcholine and myo-inositol. We implemented then a multivariate analysis approach to identify hierarchically the influence of metabolomic biomarkers on OS predictions, using a Classification Regression Tree. Classification Regression Tree based in metabolomic criteria grew up to 3 branches and split into 8 nodes, predicting correctly the outcome of 94.7% of the patients in the Short Overall Survival group, 78.9 % of the patients in the Intermediate Overall Survival group, and 75% of the patients in the Long Overall Survival group, respectively.

Conclusion: Present results indicate that metabolic profiling by HR-1H MRS provides reliable Overall Survival predictions.

Keywords: Glioma,, Metabolomic profile, High resolution proton magnetic resonance spectroscopy, Overall survival (OS) prediction, Classification decision tree

Received: 13 Feb 2019; Accepted: 11 Apr 2019.

Edited by:

Bo Gao, Affiliated Hospital of Guizhou Medical University, China

Reviewed by:

Bihong T. Chen, City of Hope National Medical Center, United States
Ru J. Wang, Tangshan Gongren Hospital, China  

Copyright: © 2019 Gandía-González, Cerdan, Barrios, López-Larrubia, G. Feijoo, Palpan, Roda and Solivera. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Maria L. Gandía-González, Department of Neurosurgery, University Hospital La Paz, Madrid, Spain,