Toward improved grading of malignancy in oligodendrogliomas using metabolomics

Abstract

In spite of having been the object of considerable attention, the histopathological grading of oligodendrogliomas is still controversial. The determination of reliable biomarkers capable of improving the malignancy grading remains an essential step in working toward better therapeutic management of patients. Therefore the metabolome of 34 human brain biopsies, histopathologically classified as low-grade (LGO, N = 10) and high-grade (HGO, N = 24) oligodendrogliomas, was studied using high-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS NMR) and multivariate statistical analysis. The classification model obtained afforded a clear distinction between LGOs and HGOs and provided some useful insights into the different metabolic pathways that underlie malignancy grading. The analysis of the most discriminant metabolites in the model revealed the presence of tumoral hypoxia in HGOs. The statistical model was then used to study biopsy samples that were classified as intermediate oligodendrogliomas (N = 6) and glioblastomas (GBMs) (N = 30) by histopathology. The results revealed a gradient of tumoral hypoxia increasing in the following direction: LGOs, intermediate oligodendrogliomas, HGOs, and GBMs. Moreover upon analysis of the clinical evolution of the patients, the metabolic classification seems to provide a closer correlation with the actual patient evolution than the histopathological analysis.