A metabolomic data fusion approach to support gliomas grading. (11th December 2019)

• Record Type: Journal Article
• Authors: Righi, Valeria; Cavallini, Nicola; Valentini, Antonella; Pinna, Giampietro; Pavesi, Giacomo; Rossi, Maria Cecilia; Puzzolante, Annette; Mucci, Adele; Cocchi, Marina
• Is Part Of: NMR in biomedicine. Volume 33:Number 3(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-11
• Subjects: Gliomas -- Brain tumors -- Metabolomics -- HR‐MAS NMR -- SIMCA -- Multivariate Curve Resolution -- Classification -- Double cross‐validation; Nuclear magnetic resonance -- Periodicals; Magnetic Resonance Spectroscopy -- Periodicals; 574
• DOI: 10.1002/nbm.4234
• Languages: English
• ISSNs: 0952-3480

Abstract

Abstract : Magnetic resonance imaging (MRI) is the current gold standard for the diagnosis of brain tumors. However, despite the development of MRI techniques, the differential diagnosis of central nervous system (CNS) primary pathologies, such as lymphoma and glioblastoma or tumor‐like brain lesions and glioma, is often challenging. MRI can be supported by in vivo magnetic resonance spectroscopy (MRS) to enhance its diagnostic power and multiproject‐multicenter evaluations of classification of brain tumors have shown that an accuracy around 90% can be achieved for most of the pairwise discrimination problems. However, the survival rate for patients affected by gliomas is still low. The High‐Resolution Magic‐Angle‐Spinning Nuclear Magnetic Resonance (HR‐MAS NMR) metabolomics studies may be helpful for the discrimination of gliomas grades and the development of new strategies for clinical intervention. Here, we propose to use T2 ‐filtered, diffusion‐filtered and conventional water‐presaturated spectra to try to extract as much information as possible, fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR). Biomarkers important for glioma's discrimination were found. In particular, we focused our attention on cystathionine (Cyst) that shows promise as a biomarker for the better prognosis of glioma tumors. Abstract : High‐Resolution Magic‐Angle‐Spinning NMR metabolomics studies can help in the discrimination of gliomas. We propose to evaluate not only T2 ‐filtered spectra but also diffusion‐filtered and water‐presaturated spectra fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution. Biomarkers important for glioma's discrimination were found, in particular, cystathionine seems a biomarker for a better prognosis of glioma tumors.