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Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data.

ABSTRACT: Metabolic alterations play a crucial role in glioma development and progression and can be detected even before the appearance of the fatal phenotype. We have compared the circulating metabolic fingerprints of glioma patients versus healthy controls, for the first time, in a quest to identify a panel of small, dysregulated metabolites with potential to serve as a predictive and/or diagnostic marker in the clinical settings. High-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS-NMR) was used for untargeted metabolomics and data acquisition followed by a machine learning (ML) approach for the analyses of large metabolic datasets. Cross-validation of ML predicted NMR spectral features was done by statistical methods (Wilcoxon-test) using JMP-pro16 software. Alanine was identified as the most critical metabolite with potential to detect glioma with precision of 1.0, recall of 0.96, and F1 measure of 0.98. The top 10 metabolites identified for glioma detection included alanine, glutamine, valine, methionine, N-acetylaspartate (NAA), γ-aminobutyric acid (GABA), serine, α-glucose, lactate, and arginine. We achieved 100% accuracy for the detection of glioma using ML algorithms, extra tree classifier, and random forest, and 98% accuracy with logistic regression. Classification of glioma in low and high grades was done with 86% accuracy using logistic regression model, and with 83% and 79% accuracy using extra tree classifier and random forest, respectively. The predictive accuracy of our ML model is superior to any of the previously reported algorithms, used in tissue- or liquid biopsy-based metabolic studies. The identified top metabolites can be targeted to develop early diagnostic methods as well as to plan personalized treatment strategies.

SUBMITTER: Firdous S

PROVIDER: S-EPMC8402070 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Succinate dehydrogenase gene (SDHx) mutations increase susceptibility to develop pheochromocytomas/paragangliomas (PHEOs/PGLs). In the present study, we evaluate the performance and clinical applications of (1)H high-resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) spectroscopy-based global metabolomic profiling in a large series of PHEOs/PGLs of different genetic backgrounds. Eighty-seven PHEOs/PGLs (48 sporadic/23 SDHx/7 von Hippel-Lindau/5 REarranged during Transfection/3 neurofibromatosis type 1/1 hypoxia-inducible factor 2α), one SDHD variant of unknown significance, and two Carney triad (CTr)-related tumors were analyzed by HRMAS-NMR spectroscopy. Compared to sporadic, SDHx-related PHEOs/PGLs exhibit a specific metabolic signature characterized by increased levels of succinate (P < .0001), methionine (P = .002), glutamine (P = .002), and myoinositol (P < .0007) and decreased levels of glutamate (P < .0007), regardless of their location and catecholamine levels. Uniquely, ATP/ascorbate/glutathione was found to be associated with the secretory phenotype of PHEOs/PGLs, regardless of their genotype (P < .0007). The use of succinate as a single screening test retained excellent accuracy in distinguishing SDHx versus non-SDHx-related tumors (sensitivity/specificity: 100/100%). Moreover, the quantification of succinate could be considered a diagnostic alternative for assessing SDHx-related mutations of unknown pathogenicity. We were also able, for the first time, to uncover an SDH-like pattern in the two CTr-related PGLs. The present study demonstrates that HRMAS-NMR provides important information for SDHx-related PHEO/PGL characterization. Besides the high succinate-low glutamate hallmark, SDHx tumors also exhibit high values of methionine, a finding consistent with the hypermethylation pattern of these tumors. We also found important levels of glutamine, suggesting that glutamine metabolism might be involved in the pathogenesis of SDHx-related PHEOs/PGLs.

Project description:BACKGROUND: Epidermal growth factor (EGF) plays an important role in carcinogenesis. An adenine (A) to guanine (G) single nucleotide polymorphism at position 61 in the 5'-untranslated region (5'-UTR) of the EGF gene has been found to be associated with levels of EGF production and contribute to the risk of glioma. However, published data are contradictory. EGF +61G/A polymorphism may contribute to the risk of glioma in different ethnic group. Patients with glioma and GG genotype have been reported to have a risk of poorer outcome than patients with AA genotype. Purpose of this study is to investigate the potential role of this polymorphism in cancer progression and its role as predictive marker of outcome in glioma caucasian patients. METHODS: The significant SNP rs4444903, EGF 61A/G, was analyzed in glioma patients and was determined by means of Polymerase Chain Reaction and Direct Sequencing method from blood samples. Association of this genetic polymorphism with clinical and pathological data of patients was evaluated. RESULTS: We investigated EGF +61G/A polymorphism in 28 glioma patients. EGF +61G allele has been found in 68% of glioma patients (22% G/G genotype and 46% A/G genotype). In astrocytomas, EGF +61G allele represents a 83% frequency; in glioblastomas and in oligodendrogliomas, EGF +61G allele frequency represents respectively 73% and 54%. In WHO IV gliomas, the EGF +61G allele represents a 72% frequency, (27% G/G and 45% A/G ), in WHO III gliomas a 81% frequency (54% G/G and 27% A/G ) and in WHO II gliomas a 33% frequency (80% A/G ). Median PFS of glioblastoma patients was 9 months. 79% of glioblastoma patients with a relapsing disease showed the G/G and A/G genotype. No difference was detected in the others histotypes. CONCLUSIONS: Our data confirm previous studies which reported G allele as a risk factor for glioma in Caucasian. G/A and G/G genotypes seem to be more rappresentative in high grade gliomas . Despite limited number of patients, our study supports the predictive role of EGF 61 A/G polymorphism in GBM. Additional large studies are warranted to confirm the role of EGF polymorphism as indipendent prognostic factor in glioma.

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Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data.

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