Twenty Metabolic Genes Based Signature Predicts Survival of Glioma Patients.

ABSTRACT: Background: Glioma, caused by carcinogenesis of brain and spinal glial cells, is the most common primary malignant brain tumor. To find the important indicator for glioma prognosis is still a challenge and the metabolic alteration of glioma has been frequently reported recently. Methods: In our current work, a risk score model based on the expression of twenty metabolic genes was developed using the metabolic gene expressions in The Cancer Genome Atlas (TCGA) dataset, the methods of which included the cox multivariate regression and the random forest variable hunting, a kind of machine learning algorithm, and the risk score generated from this model is used to make predictions in the survival of glioma patients in the training dataset. Subsequently, the result was further ver

SUBMITTER: Xu W 

PROVIDER: S-EPMC6930419 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature