A Novel 16-Genes Signature Scoring System as Prognostic Model to Evaluate Survival Risk in Patients with Glioblastoma.

ABSTRACT: Previous studies have found that gene expression levels are associated with prognosis and some genes can be used to predict the survival risk of glioblastoma (GBM) patients. However, most of them just built the survival-related gene signature, and personal survival risk can be evaluated only in group. This study aimed to find the prognostic survival related genes of GBM, and construct survival risk prediction model, which can be used to evaluate survival risk by individual. We collected gene expression data and clinical information from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analysis and LASSO-cox regression analysis were performed to get survival-related genes and establish the overall survival prediction model. The ROC curve and Kap

SUBMITTER: Yu Z 

PROVIDER: S-EPMC8869708 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature