An eight-mRNA signature outperforms the lncRNA-based signature in predicting prognosis of patients with glioblastoma.

ABSTRACT: BACKGROUND:The prognosis of the glioblastoma (GBM) is dismal. This study aims to select an optimal RNA signature for prognostic prediction of GBM patients. METHODS:For the training set, the long non-coding RNA (lncRNA) and mRNA expression profiles of 151 patients were downloaded from the TCGA. Differentially expressed mRNAs (DEGs) and lncRNAs (DE-lncRNAs) were identified between good prognosis and bad prognosis patients. Optimal prognostic mRNAs and lncRNAs were selected respectively, by using univariate Cox proportional-hazards (PH) regression model and LASSO Cox-PH model. Subsequently, four prognostic scoring models were built based on expression levels or expression status of the selected prognostic lncRNAs or mRNAs, separately. Each prognostic model was applied to the training set and

SUBMITTER: Gong Z 

PROVIDER: S-EPMC7081624 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature