Identification of a multidimensional transcriptome signature for survival prediction of postoperative glioblastoma multiforme patients.
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ABSTRACT: BACKGROUND:Glioblastoma multiform (GBM) is a devastating brain tumor with maximum surgical resection, radiotherapy plus concomitant and adjuvant temozolomide (TMZ) as the standard treatment. Diverse clinicopathological and molecular features are major obstacles to accurate predict survival and evaluate the efficacy of chemotherapy or radiotherapy. Reliable prognostic biomarkers are urgently needed for postoperative GBM patients. METHODS:The protein coding genes (PCGs) and long non-coding RNA (lncRNA) gene expression profiles of 233 GBM postoperative patients were obtained from The Cancer Genome Atlas (TCGA), TANRIC and Gene Expression Omnibus (GEO) database. We randomly divided the TCGA set into a training (n?=?76) and a test set (n?=?77) and used GSE7696 (n?=?80) as an independent validation set. Survival analysis and the random survival forest algorithm were performed to screen survival associated signature. RESULTS:Six PCGs (EIF2AK3, EPRS, GALE, GUCY2C, MTHFD2, RNF212) and five lncRNAs (CTD-2140B24.6, LINC02015, AC068888.1, CERNA1, LINC00618) were screened out by a risk score model and formed a PCG-lncRNA signature for its predictive power was strongest (AUC?=?0.78 in the training dataset). The PCG-lncRNA signature could divide patients into high- risk or low-risk group with significantly different survival (median 7.47 vs. 18.27 months, log-rank test P?
SUBMITTER: Gao WZ
PROVIDER: S-EPMC6302404 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
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