Prediction of clinical outcome in glioblastoma using a biologically relevant nine-microRNA signature.

ABSTRACT:

Background

Glioblastoma is the most aggressive primary brain tumor, and is associated with a very poor prognosis. In this study we investigated the potential of microRNA expression profiles to predict survival in this challenging disease.

Methods

MicroRNA and mRNA expression data from glioblastoma (n = 475) and grade II and III glioma (n = 178) were accessed from The Cancer Genome Atlas. LASSO regression models were used to identify a prognostic microRNA signature. Functionally relevant targets of microRNAs were determined using microRNA target prediction, experimental validation and correlation of microRNA and mRNA expression data.

Results

A 9-microRNA prognostic signature was identified which stratified patients into risk groups strongly associated with survival (p 

SUBMITTER: Hayes J 

PROVIDER: S-EPMC5528696 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature