ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma

Srinivasan, Sujaya and Patric, Irene Rosita Pia and Somasundaram, Kumaravel (2011) A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma. In: PLos One, 6 (3).

journal.pone.0017438.pdf - Published Version
Available under License Creative Commons Attribution.

Download (312kB)
Official URL: http://www.plosone.org/article/info%3Adoi%2F10.137...


Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

Item Type: Journal Article
Publication: PLos One
Publisher: Public Library of Science
Additional Information: Copyright of this article belongs to Public Library of Science.
Department/Centre: Division of Biological Sciences > Microbiology & Cell Biology
Date Deposited: 06 May 2011 05:17
Last Modified: 06 May 2011 05:17
URI: http://eprints.iisc.ac.in/id/eprint/37371

Actions (login required)

View Item View Item