AUTHOR=Xu Huifang , Zhang Linfang , Xia Xiujuan , Shao Wei 

TITLE=Identification of a Five-mRNA Signature as a Novel Potential Prognostic Biomarker for Glioblastoma by Integrative Analysis

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.931938

DOI=10.3389/fgene.2022.931938

ISSN=1664-8021

ABSTRACT=Despite the availability of advanced multimodal therapy, the prognosis of patients suffering from glioblastoma (GBM) remains poor. We conducted a genome-wide integrative analysis of mRNA expression profiles in 302 GBM tissues and 209 normal brain tissues from the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project to examine the prognostic and predictive value of specific mRNAs in GBM. A total of 26 mRNAs were identified to be closely related to GBM patients’ OS (P<0.05). Utilizing survival analysis and the Cox regression model, we discovered a set of five mRNAs (PTPRN, ABCC3, MDK, NMB, and RALYL) from these 26 mRNAs that displayed the capacity to stratify patients into high- and low-risk groups with statistically different overall survival in the training set. The model of the five-mRNA biomarker signature was successfully verified on a testing set and independent sets. Moreover, multivariate Cox regression analysis revealed that the five-mRNA biomarker signature was a prognostic factor for the survival of patients with GBM independent of clinical characteristics and molecular features (P<0.05). Gene set enrichment analysis indicated that the five-mRNA biomarker signature may be implicated in the incidence and development of GBM through its roles in known cancer-related pathways, signaling molecules and the immune system. Moreover, consistent with the bioinformatics analysis, NMB, ABCC3, and MDK mRNA expression was considerably higher and in 4 human GBM cells, and the expression of PTPRN and RALYL was decreased in GBM cells (P<0.05). Our study developed a novel candidate model that provides new prospective prognostic biomarkers for GBM.