Identification of key genes involved in the recurrence of glioblastoma multiforme using weighted gene co-expression network analysis and differential expression analysis

Abstract

Glioblastoma multiforme (GBM) is the most fatal malignancy, and despite extensive treatment, tumors inevitably recur. This study aimed to identify recurrence-associated molecules in GBM. The gene expression profile GSE139533, containing 70 primary and 47 recurrent GBM tissues and their corresponding clinical traits, was downloaded from the Gene Expression Omnibus (GEO) database and used for weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis. After identifying the hub genes which differentially expressed in recurrent GBM tissues and in the gene modules correlated with recurrence, data from the Chinese Glioma Genome Atlas (CCGA) and The Cancer Genome Atlas (TCGA) databases were analyzed with GSE43378 to determine the relationship between hub genes and patient prognosis. The diagnostic value of the identified hub genes was verified using 52 GBM tissues. Three gene modules were correlated with recurrence and 2623 genes were clustered in these clinically significant modules. Among these, 13 genes–EHF, TRPM1, FXYD4, CDH15, LHX5, TP73, FBN3, TLX1, C1QL4, COL2A, SEC61G, NEUROD4 and GPR139–were differentially expressed in recurrent GBM samples; low LHX5 and TLX1 expression predicted poor outcomes. LHX5 and TLX1 expression showed weak positive relationships with Karnofsky performance scale scores. Additionally, LHX5 and TLX1 expression was found to be decreased in our recurrent GBM samples compared with that in primary samples; these genes exhibited high diagnostic value in distinguishing recurrent samples from primary samples. Our findings indicate that LHX5 and TLX1 might be involved in GBM recurrence and act as potential biomarkers for this condition.