Identification of Autophagy-Related Prognostic Signature for Glioblastoma Standard Therapy.

Abstract

Glioblastoma is an aggressive brain tumor with poor prognosis and survival. Autophagy is induced in tumor cells under stress conditions such as treatment with chemotherapeutic agents and radiotherapy (RT), causing resistance to therapy. Thus, we analyzed autophagy-related genes using public databases to investigate a novel prognostic autophagy signature for glioblastoma patients who received temozolomide (TMZ) and RT. The TCGA and CGGA RNA sequencing datasets were classified for TMZ/RT-treated patient groups, and autophagy-related genes were obtained from Human Autophagy Database (HADb). Through sequential analyses of the datasets using univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and log-rank test, four genes (ATG9B, HSPA5, ITGA3, and RAC1) were selected to construct a prognostic risk score model. Multivariate Cox regression analysis of the risk score of these genes in the TCGA dataset demonstrated that TMZ/RT-treated patients with high-risk scores had significantly poorer overall survival and progression-free survival. Most patients designated as a high-risk group were also identified as IDH wild-type and mesenchymal subtypes. The autophagy signature was also validated in the CGGA RNA sequencing dataset and TCGA microarray dataset. Functional analysis of the autophagy signature through gene set enrichment and gene ontology analyses revealed enrichment of cellular responses to stress and the unfolded protein response. We also validated the higher expression of these genes and autophagy flux in TMZ-resistant glioblastoma cells than in TMZ-sensitive cells. Therefore, the autophagy-related gene set could serve as an independent prognostic biomarker for predicting the response to standard therapy in glioblastoma patients.