Identification and validation of an autophagy-related signature for predicting survival in lower-grade glioma.

Abstract

Abnormal levels of autophagy have been implicated in the pathogenesis of multiple diseases, including cancer. However, little is known about the role of autophagy-related genes (ARGs) in low-grade gliomas (LGG). Accordingly, the aims of this study were to assess the prognostic values of ARGs and to establish a genetic signature for LGG prognosis. Expression profile data from patients with and without primary LGG were obtained from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression databases, respectively, and consensus clustering was used to identify clusters of patients with distinct prognoses. Nineteen differentially expressed ARGs were selected with threshold values of FDR < 0.05 and |log2 fold change (FC)| ≥ 2, and functional analysis revealed that these genes were associated with autophagy processes as expected. An autophagy-related signature was established using a Cox regression model of six ARGs that separated patients from TCGA training cohort into high- and low-risk groups. Univariate and multivariate Cox regression analysis indicated that the signature-based risk score was an independent prognostic factor. The signature was successfully validated using the TCGA testing, TCGA entire, and Chinese Glioma Genome Atlas cohorts. Stratified analyses demonstrated that the signature was associated with clinical features and prognosis, and gene set enrichment analysis revealed that autophagy- and cancer-related pathways were more enriched in high-risk patients than in low-risk patients. The prognostic value and expression of the six signature-related genes were also investigated. Thus, the present study constructed and validated an autophagy-related prognostic signature that could optimize individualized survival prediction in LGG patients.