Prognostic Correlation of Autophagy-Related Gene Expression-Based Risk Signature in Patients with Glioblastoma

• Main Authors: Wang QW, Liu HJ, Zhao Z, Zhang Y, Wang Z, Jiang T, Bao ZS
• Format: Article
• Language: English
• Published: Dove Medical Press 2020-01-01
• Series: OncoTargets and Therapy
• Subjects: autophagy; cgga; glioblastoma; prognosis; risk signature
• Online Access: https://www.dovepress.com/prognostic-correlation-of-autophagy-related-gene-expression-based-risk-peer-reviewed-article-OTT

Qiang-Wei Wang,1 Han-Jie Liu,1 Zheng Zhao,1 Ying Zhang,1 Zheng Wang,2 Tao Jiang,1,2 Zhao-Shi Bao2,3 1Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, People’s Republic of China; 2Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, People’s Republic of China; 3Division of Life Science, Hong Kong University of Science and Technology, Hong Kong, People’s Republic of ChinaCorrespondence: Zhao-Shi BaoDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring West Road, Fengtai District, Beijing 100070, People’s Republic of ChinaTel/Fax [phone]Email [e-mail]: Autophagy plays a vital role in cancer initiation, malignant progression, and resistance to treatment; however, autophagy-related gene sets have rarely been analyzed in glioblastoma. The purpose of this study was to evaluate the prognostic significance of autophagy-related genes in patients with glioblastoma.Patients and methods: Here, we collected whole transcriptome expression data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets to explore the relationship between autophagy-related gene expression and glioblastoma prognosis. R language was the primary analysis and drawing tool.Results: We screened 531 autophagy-related genes and identified 14 associated with overall survival in data from 986 patients with glioblastoma. Patients could be clustered into two groups (high and low risk) using expression data from the 14 associated genes, based on significant differences in clinicopathology and prognosis. Next, we constructed a signature based on the 14 genes and found that most patients designated high risk using our gene signature were IDH wild-type, MGMT promoter non-methylated, and likely to have more malignant tumor subtypes (including classical and mesenchymal subtypes). Survival analysis indicated that patients in the high-risk group had dramatically shorter overall survival compared with their low-risk counterparts. Cox regression analysis further confirmed the independent prognostic value of our 14 gene signature. Moreover, functional and ESTIMATE analyses revealed enrichment of immune and inflammatory responses in the high-risk group.Conclusion: In this study, we identified a novel autophagy-related signature for the prediction of prognosis in patients with glioblastoma.Keywords: Chinese Glioma Genome Atlas, transcriptome, survival analysis, autophagy, glioblastoma