Research Paper Volume 11, Issue 24 pp 12246—12269
Development and validation of a nomogram with an autophagy-related gene signature for predicting survival in patients with glioblastoma
- 1 Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing 100730, P.R. China
- 2 China Pituitary Disease Registry Center, Chinese Pituitary Adenoma Cooperative Group, Dongcheng, Beijing 100730, P.R. China
Received: October 15, 2019 Accepted: November 20, 2019 Published: December 17, 2019https://doi.org/10.18632/aging.102566
How to Cite
Copyright © 2019 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Glioblastoma (GBM) is the most common brain tumor with significant morbidity and mortality. Autophagy plays a vital role in GBM development and progression. We aimed to establish an autophagy-related multigene expression signature for individualized prognosis prediction in patients with GBM. Differentially expressed autophagy-related genes (DE-ATGs) in GBM and normal samples were screened using TCGA. Univariate and multivariate Cox regression analyses were performed on DE-ATGs to identify the optimal prognosis-related genes. Consequently, NRG1 (HR=1.142, P=0.008), ITGA3 (HR=1.149, P=0.043), and MAP1LC3A (HR=1.308, P=0.014) were selected to establish the prognostic risk score model and validated in the CGGA validation cohort. GSEA revealed that these genes were mainly enriched in cancer- and autophagy-related KEGG pathways. Kaplan-Meier survival analysis demonstrated that patients with high risk scores had significantly poorer overall survival (OS, log-rank P= 6.955×10-5). The autophagy signature was identified as an independent prognostic factor. Finally, a prognostic nomogram including the autophagy signature, age, pharmacotherapy, radiotherapy, and IDH mutation status was constructed, and TCGA/CGGA-based calibration plots indicated its excellent predictive performance. The autophagy-related three-gene risk score model could be a prognostic biomarker and suggest therapeutic targets for GBM. The prognostic nomogram could assist individualized survival prediction and improve treatment strategies.