Prognostic Model and Nomogram Construction Based on a Novel Ferroptosis-Related Gene Signature in Lower-Grade Glioma - Zhao, Junsheng; Liu, Zhengtao; Zheng, Xiaoping; Gao, Hainv; Li, Lanjuan (Frontiers in Genetics, 2021)
Background: Low-grade glioma (LGG) is considered as a fatal disease for young adults, with overall survival widely ranges from 1 to 15 years depending on histopathologic and molecular subtypes. As novel type of programmed cell death, ferroptosis was reported to be involved in tumorigenesis and development which was being intensively studied in recent years. Methods: For discovery cohort, data from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression (GTEx) were used to identify the differentially expressed and prognostic ferroptosis-related genes (FRGs). Least Absolute Shrinkage and Selection Operator (LASSO)and multivariate Cox were used to establish a prognosis signature with above selected FRGs. Then the signature was developed and validated in TCGA and Chinese Glioma Genome Atlas (CGGA) database. By combining clinic-pathological features and FRGs signature, a nomogram was established to predict individuals 1-, 3-, and 5-year survival probability, and its predictive performance was evaluated by Harrell’s concordance index (C-index) and calibration curves. Enrichment analysis was performed to explore the signaling pathways regulated by the signature. Results: A novel risk signature contains seven FRGs were constructed and were used to divide patients into two groups. Kaplan-Meier (K-M) survival curve and receiver operating characteristic (ROC) curves analyses confirmed the prognostic performance of the risk model, followed by external validation based on data from CGGA. The nomogram based on the risk signature and clinical traits which was validated to perform well for predicting survival rate of LGG. Finally, functional analysis revealed that the immune statuses were different between two risk groups, which might help explain the underlying mechanisms of ferroptosis in LGG.