Prognostic Model and Nomogram Construction Based on a Novel Ferroptosis-Related Gene Signature in Lower-Grade Glioma

• DOI: 10.3389/fgene.2021.753680
• Publication Date: 2021-11-08T06:15:27Z
• Authors: Junsheng Zhao; Zhengtao Liu; Xiaoping Zheng; Hainv Gao; Lanjuan Li
• Keywords: Nomogram; Gene signature; Concordance

Background: Low-grade glioma (LGG) is considered a fatal disease for young adults, with overall survival widely ranging from 1 to 15 years depending on histopathologic and molecular subtypes. As novel type of programmed cell death, ferroptosis was reported be involved in tumorigenesis development, which has been intensively studied recent years. Methods: For the discovery cohort, data The Cancer Genome Atlas (TCGA) Genotype-Tissue Expression (GTEx) were used identify differentially expressed prognostic ferroptosis-related genes (FRGs). least absolute shrinkage selection operator (LASSO) multivariate Cox establish signature above-selected FRGs. Then, developed validated TCGA Chinese Glioma (CGGA) databases. By combining clinicopathological features FRG signature, nomogram established predict individuals' one-, three-, five-year probability, its predictive performance evaluated by Harrell's concordance index (C-index) calibration curves. Enrichment analysis performed explore signaling pathways regulated signature. Results: A risk contains seven FRGs that constructed divide patients into two groups. Kaplan-Meier (K-M) curve receiver-operating characteristic (ROC) analyses confirmed model, followed external validation based CGGA. clinical traits perform well predicting rate LGG. Finally, functional revealed immune statuses different between groups, might help explain underlying mechanisms Conclusion: In conclusion, this study robust seven-FRG LGG prediction.