A novel signature based on necroptosis-related long non-coding RNAs for predicting prognosis of patients with glioma - Xia, Pengfei; Huang, Yimin; Chen, Gang (Frontiers in Oncology, 2022)
Necroptosis is closely related to the occurrence and development of tumors, including glioma. Growing number of studies indicate that targeting necroptosis could be an effective treatment strategy against cancer. Long non-coding RNA (lncRNA) is also believed to play a pivotal role in tumor epigenetics. Therefore, it is necessary to identify the functions of necroptosis-related lncRNAs in Glioma. In this study, the transcriptome as well as clinical characteristics data of glioma patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database were collected, and the differentially expressed necroptosis-related lncRNAs in TCGA that have an impact on overall survival (OS) were screened out to construct risk score (RS) formula, which was verified in CGGA. A nomogram was constructed to predict the prognosis of glioma patients based on clinical characteristics and RS. In addition, Gene Set Enrichment Analysis (GSEA) was used to analyze the main enrichment functions of these necroptosis-related lncRNAs and the immune microenvironment. A total of 9 necroptosis related lncRNAs have been identified to construct RS formula, and (Kaplan-Meier) K-M survival analysis showed significantly poorer outcomes in the high RS group in both TCGA and CGGA databases. Moreover, the receiver operating characteristic (ROC) curve shows that our prediction RS model has good predictability. Regarding analysis of immune microenvironment, significant differences were observed in immune function and immune checkpoint between the high RS group and the low RS group. In conclusion, we constructed the necroptosis-related lncRNAs RS model that can effectively predict the prognosis of glioma patients, and provided theoretical basis and the potential therapeutic targets for immunotherapy against gliomas.