Risk Model and Immune Signature of m7G-Related lncRNA Based on Lung Adenocarcinoma - Zhang, Chuanhao; Zhou, Dong; Wang, Zhe; Ju, Zaishuang; He, Jiabei; Zhao, Genghao; Wang, Ruoyu (Frontiers in Genetics, 2022)
Lung cancer is a major cause of cancer-related deaths globally, with a dismal prognosis. N7-methylguanosine (m7G) is essential for the transcriptional phenotypic modification of messenger RNA (mRNA) and long noncoding RNA (lncRNA). However, research on m7G-related lncRNAs involved in lung adenocarcinoma (LUAD) regulation is still limited. Herein, we aim to establish for the first time a prognostic model of m7G-related lncRNAs and investigate their immune properties. Eight prognostic m7G-related lncRNAs were identified using univariate Cox analysis. Six m7G-related lncRNAs were identified using LASSO-Cox regression analysis to construct risk models. The accuracy of the model was verified by Kaplan-Meier analysis, time-dependent receiver operating characteristic, principal component analysis, independent prognostic analysis, nomogram, and calibration curve. A risk model-based gene set enrichment analysis, disease ontology enrichment analysis, immune correlation analysis, and drug sensitivity analysis were also analyzed. In conclusion, a risk model based on 6 m7G-related lncRNAs can not only predict the OS rate of LUAD patients but also guide individualized treatment for these patients.