Prognostic Signature and Tumor Immune Landscape of N7-Methylguanosine-Related lncRNAs in Hepatocellular Carcinoma

肝细胞癌中N7-甲基鸟苷相关lncRNA的预后特征和肿瘤免疫图谱

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Abstract

Despite great advances in the treatment of liver hepatocellular carcinoma (LIHC), such as immunotherapy, the prognosis remains extremely poor, and there is an urgent need to develop novel diagnostic and prognostic markers. Recently, RNA methylation-related long non-coding RNAs (lncRNAs) have been demonstrated to be novel potential biomarkers for tumor diagnosis and prognosis as well as immunotherapy response, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-Methylguanosine (m7G) is a widespread RNA modification in eukaryotes, but the relationship between m7G-related lncRNAs and prognosis of LIHC patients as well as tumor immunotherapy response is still unknown. In this study, based on the LIHC patients' clinical and transcriptomic data from TCGA database, a total of 992 m7G-related lncRNAs that co-expressed with 22 m7G regulatory genes were identified using Pearson correlation analysis. Univariate regression analysis was used to screen prognostic m7G-related lncRNAs, and the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were applied to construct a 9-m7G-related-lncRNA risk model. The m7G-related lncRNA risk model was validated to exhibit good prognostic performance through Kaplan-Meier analysis and ROC analysis. Together with the clinicopathological features, the m7G-related lncRNA risk score was found to be an independent prognostic factor for LIHC. Furthermore, the high-risk group of LIHC patients was unveiled to have a higher tumor mutation burden (TMB), and their tumor microenvironment was more prone to the immunosuppressive state and exhibited a lower response rate to immunotherapy. In addition, 47 anti-cancer drugs were identified to exhibit a difference in drug sensitivity between the high-risk and low-risk groups. Taken together, the m7G-related lncRNA risk model might display potential value in predicting prognosis, immunotherapy response, and drug sensitivity in LIHC patients.

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