Comprehensive pan-cancer analysis of N7-methylguanosine regulators: Expression features and potential implications in prognosis and immunotherapy

N7-甲基鸟苷调节因子的泛癌综合分析:表达特征及其在预后和免疫治疗中的潜在意义

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Abstract

Although immunotherapy has made great strides in cancer therapy, its effectiveness varies widely among individual patients as well as tumor types, and there is an urgent need to develop biomarkers for effectively assessing immunotherapy response. In recent years, RNA methylation regulators have demonstrated to be novel potential biomarkers for prognosis as well as immunotherapy of cancers, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-methylguanosine (m7G) is a prevalent RNA modification in eukaryotes, but the relationship between m7G regulators and prognosis as well as tumor immune microenvironment is still unclear. In this study, a pan-cancer analysis of 26 m7G regulators across 17 cancer types was conducted based on the bioinformatics approach. On the one hand, a comprehensive analysis of expression features, genetic variations and epigenetic regulation of m7G regulators was carried out, and we found that the expression tendency of m7G regulators were different among tumors and their aberrant expression in cancers could be affected by single nucleotide variation (SNV), copy number variation (CNV), DNA methylation and microRNA (miRNA) separately or simultaneously. On the other hand, the m7Gscore was modeled based on single sample gene set enrichment analysis (ssGSEA) for evaluating the relationships between m7G regulators and cancer clinical features, hallmark pathways, tumor immune microenvironment, immunotherapy response as well as pharmacotherapy sensitivity, and we illustrated that the m7Gscore exhibited tight correlations with prognosis, several immune features, immunotherapy response and drug sensitivity in most cancers. In conclusion, our pan-cancer analysis revealed that m7G regulators may exert critical roles in the tumor progression and immune microenvironment, and have the potential as biomarkers for predicting prognosis, immunotherapy response as well as candidate drug compounds for cancer patients.

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