Background. 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment. Methods. Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan–Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail. Results. Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database. Conclusions. Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients.

中文翻译：

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m5C RNA 修饰相关基因对卵巢癌患者预后和免疫治疗预测的贡献

背景。5-甲基胞嘧啶 (m5C) RNA 修饰与多种癌症的发生密切相关。在这里，我们基于 m5C RNA 修饰相关基因建立了卵巢癌 (OC) 患者的新预后特征，并探讨了这些基因与肿瘤免疫微环境之间的相关性。方法。甲基化RNA免疫沉淀测序帮助我们首先鉴定了与m5C RNA修饰相关的候选基因。基于TCGA数据库，筛选与预后相关的差异表达候选基因，并利用LASSO Cox回归分析构建预后模型。值得注意的是，该模型的准确性是通过 Kaplan-Meier 分析和接收者操作员特征曲线进行评估的。通过Cox比例风险模型研究独立的预后危险因素。此外，我们还分析了签名中涉及的生物学功能和途径。最后，模型的免疫反应被非常详细地可视化。结果。总共有 2,493 个候选基因被证明参与了 OC RNA 的 m5C 修饰。我们开发了一个具有预后价值的特征，由六个 m5C RNA 修饰相关基因组成。特别是，根据模型将样本分为低风险和高风险评分的两个队列，其中低风险的 OC 患者比高风险评分的患者表现出明显更好的总生存时间。此外，该模型不仅是独立于其他临床特征的预后因素，而且可以预测 OC 中免疫反应的强度。值得注意的是，签名的准确性和可用性得到了 ICGC 数据库的验证。结论。我们的研究弥合了m5C RNA修饰与OC预后之间的差距，有望为OC患者的免疫治疗提供有效的突破。