Huang Xiaoliang, Chen Zuyuan, Xiang Xiaoyun, Liu Yanling, Long Xingqing, Li Kezhen, Qin Mingjian, Long Chenyan, Mo Xianwei, Tang Weizhong, Liu Jungang
Division of Colorectal & Anal Surgery, Department of Gastrointestinal Surgery, Guangxi Medical University Cancer Hospital, Nanning, The People's Republic of China.
EPMA J. 2022 Nov 22;13(4):671-697. doi: 10.1007/s13167-022-00305-1. eCollection 2022 Dec.
The N7-methylguanosine modification (m7G) of the 5' cap structure in the mRNA plays a crucial role in gene expression. However, the relation between m7G and tumor immune remains unclear. Hence, we intended to perform a pan-cancer analysis of m7G which can help explore the underlying mechanism and contribute to predictive, preventive, and personalized medicine (PPPM / 3PM).
The gene expression, genetic variation, clinical information, methylation, and digital pathological section from 33 cancer types were downloaded from the TCGA database. Immunohistochemistry (IHC) was used to validate the expression of the m7G regulator genes (m7RGs) hub-gene. The m7G score was calculated by single-sample gene-set enrichment analysis. The association of m7RGs with copy number variation, clinical features, immune-related genes, TMB, MSI, and tumor immune dysfunction and exclusion (TIDE) was comprehensively assessed. CellProfiler was used to extract pathological section characteristics. XGBoost and random forest were used to construct the m7G score prediction model. Single-cell transcriptome sequencing (scRNA-seq) was used to assess the activation state of the m7G in the tumor microenvironment.
The m7RGs were highly expressed in tumors and most of the m7RGs are risk factors for prognosis. Moreover, the cellular pathway enrichment analysis suggested that m7G score was closely associated with invasion, cell cycle, DNA damage, and repair. In several cancers, m7G score was significantly negatively correlated with MSI and TMB and positively correlated with TIDE, suggesting an ICB marker potential. XGBoost-based pathomics model accurately predicts m7G scores with an area under the ROC curve (AUC) of 0.97. Analysis of scRNA-seq suggests that m7G differs significantly among cells of the tumor microenvironment. IHC confirmed high expression of EIF4E in breast cancer. The m7G prognostic model can accurately assess the prognosis of tumor patients with an AUC of 0.81, which was publicly hosted at https://pan-cancer-m7g.shinyapps.io/Panca-m7g/.
The current study explored for the first time the m7G in pan-cancer and identified m7G as an innovative marker in predicting clinical outcomes and immunotherapeutic efficacy, with the potential for deeper integration with PPPM. Combining m7G within the framework of PPPM will provide a unique opportunity for clinical intelligence and new approaches.
The online version contains supplementary material available at 10.1007/s13167-022-00305-1.
mRNA中5'帽结构的N7-甲基鸟苷修饰（m7G）在基因表达中起关键作用。然而，m7G与肿瘤免疫之间的关系仍不清楚。因此，我们旨在对m7G进行泛癌分析，这有助于探索潜在机制，并为预测、预防和个性化医学（PPPM / 3PM）做出贡献。
从TCGA数据库下载33种癌症类型的基因表达、基因变异、临床信息、甲基化和数字病理切片。采用免疫组织化学（IHC）验证m7G调节基因（m7RGs）枢纽基因的表达。通过单样本基因集富集分析计算m7G评分。全面评估m7RGs与拷贝数变异、临床特征、免疫相关基因、肿瘤突变负荷（TMB）、微卫星高度不稳定（MSI）以及肿瘤免疫功能障碍和排除（TIDE）的关联。使用CellProfiler提取病理切片特征。采用XGBoost和随机森林构建m7G评分预测模型。利用单细胞转录组测序（scRNA-seq）评估肿瘤微环境中m7G的激活状态。
m7RGs在肿瘤中高表达，且大多数m7RGs是预后危险因素。此外，细胞通路富集分析表明，m7G评分与侵袭、细胞周期、DNA损伤和修复密切相关。在几种癌症中，m7G评分与MSI和TMB显著负相关，与TIDE正相关，提示其具有免疫检查点阻断（ICB）标志物潜力。基于XGBoost的病理组学模型能够准确预测m7G评分，受试者工作特征曲线（ROC）下面积（AUC）为0.97。scRNA-seq分析表明，肿瘤微环境中的细胞间m7G存在显著差异。IHC证实乳腺癌中真核翻译起始因子4E（EIF4E）高表达。m7G预后模型能够准确评估肿瘤患者的预后，AUC为0.81，该模型可在https://pan-cancer-m7g.shinyapps.io/Panca-m7g/上公开获取。
本研究首次在泛癌中探索了m7G，并将其确定为预测临床结局和免疫治疗疗效的创新标志物，具有与PPPM进行更深入整合的潜力。在PPPM框架内结合m7G将为临床智能和新方法提供独特机会。
在线版本包含可在10.1007/s13167-022-00305-1获取的补充材料。
