DataSheet2_Prognostic Role of M6A-Associated Immune Genes and Cluster-Related Tumor Microenvironment Analysis: A Multi-Omics Practice in Stomach Adenocarcinoma.ZIP

N6-methylandrostenedione (m6A) methylation plays a very important role in the development of malignant tumors. The immune system is the key point in the progression of tumors, particularly in terms of tumor treatment and drug resistance. Tumor immunotherapy has now become a hot spot and a new approach for tumor treatment. However, as far as the stomach adenocarcinoma (STAD) is concerned, the in-depth research is still a gap in the m6A-associated immune markers. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases is extremely important for our research, where we obtained gene mutation, gene expression data and relevant clinical information of STAD patients. Firstly, the samples from GEO were used as external validation groups, while the TCGA samples were divided into a training group and an internal validation group randomly. Using the way of Single factor COX-LASSO- and multi-factor Cox to construct the prognostic model. Then, all samples were subjected to cluster analysis to generate high and low expression groups of immune gene. Meanwhile, we also collected the correlation between these types and tumor microenvironment. On this basis, a web version of the dynamic nomogram APP was developed. In addition, we performed microenvironmental correlation, copy number variation and mutation analyses for model genes. The prognostic model for STAD developed here demonstrated a very strong predictive ability. The results of cluster analysis manifested that the immune gene low expression group had lower survival rate and higher degree of immune infiltration. Therefore, the immune gene low expression group was associated with lower survival rates and a higher degree of immune infiltration. Gene set enrichment analysis suggested that the potential mechanism might be related to the activation of immunosuppressive functions and multiple signaling pathways. Correspondingly, the web version of the dynamic nomogram APP produced by the DynNom package has successfully achieved rapid and accurate calculation of patient survival rates. Finally, the multi-omics analysis of model genes further enriched the research content. Interference of RAB19 was confirmed to facilitate migration of STAD cells in vitro, while its overexpression inhibited these features. The prognostic model for STAD constructed in this study is accurate and efficient based on multi-omics analysis and experimental validation. Additionally, the results of the correlation analysis between the tumor microenvironment and m6Ascore are the basics of further exploration of the pathophysiological mechanism in STAD.

N6-甲基雄烯二酮（N6-methylandrostenedione，m6A）甲基化在恶性肿瘤发生发展中发挥着至关重要的作用。免疫系统是肿瘤进展的核心调控环节，尤其在肿瘤治疗与耐药性层面具有关键意义。当前，肿瘤免疫治疗已成为肿瘤治疗领域的研究热点与全新方向。然而针对胃腺癌（stomach adenocarcinoma, STAD）而言，有关m6A相关免疫标志物的深入研究仍存在空白。癌症基因组图谱（The Cancer Genome Atlas, TCGA）与基因表达综合数据库（Gene Expression Omnibus, GEO）为本研究提供了重要的数据支撑，我们从中获取了胃腺癌患者的基因突变、基因表达数据及相关临床信息。首先，将GEO数据集样本作为外部验证组，将TCGA数据集样本随机划分为训练组与内部验证组。采用单因素COX回归、最小绝对收缩与选择算子（least absolute shrinkage and selection operator, LASSO）及多因素Cox回归分析方法构建预后模型。随后，对所有样本进行聚类分析，得到免疫基因高表达组与低表达组；同时，本研究还分析了上述分组与肿瘤微环境之间的相关性。在此基础上，开发了网页版动态列线图应用程序。此外，本研究还对模型基因开展了微环境相关性分析、拷贝数变异分析及突变分析。本研究构建的胃腺癌预后模型展现出极强的预测性能。聚类分析结果显示，免疫基因低表达组患者的生存率更低，免疫浸润程度更高，即该分组与较差的生存率及更高的免疫浸润程度密切相关。基因集富集分析（Gene Set Enrichment Analysis, GSEA）结果提示，其潜在机制可能与免疫抑制功能的激活及多条信号通路的活化有关。相应地，本研究通过DynNom包开发的网页版动态列线图工具，已成功实现患者生存率的快速精准计算。最后，对模型基因的多组学分析进一步丰富了本研究的内容。体外实验证实，敲低RAB19基因可促进胃腺癌细胞的迁移能力，而过表达该基因则会抑制上述细胞行为。本研究构建的胃腺癌预后模型，基于多组学分析与实验验证，具备精准高效的预测性能。此外，肿瘤微环境与m6A评分的相关性分析结果，为进一步探索胃腺癌的病理生理机制奠定了基础。