本研究的目标是在结肠腺癌中鉴定甲基化驱动基因并探索其预后价值。使用癌症基因组图谱（TCGA）数据库获取整理的结肠腺癌转录组基因表达矩阵（包含59,427个转录本）、转录组基因甲基化水平矩阵（包含29,602个甲基化改变的基因），其中包括517份样本，其中正常组织（NT）样本41份和结肠腺癌样本476份，并获取患者的临床信息文件（包括患者生存时间、生存状态、年龄、性别和肿瘤分期等）。通过对结肠腺癌转录表达矩阵进行差异表达基因（DEGs）分析，共获得9807个差异表达基因（DEGs），其中5874个上调表达，3933个下调表达。通过DEGs分析、基因甲基化水平差异分析以及二者之间的相关分析，获得了46个甲基化驱动差异表达基因（MD-DEGs）。然后，通过Cox回归分析，鉴定了三个与预后相关的甲基化驱动差异表达基因（PMD-DEGs）（IDUA、ZBTB18和C5orf38），并通过最小绝对收缩和选择算子（LASSO）回归分析和交叉验证分析构建了由这三个PMD-DEGs组成的预后模型。此外，采用生存分析、受试者工作特征（ROC）曲线分析和独立预后分析来评估和验证我们构建的预后模型能够准确且独立地预测结肠腺癌患者的预后。最后，我们基于预后模型构建了一个诊断病人存活预后的个人化Nomogram。综上所述，我们鉴定了结肠腺癌的甲基化驱动基因，并构建了一个预后模型和Nomogram来个人化预测患者的预后，为临床实践中的准确诊断和治疗开辟了新的前景。© 2023. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.

The objective of this study was to identify methylation-driven genes and explore their prognostic value in colon adenocarcinoma (COAD). The Cancer Genome Atlas (TCGA) database was used to acquire collated COAD transcriptome gene expression matrix (containing 59,427 transcripts), transcriptome gene methylation level matrix (containing 29,602 methylated modified genes), which included 517 samples containing 41 samples of normal tissue (NT) & 476 samples of COAD, and patient clinical information files (including patient survival time, survival status, age, gender and tumor stage, etc.), for all COAD samples. A total of 9807 differentially expressed genes (DEGs) were obtained by DEG analysis of the COAD transcriptional expression matrix, of which 5874 were up-regulated and 3933 were down-regulated. And 46 methylation-driven DEGs (MD-DEGs) in COAD were obtained by DEG analysis, differential analysis of gene methylation levels, and correlation analysis between them. Next, three prognostic associated MD-DEGs (PMD-DEGs) (IDUA, ZBTB18 and C5orf38) were identified by Cox regression analysis, and a prognostic model composed of the three PMD-DEGs was constructed by least absolute shrinkage and selection operator (LASSO) regression analysis and cross-validation analysis. In addition, survival analysis, the receiver operating characteristics (ROC) curve analysis and independent prognostic analysis were used to evaluate and verify that the prognostic model we constructed could accurately and independently predict the prognosis of COAD patients. Finally, we constructed a nomogram based on the prognosis model to accurately and personalized predict the survival prognosis of COAD patients. In conclusion, we identified the methylation driver gene of COAD and constructed a prognostic model and nomogram to personalized predict the prognosis of patients, which opened a new prospect for accurate diagnosis and treatment in clinical practice.© 2023. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.