Liu ZhenDong, Xu YuYang, Jin Shan, Liu Xin, Wang BaoChun
Department of General Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People's Republic of China.
Department of Anesthesiology, Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People's Republic of China.
Cancer Manag Res. 2023 Oct 5;15:1097-1110. doi: 10.2147/CMAR.S417897. eCollection 2023.
Colon adenocarcinoma (COAD) is the second leading cause of death in the world, and the new incidence rate ranks third among all cancers. Abnormal DNA methylation is related to the occurrence and development of tumors. In this study, we aimed to identify genes associated with abnormal methylation in COAD.
COAD transcriptome data, methylation data and clinical information were downloaded from the TCGA database and GEO database. The differentially expressed genes (DEGs) and methylated genes (DMGs) were analyzed and identified in COAD. PCA analysis was applied to divide COAD into subtypes, and the survival and immune cell infiltration of each subtype were evaluated. Cox and LASSO analyses were performed to construct COAD risk model. GSEA was used to evaluate the enrichment pathways. The Kaplan-Meier was used to analyze the difference in survival. ROC curve was plotted to evaluate the accuracy of the model, and GSE17536 was used to verify the accuracy of the risk model. The risk model is combined with the clinicopathological characteristics of COAD patients to perform multivariate Cox regression analysis to obtain independent risk factors and draw nomograms.
In total, 4564 DEGs and 1093 DMGs were screened, among which 298 were found to be overlapping genes. For 220 of these overlapping genes, the methylation was significantly negatively correlated to expression levels. An optimal signature from 4 methylated biomarkers was identified to construct the prognostic model.
Our study identified 4 methylated biomarkers in the COAD. Then, we constructed the risk model to provide a theoretical basis and reference value for the research and treatment of COAD.
结肠腺癌(COAD)是全球第二大致死原因,其新增发病率在所有癌症中排名第三。DNA甲基化异常与肿瘤的发生发展相关。在本研究中,我们旨在鉴定与COAD中甲基化异常相关的基因。
从TCGA数据库和GEO数据库下载COAD转录组数据、甲基化数据及临床信息。对COAD中的差异表达基因(DEGs)和甲基化基因(DMGs)进行分析和鉴定。应用主成分分析(PCA)将COAD分为不同亚型,并评估各亚型的生存情况和免疫细胞浸润情况。进行Cox和LASSO分析以构建COAD风险模型。使用基因集富集分析(GSEA)评估富集通路。采用Kaplan-Meier法分析生存差异。绘制ROC曲线评估模型的准确性,并使用GSE17536验证风险模型的准确性。将风险模型与COAD患者的临床病理特征相结合进行多因素Cox回归分析,以获得独立危险因素并绘制列线图。
共筛选出4564个DEGs和1093个DMGs,其中发现298个重叠基因。在这些重叠基因中的220个中,甲基化与表达水平显著负相关。从4个甲基化生物标志物中鉴定出一个最佳特征来构建预后模型。
我们的研究在COAD中鉴定出4个甲基化生物标志物。然后,我们构建了风险模型,为COAD的研究和治疗提供理论依据和参考价值。