基于循环肿瘤DNA甲基化的结直肠癌筛查预测模型的构建与验证  

Construction and validation of a predictive model for screening of colorectal cancer based on circulating tumor DNA methylation

作　　者：孙晗 于冰 武侠[1] 周熙朗 Sun Han;Yu Bing;Wu Xia;Zhou Xilang(Department of Gastroenterology,Xuzhou Central Hospital,Xuzhou 221000,China;Department of Outpatient,Xuzhou Civil and Mental Hospital,Xuzhou 221000,China)

机构地区：[1]徐州市中心医院消化内科,江苏省221000 [2]徐州市民政精神病医院门诊,江苏省221000

出　　处：《中华消化病与影像杂志（电子版）》2024年第6期500-506,共7页Chinese Journal of Digestion and Medical Imageology(Electronic Edition)

基　　金：徐州市卫生健康委科技计划青年项目(XWKYHT20230080)。

摘　　要：目的探讨循环肿瘤DNA(ctDNA)甲基化预测结直肠癌(CRC)模型构建与验证。方法2021年8月至2023年7月前瞻性收集徐州市中心医院收治的CRC患者作为研究对象(CRC组),同时期年龄和性别匹配的健康体检者作为对照组。比较两组相关临床资料、血清ctDNA甲基化水平;通过公共数据库“Marmal-aid”获得CRC的DNA甲基化标志物;通过LASSO和RF分析筛选DNA甲基化标志物;通过ROC曲线和Logistic多因素回归分析,构建基于筛选的DNA甲基化标志物预测CRC的模型;通过训练队列和验证队列分别明确本模型对CRC的预测效能。结果通过公共数据库进行筛选,共鉴定出3997个差异性DNA甲基化CpG(DMCs),并通过分层聚类和KEGG显示出CRC和正常结直肠黏膜在这些DMCs中不同的甲基化模式及富集通路,并逐步筛选保留了19个甲基化标志物。通过LASSO和RF分析评估了19个标志物的稳定性,获得了3个DNA甲基化标志物(cg08131100、cg16934178和cg24171907),预测CRC的AUC分别为0.887、0.841和0.715。Logistic回归分析显示,cg08131100、cg16934178和cg24171907是影响CRC发病的独立危险因素;在训练队列和验证队列中,CRC的甲基化评分均显著高于对照组;通过ROC曲线评价甲基化模型预测CRC的效能,模型在训练组AUC为0.841(95%CI0.756~0.927),模型在验证组AUC为0.823(95%CI 0.728~0.919)。结论本研究基于ctDNA甲基化构建了预测CRC患者的模型,为CRC的无创检测和筛查提供了具有临床转化意义的工具。Objective To investigate the construction and validation of a model for prediction of colorectal cancer(CRC)by circulating tumor DNA(ctDNA)methylation.Methods Prospectively enrolled colorectal cancer patients between August 2021 and July 2023 were selected as the study subjects(CRC group),and age-and gender-matched healthy medical check-ups in the same period served as the control group.The two groups were compared in terms of clinical data and serum ctDNA methylation levels;DNA methylation markers of CRC were obtained from the public database“Marmal-aid”;DNA methylation markers were screened by LASSO and RF analyses.The model of CRC prediction based on the screened DNA methylation markers was constructed by ROC curve and logistic multifactorial regression analysis;the prediction efficacy of the model for CRC was clarified by the training cohort and validation cohort,respectively.Results A total of 3997 differentially DNA methylated CpGs(DMCs)were identified by screening through public databases,and 19 methylation markers were retained by stepwise screening through hierarchical clustering and KEGG showing the different methylation patterns and enrichment pathways between CRC and normal colorectal mucosa in these DMCs.The stability of the 19 markers was assessed by LASSO and RF analyses,and three DNA methylation markers(cg08131100,cg16934178,and cg24171907)were obtained,with predicted AUCs of 0.887,0.841,and 0.715 for CRC,respectively.Logistic regression analyses showed that cg08131100,cg16934178 and cg24171907 were independent risk factors influencing the onset of CRC;the methylation scores of CRC were significantly higher than those of the control group in both the training and validation cohorts;and the efficacy of the methylation model in predicting CRC was evaluated by ROC curves,and the model had an AUC of 0.841 in the training group(95%CI:0.756-0.927),and the AUC of the model in the validation group was 0.823(95%CI:0.728-0.919).Conclusion This study constructs a model for prediction of CRC patients base

关 键 词：结直肠癌 循环肿瘤DNA 甲基化 预测模型 

分 类 号：R735.34[医药卫生—肿瘤]