基于ADME相关基因标记构建和验证子宫内膜癌预后风险评分模型  

Construction and Validation of Prognostic Risk Scoring Model for Uterine Corpus Endometrial Carcinoma Based on ADME-related Gene Markers

作　　者：禚映辰 张素雅 宋鹏飞 封卫毅[1] ZHUO Yingchen;ZHANG Suya;SONG Pengfei;FENG Weiyi(Department of Pharmacy,the First Affiliated Hospital of Xi’an Jiaotong University,Xi'an 710061,China)

机构地区：[1]西安交通大学第一附属医院药学部,西安710061

出　　处：《医药导报》2024年第6期970-976,共7页Herald of Medicine

基　　金：陕西省自然科学基础研究计划项目(2022JM-589)。

摘　　要：目的基于控制药物吸收、分布、代谢和排泄(ADME)过程的ADME基因,构建子宫内膜癌(UCEC)预后模型,为预测UCEC的预后及肿瘤治疗提供参考。方法从TCGA数据库和ICGC数据库中收集UCEC患者的基因表达谱以及临床数据。使用单因素Cox回归分析确定与UCEC预后相关的ADME基因,使用最小绝对收缩与选择算子(LASSO)回归筛选出最佳预后基因并构建风险评分模型。采用Kaplan-Meier生存分析和受试者工作特征曲线(ROC)评估其预测能力,以R软件筛选差异表达基因并进行功能富集分析。结果筛选出9个ADME基因(DHRS7B、CYP46A1、SLCO4C1、NR1I2、SLC16A1、SLCO3A1、ARSA、ABCC5、MGST2)用于构建UCEC预后风险评分模型。生存分析显示,低风险评分组患者的生存时间明显长于高风险评分组患者(训练集:P<0.001;验证集P=0.032)。训练集ROC曲线显示1、3和5年的曲线下面积分别为0.792、0.724和0.712,验证集分别为0.651、0.620和0.677,提示该预后风险评分模型对UCEC患者的生存状态具有良好的预测能力。单因素和多因素Cox回归分析显示,风险评分可作为UCEC潜在的独立预后因素(HR=1.77,P=0.035)。高风险评分组和低风险评分组在miRNA介导的基因沉默、调控血管内皮细胞增殖与新生血管生成和萌芽血管生成的生物学过程中存在差异。结论该研究筛选出的9个ADME基因所构建的预后风险评分模型可用于评估UCEC患者的预后。Objective To construct a prognostic model for uterine corpus endometrial carcinoma(UCEC)using the prognosis-associated ADME genes involved in controlling drug absorption,distribution,metabolism,and excretion(ADME),providing a reference for predicting the prognosis of UCEC and tumor treatment.Methods The gene expression and clinical information data of UCEC were obtained from the TCGA and ICGC databases.Prognosis-related ADME genes were screened using the univariate Cox regression analysis.Least absolute shrinkage and selection operator(LASSO)regression was used to identify optimal prognostic genes,and then a risk score model was constructed.Kaplan-Meier curve and receiver operating characteristic(ROC)curve were constructed to assess predictive capability.R software was used to perform differentially expressed genes analysis,functional enrichment analysis.Results A nine-gene signature(DHRS7B,CYP46A1,SLCO4C1,NR1I2,SLC16A1,SLCO3A1,ARSA,ABCC5,MGST2)was used for constructing a risk score model.Survival analysis showed that the survival time in high-risk patients was significantly shorter than in low-risk patients(the train set:P<0.001;the test set:P=0.032).The areas under the ROC curve of the train set and the test set for ROC at 1,3,5 years were 0.792,0.724,0.712,and 0.651,0.620,0.677,respectively.Univariate and multivariate Cox regression analysis showed that the risk score was an independent risk factor for UCEC(HR=1.77,P=0.035).In addition,there was a significant difference in the miRNA-mediated silencing and regulation of sprouting angiogenesis pathways between the high-risk and low-risk score groups.Conclusion The prognosis model constructed with nine key ADME genes may have the potential to be used for predicting the survival prognosis of patients with UCEC.

关 键 词：子宫内膜癌 预后预测模型 基因标记 癌症基因组图谱 

分 类 号：R969.1[医药卫生—药理学] R737.77[医药卫生—药学]