基于铂类耐药相关基因的卵巢癌分型和预后研究  

Classification and prognosis of ovarian cancer based on platinum resistance related genes

作　　者：孙莉君[1] 董大伟[1] SUN Lijun;DONG Dawei(Department of Pharmacy,Daqing People′s Hospital,Daqing 163316,China)

机构地区：[1]大庆市人民医院药剂科,大庆163316

出　　处：《实用肿瘤学杂志》2024年第3期184-191,共8页Practical Oncology Journal

摘　　要：目的本研究利用铂类耐药相关(Platinum resistance-related,PRR)基因对卵巢癌患者进行分型研究,建立预后风险模型,以期为卵巢癌患者临床个体化治疗及相关机制研究提供参考。方法利用单因素Cox回归分析筛选有预后价值的PRR基因,利用无监督共识聚类进行分型,并比较各亚型间预后差异;LASSO回归分析进一步筛选预后相关基因,构建PRR基因预后标签,联合临床信息,构建卵巢癌患者预后风险模型。结果单因素Cox回归分析筛选出68个与患者预后相关的PRR基因,无监督共识聚类获得2个卵巢癌亚型,C1组患者预后较好;12个基因用于构建PRR基因得分(Platinum resistance-related gene score,PRR-GS)预后标签,1、3、5年ROC曲线下面积均高于0.700。多因素Cox回归分析中,年龄、分期和PRR-GS为预后的独立影响因素,模型C指数为0.719,1、3、5年总生存率ROC曲线下面积分别为0.774、0.758、0.768,校准曲线和决策曲线分析表明模型预测效果良好。结论获得卵巢癌患者的2个亚型,各亚型在免疫微环境、预后等方面均存在差异;PRR-GS是独立危险因素,联合临床变量可有效预测患者生存结局。Objective This study aimed to use platinum resistance-related(PRR)genes to classify ovarian cancer(OV)patients and establish a prognostic risk model,in order to provide reference for individualized clinical treatment and related mechanism research of OV patients.Methods The univariate Cox regression was used to screen PRR genes with prognostic value,unsupervised consensus clustering was used for subtyping,and the prognostic differences were compared between subtypes.LASSO regression analysis was used to further screen prognosis related PRR genes and construct platinum resistance related gene scores(PRR-GS),combined with clinical information,constructed a prognostic risk model for OV patients,and validated it.Results Univariate Cox regression analysis identified 68 platinum resistance related genes that were associated with patient prognosis.Unsupervised consensus clustering identified 2 subtypes of OV,with C1 group patients having a better prognosis.Twelve genes were used to construct prognostic markers for PRR genes score,and the area under the ROC curves at 1,3,and 5 years were all above 0.700.Age,stage,and PRR-GS were independent factors affecting prognosis in multivariate Cox regression analysis.The model′s C-index was 0.719,and the areas under the ROC curves for 1-year,3-year,and 5-year overall survival rates were 0.774,0.758,and 0.768,respectively.The calibration curve and decision curve analysis showed that the model had good predictive performance.Conclusion Two subtypes of OV patients were identified,each with differences in immune microenvironment,prognosis,and other aspects.The platinum resistance gene prognostic score is an independent risk factor,and when combined with clinical variables,it can effectively predict patient survival outcomes.

关 键 词：卵巢癌 铂类耐药 分型 免疫微环境 预后 

分 类 号：R737.31[医药卫生—肿瘤]