ATP结合盒转运蛋白家族与膀胱癌免疫治疗效果的关联性分析  

Analysis of the association between ATP-binding cassette transporter family and the efficacy of immunotherapy for bladder cancer

作　　者：王廷正 张青[2] 郭宏骞[1,2] WANG Tingzheng;ZHANG Qing;GUO Hongqian(Drum Tower Clinical Medicine College of Nanjing Medical University,Nanjing 210029;Department of Urology,Nanjing Drum Tower Hospital,The Affiliated Hospital of Nanjing University Medical School,Nanjing 210008,China)

机构地区：[1]南京医科大学鼓楼临床医学院,江苏南京210029 [2]南京大学医学院附属鼓楼医院泌尿外科,江苏南京210008

出　　处：《现代泌尿外科杂志》2024年第12期1033-1038,共6页Journal of Modern Urology

基　　金：国家自然科学基金项目(No.82072822)。

摘　　要：目的基于IMvigor210和UNC-108(GSE176307)数据集分析探讨ATP结合盒(ABC)转运蛋白家族在膀胱癌患者免疫治疗中的临床应用价值。方法从IMvigor210数据集下载348例接受免疫治疗的膀胱尿路上皮癌患者的基因表达数据,将患者基于ABC转运蛋白家族基因表达水平进行共识聚类,分为聚类1和聚类2进行生存分析。通过单因素Cox回归分析筛选出对预后有影响的ABC转运蛋白家族基因,使用随机生存森林算法构建ABC评分预测模型,用于预测患者的生存期及免疫治疗反应,利用UNC-108数据集进一步验证模型的准确性。最后,采用ESTIMATE、ssGSEA算法评估患者的肿瘤微环境情况、oncoPredict算法预测患者对化疗药物顺铂的敏感性。结果筛选出9个ABC转运蛋白家族基因用于构建ABC评分预测模型。在IMvigor210队列中,Kaplan-Meier生存分析显示ABC评分低的患者总生存时间明显长于ABC评分高的患者(P<0.001);ABC评分模型对患者0.5年、1年和1.5年生存预测的受试者工作特征曲线下面积(AUC)分别为0.80、0.87和0.88;ABC评分对免疫治疗效果的预测能力的AUC为0.78,高于肿瘤突变负荷(AUC:0.72)和程序性死亡受体配体1(AUC:0.58)。ABC评分在UNC-108验证队列中也有着良好的预测效果。ABC评分与肿瘤微环境、多种免疫细胞、免疫表型、免疫评分、免疫检查点基因表达情况显著相关。结论ABC转运蛋白家族与膀胱癌的肿瘤微环境、免疫治疗效果关系密切,有望成为膀胱癌免疫治疗的新型生物标志物。Objective To investigate the clinical utility of ATP-binding cassette transporter family in immunotherapy for bladder cancer based on IMvigor210 and UNC-108(GSE176307)datasets.Methods Gene expression data of 348 patients with bladder urothelial carcinoma were downloaded from the IMvigor210 database.Firstly,consensus clustering was performed to the gene expression levels of the ATP-binding cassette transporter family,resulting in two clusters:Cluster 1 and Cluster 2.Survival analysis was conducted between the two clusters.Next,univariate Cox regression was employed to identify ATP-binding cassette transporter family genes significantly affecting prognosis.A predictive model was constructed using the random survival forest algorithm to predict treatment response and survival outcomes in patients with bladder cancer receiving immunotherapy.The model s accuracy was validated with UNC-108 dataset.Then,ESTIMATE and ssGSEA were applied to analyze differences in the tumor microenvironment.Furthermore,oncoPredict algorithm was used to predict the sensitivity of patients to cisplatin.Results A total of 9 ATP-binding cassette transporter family genes were selected to construct the ABC score predictive model.In the IMvigor210 datasets,the Kaplan-Meier analysis revealed that patients with low ABC score had significantly longer overall survival compared to those with high ABC score(P<0.001).The ABC score model demonstrated good performance with area under the ROC curve(AUC)of 0.80,0.87,and 0.88 for predicting 0.5-year,1-year,and 1.5-year survival,respectively.The predictive ability of the ABC score for immunotherapy response,with an AUC of 0.78,outperformed that of TMB(AUC:0.72)and PD-L1(AUC:0.58).The ABC score also exhibited favorable predictive performance in the UNC-108 validation cohort.ABC score was also significantly correlated with tumor microenvironment immune scores,various immune cells,and the expression of immune checkpoint genes.Conclusion ATP-binding cassette transporter family is closely associated with the tumor

关 键 词：膀胱癌 ATP结合盒转运蛋白 免疫治疗 肿瘤微环境 基因 预测模型 生存分析 顺铂 

分 类 号：R737.14[医药卫生—肿瘤]