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基于免疫细胞浸润评分实现膀胱癌分型及预后风险评估

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目的:基于免疫细胞浸润评分实现膀胱癌患者分型并构建预后风险评估模型。方法:首先从癌症基因组图谱(TCGA)数据库下载膀胱癌患者的转录组数据和临床数据。然后,采用单样本基因集富集分析方法计算16种免疫细胞的浸润评分。接着,通过无监督聚类实现膀胱癌患者的分型并分析不同分型的患者对免疫治疗和化疗药物敏感性的差异。随后,通过加权相关网络分析(WGCNA)识别与关键免疫细胞浸润显著相关的关键模块,并提取模块内的关键基因。最后,构建并验证膀胱癌预后相关的风险评分模型,并结合患者临床特征构建列线图并进行验证。结果:计算得到正常组织和肿瘤组织的免疫细胞浸润评分,确定B细胞、肥大细胞、中性粒细胞、辅助性T细胞和肿瘤浸润淋巴细胞为膀胱癌的关键免疫细胞。基于免疫细胞浸润评分将膀胱癌患者聚类为两类(聚类1´和聚类2)。与聚类1´患者比较,聚类2患者更能从免疫治疗中获益(P<0。05),且聚类 2患者对恩贝酸、多西他赛、环巴胺和阿卡地新更为敏感(P<0。05)。通过WGCNA筛选出35个与关键免疫细胞相关的基因,经LASSO Cox回归进一步筛选出四个与膀胱癌预后相关的基因(GPR171、HOXB3、HOXB5和HOXB6)。基于这四个基因构建的膀胱癌预后风险评分模型预测患者1、3、5年预后的曲线下面积分别为0。735、0。765、0。799。结合风险评分和临床参数构建的列线图预测膀胱癌患者1、3、5年总存活率的准确性较高。结论:根据免疫细胞浸润评分可以实现膀胱癌患者分型,基于关键免疫细胞相关基因构建的膀胱癌预后风险评分模型及列线图对于膀胱癌患者预后预测的准确性较好。
Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis
Objective:To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.Methods:The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas(TCGA)database.Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells.The classification of breast cancer patients was achieved by unsupervised clustering,and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed.The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis(WGCNA),and the key genes in the modules were identified.A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.Results:B cells,mast cells,neutrophils,T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer.The patients were clustered into two groups(Cluster 1´ and Custer 2)based on immune cell infiltration scores.Compared with patients with Cluster 1´,patients with Cluster 2 were more likely to benefit from immunotherapy(P<0.05),and patients with Cluster 2 were more sensitive to Enbeaten,Docetaxel,Cyclopamine,and Akadixin(P<0.05).35 genes related to key immune cells were screened out by WGCNA and 4 genes(GPR171,HOXB3,HOXB5 and HOXB6)related to the prognosis of bladder cancer were further screened by LASSO Cox regression.The areas under the ROC curve(AUC)of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-,3-and 5-year survival of patients were 0.735,0.765 and 0.799,respectively.The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-,3-,and 5-year overall survival of bladder cancer patients.Conclusions:According to the immune cell infiltration score,bladder cancer patients can be classified.Furthermore,bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Bladder cancerImmune infiltrationImmunotherapyPrognostic modelNomogram

殷桂草、郑生旗、张伟、董欣、祁乐中、李一帆

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扬州大学附属医院泌尿外科,江苏 扬州 225000

扬州大学护理学院 公共卫生学院,江苏 扬州 225000

膀胱癌 免疫浸润 免疫治疗 预后模型 列线图

国家自然科学基金江苏省科技计划青年基金扬州市重点研发计划社会发展项目扬州市软科学研究计划江苏省博士后研究资助计划扬州大学高层次人才研究启动基金

82002675BK2020938YZ2020110YZ20222672020Z2682019LYF

2024

浙江大学学报(医学版)
浙江大学

浙江大学学报(医学版)

CSTPCD北大核心
影响因子:0.926
ISSN:1008-9292
年,卷(期):2024.53(1)
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