南方医科大学学报

南方医科大学学报 ›› 2024, Vol. 44 ›› Issue (4): 727-738.doi: 10.12122/j.issn.1673-4254.2024.04.15

• • 上一篇    下一篇

基于高通量 RNA 测序分析 Wilms 瘤中关键基因对预后及免疫应答的影响

高志强，林 洁，洪 鹏，胡再宏，董军君，石秦林，田小毛，刘 丰，魏光辉   

  1. 重庆医科大学附属儿童医院泌尿外科//国家儿童健康与疾病临床医学研究中心//儿童发育疾病研究教育部重点实验室//结构性出生缺陷与器官修复重建重庆市重点实验室，重庆 400014
  • 发布日期:2024-04-29

Identification of key genes in Wilms tumor based on high- throughput RNA sequencing and their impacts on prognosis and immune responses

GAO Zhiqiang, LIN Jie, HONG Peng, HU Zaihong, DONG Junjun, SHI Qinlin, TIAN Xiaomao, LIU Feng, WEI Guanghui   

  1. Department of Urological Surgery, Children's Hospital of Chongqing Medical University; National Clinical Research Center for Child Health and Disorders; Ministry of Education Key Laboratory of Child Development and Disorders; Chongqing Key Laboratory of Structural Birth Defect and Reconstruction, Chongqing 400014, China
  • Published:2024-04-29

RichHTML

17

PDF

372

摘要： 目的 探索肾母细胞瘤（WT）中关键基因及其对预后和免疫应答的潜在影响。方法 采用高通量RNA测序技术分析临床肿瘤样本和配对正常组织的mRNA全面表达谱，并鉴定差异表达基因。使用GO、KEGG和GSEA富集分析探索差异表达基因在肾母细胞瘤中的潜在生物学功能和机制。使用STRING数据库鉴定HUB基因。LASSO回归用于构建HUB基因预后模型。基于cBioPortal平台分析关键HUB基因的突变特征并对其免疫治疗效果进行预测。采用qPCR验证关键HUB基因的差异表达。结果 本研究筛选出1612个差异表达基因，其中1030个上调，582个下调。GO、KEGG或GSEA富集分析显示，差异基因集与细胞周期和免疫应答有关，一定程度上参与了WT的发生发展。基于STRING数据库构建差异基因的PPI网络，进一步确定了10个HUB基因。其中4个HUB基因（TP53、MED1、CCNB1和EGF）被证实与WT患儿的生存密切相关。通过LASSO回归分析构建WT患者的三基因预后签名，根据该签名将患者分为高危或低危组，生存分析显示显著的预后差异（HR=1.814, Log-rank P=0.002）。该模型的3年、5年和7年生存ROC曲线的AUC值均大于0.7。突变分析显示，关键HUB基因整体突变或TP53/CCNB1的单独突变与较低的生存率密切相关，其中TP53高表达与较差的免疫治疗疗效有关。qPCR结果显示，关键HUB基因在肿瘤组织和细胞中呈现出显著的表达差异。结论 TP53基因在WT中发挥重要作用，可能成为新的免疫治疗生物标志物和治疗靶点。

关键词: Wilms瘤；肾母细胞瘤；RNA测序；分子标志物；免疫微环境；预后模型

Abstract: Objective To identify the key genes differentially expressed in Wilms tumor and analyze their potential impacts on prognosis and immune responses of the patients. Methods High-throughput RNA sequencing was used to identify the differentially expressed mRNAs in clinical samples of Wilms tumor and paired normal tissues, and their biological functions were analyzed using GO, KEGG and GSEA enrichment analyses. The hub genes were identified using STRING database, based on which a prognostic model was constructed using LASSO regression. The mutations of the key hub genes were analyzed and their impacts on immunotherapy efficacy was predicted using the cBioPortal platform. RT-qPCR was used to verify the differential expressions of the key hub genes in Wilms tumor. Results Of the 1612 differentially expressed genes identified in Wilms tumor, 1030 were up-regulated and 582 were down-regulated, involving mainly cell cycle processes and immune responses. Ten hub genes were identified, among which 4 genes (TP53, MED1, CCNB1 and EGF) were closely related to the survival of children with Wilms tumor. A 3-gene prognostic signature was constructed through LASSO regression analysis, and the patients stratified into with high- and low- risk groups based on this signature had significantly different survival outcomes (HR=1.814, log-rank P=0.002). The AUCs of the 3-, 5- and 7-year survival ROC curves of this model were all greater than 0.7. The overall mutations in the key hub genes or the individual mutations in TP53/CCNB1 were strongly correlated with a lower survival rates, and a high TP53 expression was correlated with a poor immunotherapy efficacy. RT-qPCR confirmed that the key hub genes had significant differential expressions in Wilms tumor tissues and cells. Conclusion TP53 gene plays an important role in the Wilms tumor and may potentially serve as a new immunotherapeutic biomarker as well as a therapeutic target.

Key words: Wilms tumor; nephroblastoma; RNA sequencing; prognostic markers; immune microenvironment; prognostic model