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联合免疫相关性lncRNA和临床病理学特征建立肾透明细胞癌的预后模型 被引量:1

Establish of a prognostic model of renal clear cell carcinoma by combining immune-related lncRNA and clinicopathological characteristics
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摘要 目的旨在建立基于免疫相关长链非编码RNA(lncRNA)和临床病理学特征的新型肾透明细胞癌(ccRCC)预后模型,从而提高ccRCC患者的临床疗效及预后。方法在癌症基因组图谱(TCGA)数据库中下载ccRCC的基因表达数据。将TCGA基因表达数据与基因集富集分析(GSEA)数据库共表达分析,得到免疫相关的lncRNA。利用生存分析和Cox回归分析建立联合免疫相关lncRNA和临床病理特征的预后模型。利用Kaplan-Meier生存曲线验证预测模型的预后价值;利用受试者工作特征曲线下面积验证模型预测的准确性。结果从TCGA数据库下载了539例ccRCC组织数据和72例正常肾脏组织数据。得到了7个免疫相关的lncRNA,计算风险评分并组成预后模型。结合临床病理学特征(年龄、性别、肿瘤分级及肿瘤分期),建立联合预后模型。根据中位风险评分将患者分为高危组和低危组。结果显示,相对低危组而言,高危组患者的预后更差。联合预后模型C指数为0.78。结论联合预后模型具有优越的预测效能,该预后模型在预测ccRCC患者预后和指导临床治疗方面具有重要的临床意义。 Objective To establish a novel prognostic model of clear cell renal cell carcinoma(ccRCC)based on immune-related long non-coding RNA(lncRNA)and clinicopathological features,thereby improving the clinical efficacy and prognosis of ccRCC patients.Methods We downloaded gene expression data for ccRCC in The Cancer Genome Atlas(TCGA)database.The TCGA gene expression data were co-expressed with the Gene Set Enrichment Analysis(GSEA)database to obtain immune-related lncRNAs.Survival analysis and Cox regression analysis were used to establish a prognostic model combining immune-related lncRNAs and clinicopathological features.The Kaplan-Meier survival curve was used to verify the prognostic value of the prediction model,and the area under the ROC curve was used to verify the prediction accuracy of the model.Results A total of 539 ccRCC data and 72 normal kidney tissue data were downloaded from TCGA.Seven immune-related lncRNAs were obtained,risk scores were calculated and prognostic models were formed.Combined with clinicopathological features(age,gender,tumor grade and tumor stage),a combined prognostic model was established.According to the median risk score,patients were divided into high-risk and low-risk groups.Compared with the low-risk group,patients in the high-risk group had a worse prognosis.Combined prognostic model C index was 0.78.Conclusions The combined prognostic model has superior predictive performance,and the prognostic model has important clinical significance in predicting the prognosis of patients and guiding clinical treatment.
作者 叶硕鹏 林登强 陈凌宇 赖鹏 YE Shuopeng;LIN Dengqiang;CHEN Lingyu;LAI Peng(Department of Urology,Zhongshan Hospital,Fudan University(Xiamen branch),Xiamen 361015,China)
出处 《现代泌尿生殖肿瘤杂志》 2022年第5期308-312,共5页 Journal of Contemporary Urologic and Reproductive Oncology
关键词 肾透明细胞癌 长链非编码RNA 预后模型 癌症基因组数据库 Clear cell renal cell carcinoma Long non-coding RNA Prognostic model The Cancer Genome Atlas database
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