肾透明细胞癌线粒体相关lncRNA预后模型的建立

Establishment of a prognostic model for mitochondriaassociated lncRNA in clear cell carcinoma of kidney

目的:近年来对肾透明细胞癌(clear cell carcinoma of kidney,KIRC)的研究进展显著,但该疾病的预后较差,特别是在肿瘤转移的情况下。因此,寻找有效的预后指标和治疗靶点对提高KIRC患者的生存率和生活质量至关重要。本研究旨在探讨线粒体相关长非编码RNA(long non-coding RNA,lncRNA)在KIRC中的预后作用,并建立一个预后模型。方法:从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库中获取KIRC的RNA测序和临床数据,并从MitoCarta3.0数据库中提取线粒体基因列表。计算每个lncRNA与线粒体基因的相关系数,并筛选出显著相关的lncRNA。采用R软件的Cox回归分析结合Kaplan-Meier法筛选与KIRC预后相关的lncRNA。构建预后模型,根据模型计算每个样本的风险评分,并根据评分将其分为高风险组和低风险组,进而比较2组的生存期,利用受试者操作特征(receiver operator characteristic,ROC)曲线评估模型的预测能力,再使用Cox回归分析风险评分与患者临床特征的相关性。结果:相关系数筛选出31个与KIRC线粒体相关的lncRNA。Cox回归分析和Kaplan-Meier法筛选确定了6个与KIRC预后高度相关的lncRNA,并构建了其预后模型。该模型的ROC曲线下面积为0.723,表明该模型具有良好的预测能力。另外,风险评分与患者年龄、肿瘤分级、病理分期及T分期呈正相关,多因素Cox分析结果显示风险评分为KIRC的独立预后预测因子。结论:本研究建立的基于线粒体相关lncRNA的预后模型为KIRC患者提供了一个预后评估工具,这将有助于指导KIRC的个体化治疗和预后评估。

Objective:Significant progress has been made in the study of clear cell carcinoma of kidney(KIRC)in recent years,but the prognosis of this disease remains poor,especially in cases of tumor metastasis.Therefore,identifying effective prognostic indicators and therapeutic targets is crucial for improving the survival rate and quality of life of KIRC patients.This study aims to explore the prognostic role of mitochondrial-associated long noncoding RNA(lncRNA)in KIRC and establish a prognostic risk model.Methods:RNA sequencing and clinical data for KIRC were obtained from the Cancer Genome Atlas(TCGA)database,and a list of mitochondrial genes was extracted from the MitoCarta3.0 database.The correlation coefficient between each lncRNA and mitochondrial genes was calculated,and significantly correlated lncRNAs were identified.Prognosis-related lncRNAs were screened using Cox regression analysis combined with the Kaplan-Meier method in R software.A prognostic risk model was constructed,and the risk score for each sample was calculated according to the model.Samples were classified into a high-risk group and a low-risk groups according to their scores,and the survival times of the 2 groups were compared.The predictive ability of the model was assessed using the receiver operator characteristic(ROC)curve,and the correlation between the risk scores and clinical characteristics of patients was analyzed using Cox regression analysis.Results:A total of 31 mitochondria-associated lncRNAs related to KIRC were identified through correlation coefficient screening.Six lncRNAs highly associated with KIRC prognosis were selected to construct the prognostic model using Cox regression analysis and the Kaplan-Meier method.The area under the ROC curve for the model was 0.723,indicating good predictive ability.In addition,risk scores were positively correlated with patient age,tumor grade,pathological stage,and T stage.Multivariate Cox analysis showed that the risk score was an independent prognostic predictor for KIRC.Conclusion:The prognostic risk model based on mitochondria-associated lncRNAs provides a prognostic assessment tool for KIRC patients,which will help guide individualized treatment and prognosis assessment for KIRC.