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一种新的与RNA结合蛋白相关的特征可预测结肠腺癌患者的预后。

A New RBPs-Related Signature Predicts the Prognosis of Colon Adenocarcinoma Patients.

作者信息

Chang Kaili, Yuan Chong, Liu Xueguang

机构信息

Department of Pathology, School of Basic Medical Sciences, Fudan University, Shanghai, China.

出版信息

Front Oncol. 2021 Mar 9;11:627504. doi: 10.3389/fonc.2021.627504. eCollection 2021.

Abstract

The dysregulation of RNA binding proteins (RBPs) is closely related to tumorigenesis and development. However, the role of RBPs in Colon adenocarcinoma (COAD) is still poorly understood. We downloaded COAD's RNASeq data from the Cancer Genome Atlas (TCGA) database, screened the differently expressed RBPs in normal tissues and tumor, and constructed a protein interaction network. COAD patients were randomly divided into a training set (N = 315) and a testing set (N = 132). In the training set, univariate Cox analysis identified 12 RBPs significantly related to the prognosis of COAD. By multivariate COX analysis, we constructed a prognostic model composed of five RBPs (CELF4, LRRFIP2, NOP14, PPARGC1A, ZNF385A) based on the lowest Akaike information criterion. Each COAD patient was scored according to the model formula. Further analysis showed that compared with the low-risk group, the overall survival rate (OS) of patients in the high-risk group was significantly lower. The area under the curve of the time-dependent receiver operator characteristic (ROC) curve was 0.722 in the training group and 0.738 in the test group, which confirmed a good prediction feature. In addition, a nomogram was constructed based on clinicopathological characteristics and risk scores. C-index and calibration curve proved the accuracy in predicting the 1-, 3-, and 5-year survival rates of COAD patients. In short, we constructed a superior prognostic and diagnostic signature composed of five RBPs, which indicates new possibilities for individualized treatment of COAD patients.

摘要

RNA结合蛋白(RBPs)的失调与肿瘤的发生和发展密切相关。然而,RBPs在结肠腺癌(COAD)中的作用仍知之甚少。我们从癌症基因组图谱(TCGA)数据库下载了COAD的RNA测序数据,筛选出正常组织和肿瘤中差异表达的RBPs,并构建了一个蛋白质相互作用网络。COAD患者被随机分为训练集(N = 315)和测试集(N = 132)。在训练集中,单因素Cox分析确定了12个与COAD预后显著相关的RBPs。通过多因素COX分析,我们基于最低赤池信息准则构建了一个由五个RBPs(CELF4、LRRFIP2、NOP14、PPARGC1A、ZNF385A)组成的预后模型。根据模型公式对每位COAD患者进行评分。进一步分析表明,与低风险组相比,高风险组患者的总生存率(OS)显著更低。训练组中时间依赖的受试者工作特征(ROC)曲线下面积为0.722,测试组中为0.738,证实了良好的预测特征。此外,基于临床病理特征和风险评分构建了列线图。C指数和校准曲线证明了预测COAD患者1年、3年和5年生存率的准确性。简而言之,我们构建了一个由五个RBPs组成的优良预后和诊断标志物,这为COAD患者的个体化治疗指明了新的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/045a/7985171/c11bef37d5c2/fonc-11-627504-g001.jpg

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