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肾母细胞瘤中与生存相关的预后性长链非编码RNA、微小RNA和信使RNA竞争性内源性RNA网络

A Survival-Related Competitive Endogenous RNA Network of Prognostic lncRNAs, miRNAs, and mRNAs in Wilms Tumor.

作者信息

Liu HengChen, Zhang MingZhao, Shi ManYu, Zhang TingTing, Zhang ZeNan, Cui QingBo, Yang ShuLong, Li ZhaoZhu

机构信息

Department of Pediatric Surgery, The Second Hospital Affiliated to Harbin Medical University, Harbin, China.

出版信息

Front Oncol. 2021 Feb 26;11:608433. doi: 10.3389/fonc.2021.608433. eCollection 2021.

Abstract

Wilms tumor (WT) commonly occurs in infants and children. We evaluated clinical factors and the expression of multiple RNAs in WT samples in the TARGET database. Eight long non-coding RNAs (lncRNAs; AC079310.1, MYCNOS, LINC00271, AL445228.3, Z84485.1, AC091180.5, AP002518.2, and AC007879.3), two microRNAs (miRNAs; hsa-mir-152 andhsa-mir-181a), and nine messenger RNAs (mRNAs; TCTEX1D4, RNF133, VRK1, CCNE1, HEY1, C10orf71, SPRY1, SPAG11A, and MAGEB18) were screened from differentially expressed RNAs and used to construct predictive survival models. These models showed good prognostic ability and were highly correlated with tumor stage and histological classification. Additionally, survival-related ceRNA network was constructed using 35 RNAs (15 lncRNAs, eight miRNAs, and 12 mRNAs). KEGG pathway analysis suggested the "Wnt signaling pathway" and "Cellular senescence" as the main pathways. In conclusion, we established a multinomial predictive survival model and a survival-related ceRNA network, which provide new potential biomarkers that may improve the prognosis and treatment of WT patients.

摘要

肾母细胞瘤(WT)常见于婴幼儿。我们在TARGET数据库中评估了WT样本的临床因素及多种RNA的表达情况。从差异表达的RNA中筛选出8种长链非编码RNA(lncRNA;AC079310.1、MYCNOS、LINC00271、AL445228.3、Z84485.1、AC091180.5、AP002518.2和AC007879.3)、2种微小RNA(miRNA;hsa - mir - 152和hsa - mir - 181a)以及9种信使RNA(mRNA;TCTEX1D4、RNF133、VRK1、CCNE1、HEY1、C10orf71、SPRY1、SPAG11A和MAGEB18),并用于构建预测生存模型。这些模型显示出良好的预后能力,且与肿瘤分期和组织学分类高度相关。此外,利用35种RNA(15种lncRNA、8种miRNA和12种mRNA)构建了生存相关的竞争性内源性RNA(ceRNA)网络。KEGG通路分析表明“Wnt信号通路”和“细胞衰老”是主要通路。总之,我们建立了一个多项预测生存模型和一个生存相关的ceRNA网络,它们提供了可能改善WT患者预后和治疗的新潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a726/7953909/866a7d1e379c/fonc-11-608433-g001.jpg

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