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长链非编码 RNA 介导的环状 RNA 网络在甲状腺乳头状癌中的综合分析。

Comprehensive analysis of lncRNA-mediated ceRNA network in papillary thyroid cancer.

机构信息

Geriatric Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.

出版信息

Eur Rev Med Pharmacol Sci. 2020 Oct;24(19):10003-10014. doi: 10.26355/eurrev_202010_23214.

DOI:10.26355/eurrev_202010_23214
PMID:33090405
Abstract

OBJECTIVE

Papillary thyroid cancer (PTC) is one type of thyroid cancer. Although it has a good prognosis, the recurrence and metastasis rates remain high.

MATERIALS AND METHODS

The microarray dataset GSE66783 was downloaded from the Gene Expression Omnibus (GEO). With the R package, the differentially expressed genes (DEGs) and lncRNAs between normal adjacent tissues and cancer tissues of PTC were identified. The miRNAs that were targeted by DElncRNAs and the mRNAs that were targeted by miRNAs were discovered through miRcode and through miRTarBase, TargetScan, and miRDB, respectively. Furthermore, the ceRNA network was constructed. GO and KEGG enrichment analyses were performed on the DEGs. The PPI network of the DEGs was obtained from the STRING database, and the top 5 hub genes that had a tight correlation with the disease were obtained by using Cytoscape. Finally, the study used the Kaplan-Meier method to analyze PTC patient survival time, and the Human Protein Atlas database was used to retrieve the expression of the hub genes in normal and PTC patient tissues.

RESULTS

Five hub genes showed significant differences in expression in the PPI network, and 12 lncRNA-miRNA-mRNA pathways might participate in the potential pathophysiological process of PTC.

CONCLUSIONS

The study indicated that these ceRNAs might contribute to future therapies for PTC.

摘要

目的

甲状腺乳头状癌(PTC)是一种甲状腺癌。尽管它预后良好,但复发和转移率仍然很高。

材料与方法

从基因表达综合数据库(GEO)下载微阵列数据集 GSE66783。使用 R 包,鉴定 PTC 癌组织与正常邻近组织之间的差异表达基因(DEGs)和长链非编码 RNA(lncRNAs)。通过 miRcode 发现靶向 DElncRNAs 的 miRNAs,通过 miRTarBase、TargetScan 和 miRDB 发现靶向 miRNAs 的 mRNAs。此外,构建 ceRNA 网络。对 DEGs 进行 GO 和 KEGG 富集分析。从 STRING 数据库获取 DEGs 的 PPI 网络,并用 Cytoscape 获得与疾病相关性较强的前 5 个 hub 基因。最后,本研究采用 Kaplan-Meier 方法分析 PTC 患者的生存时间,并从人类蛋白质图谱数据库检索 hub 基因在正常和 PTC 患者组织中的表达。

结果

在 PPI 网络中,有 5 个 hub 基因的表达差异具有统计学意义,12 条 lncRNA-miRNA-mRNA 通路可能参与 PTC 的潜在病理生理过程。

结论

该研究表明,这些 ceRNAs 可能有助于未来 PTC 的治疗。

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