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基于生物信息学分析鉴定和交互分析甲状腺髓样癌中的关键 miRNAs。

Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis.

机构信息

Tumor Diagnosis and Treatment Center, PLA 901 Hospital, Hefei, Anhui 230031, P.R. China.

General Surgery Department, PLA 901 Hospital, Hefei, Anhui 230031, P.R. China.

出版信息

Mol Med Rep. 2019 Sep;20(3):2316-2324. doi: 10.3892/mmr.2019.10463. Epub 2019 Jul 3.

DOI:10.3892/mmr.2019.10463
PMID:31322209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6691269/
Abstract

Medullary thyroid carcinoma (MTC) is an endocrine tumor and comprises 5‑10% of all primary thyroid malignancies. However, the biomechanical contribution to the development and progression of MTC remains unclear. In this study, To discover the key microRNAs (miRNAs or miRs) and their potential roles in the tumorigenesis of MTC, the microarray datasets GSE97070, GSE40807 and GSE27155 were analyzed. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed miRNAs (DEMs) and genes (DEGs) were accessed by R. Targets of DEMs and predicted using starBase, and functional and pathway enrichment analyses were performed using Metascape. A protein‑protein interaction (PPI) network and an analysis of modules were constructed using NetworkAnalyst. Finally, a network was constructed to show the regulatory association between transcription factors (TFs), DEMs and downstream genes. A total of 5 DEMs were found both in GSE97070 and GSE40807, including 3 upregulated DEMs and 2 downregulated DEMs. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from Metascape revealed that the target genes of upregulated DEMs were significantly enriched in adherens junction, kinase and protein binding, while the target genes of downregulated DEMs were mainly involved in non‑canonical Wnt signaling pathway and RNA transport. From the PPI network, 13 nodes were screened as hub genes. Pathway enrichment analysis revealed that the top 5 modules were mostly enriched in the neurotrophin signaling pathway, mRNA surveillance pathway and MAPK signaling pathway. In addition, the TF‑DEMs‑target gene and DEGs regulatory network revealed that 17 TFs regulated 2 miRNAs, including upregulated or downregulated DEMs, CREB1 regulated all upregulated DEMs, and TGFB1 was an activator of hsa‑miR‑199a‑3p and a repressor of hsa‑miR‑429. Taken together, the present study identified several miRNAs and potential biological mechanisms involved in the tumorigenesis of MTC. This study identified the key DEMs and potential mechanisms underlying the development of MTC, and provided a series of biomarkers and targets for the management of MTC.

摘要

甲状腺髓样癌 (MTC) 是一种内分泌肿瘤,占所有原发性甲状腺恶性肿瘤的 5-10%。然而,其在肿瘤发生和进展中的生物力学贡献尚不清楚。在这项研究中,为了发现关键的 microRNAs (miRNAs 或 miRs) 及其在 MTC 肿瘤发生中的潜在作用,分析了 microarray 数据集 GSE97070、GSE40807 和 GSE27155。这些数据集从基因表达综合 (GEO) 数据库中下载。使用 R 访问差异表达的 miRNAs (DEMs) 和基因 (DEGs)。使用 starBase 预测 DEMs 的靶标,并使用 Metascape 进行功能和途径富集分析。使用 NetworkAnalyst 构建蛋白质-蛋白质相互作用 (PPI) 网络和模块分析。最后,构建了一个网络来显示转录因子 (TFs)、DEMs 和下游基因之间的调控关联。在 GSE97070 和 GSE40807 中均发现了 5 个 DEMs,包括 3 个上调的 DEMs 和 2 个下调的 DEMs。Metascape 的基因本体论 (GO) 和京都基因与基因组百科全书 (KEGG) 途径富集分析表明,上调 DEMs 的靶基因显著富集于粘着连接、激酶和蛋白结合,而下调 DEMs 的靶基因主要参与非经典 Wnt 信号通路和 RNA 运输。从 PPI 网络中筛选出 13 个节点作为枢纽基因。途径富集分析表明,前 5 个模块主要富集于神经生长因子信号通路、mRNA 监测途径和 MAPK 信号通路。此外,TF-DEMs-靶基因和 DEGs 调控网络表明,17 个 TFs 调控 2 个 miRNAs,包括上调或下调的 DEMs,CREB1 调控所有上调的 DEMs,TGFB1 是 hsa-miR-199a-3p 的激活剂,也是 hsa-miR-429 的抑制剂。综上所述,本研究鉴定了一些 miRNAs 和参与 MTC 肿瘤发生的潜在生物学机制。本研究鉴定了 MTC 发生的关键 DEMs 和潜在机制,为 MTC 的治疗提供了一系列生物标志物和靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/3acb5a7c2a7b/MMR-20-03-2316-g04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/e62b2642ddba/MMR-20-03-2316-g00.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/91b78b49c2ca/MMR-20-03-2316-g01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/a0255a0cfd87/MMR-20-03-2316-g02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/3aabd1cf3d1e/MMR-20-03-2316-g03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/3acb5a7c2a7b/MMR-20-03-2316-g04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/e62b2642ddba/MMR-20-03-2316-g00.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/91b78b49c2ca/MMR-20-03-2316-g01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/a0255a0cfd87/MMR-20-03-2316-g02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/3aabd1cf3d1e/MMR-20-03-2316-g03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6691269/3acb5a7c2a7b/MMR-20-03-2316-g04.jpg

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