Suppr超能文献

骨肉瘤 miRNA-mRNA 调控网络的生物标志物筛选与分析。

Screening and Analysis of Biomarkers in the miRNA-mRNA Regulatory Network of Osteosarcoma.

机构信息

Department of Orthopedics, The Fourth Medical Center of General Hospital of PLA, Beijing 100048, China.

出版信息

J Healthc Eng. 2022 Mar 15;2022:8055052. doi: 10.1155/2022/8055052. eCollection 2022.

Abstract

Osteosarcoma is a malignant disease, and few effective strategies can completely overcome the prognosis of these patients. This study attempted to reveal the key factors and related molecular mechanisms of osteosarcoma via excavating public microarray datasets. The data were obtained from the Gene Expression Omnibus (GEO) database; the differentially expressed miRNAs and differentially expressed genes were obtained in GSE69470 and GSE12685l, respectively; the target of miRNAs were predicted with the miRDIP database; the functions of the factors were analyzed and visualized by the David database and R language, respectively. Moreover, the protein-protein interaction network and miRNA-mRNA network were performed with the STRING database and Cytoscape software to identify the hub nodes in GSE69470 and GSE12685. The results showed that 834 DEGs were found in GSE12685 and 37 miRNAs were found in GSE69470. Moreover, the target of 37 miRNAs were enriched in PI3K/AKT, P53, Wnt/-catenin, and TGF- pathways and related with skeletal system development and cell growth. Besides, the miRNAs including miR-22-3p, miR-154-5p, miR-34a-5p, miR-485-3p, miR-93-5p, and miR-9-5p and the genes including LEF1, RUNX2, CSF1R, CDKN1A, and FBN1 were identified as the hub nodes via network analysis. In conclusion, this study suggested that the miRNAs including miR-22-3p, miR-154-5p, miR-34a-5p, miR-485-3p, miR-93-5p, and miR-9-5p and the genes including LEF1, RUNX2, CSF1R, CDKN1A, and FBN1 act as key factors in the progression of osteosarcoma.

摘要

骨肉瘤是一种恶性疾病,很少有有效的策略可以完全克服这些患者的预后。本研究试图通过挖掘公共微阵列数据集来揭示骨肉瘤的关键因素和相关分子机制。数据来自基因表达综合(GEO)数据库;在 GSE69470 和 GSE12685l 中分别获得差异表达的 miRNAs 和差异表达的基因;miRDIP 数据库预测 miRNA 的靶标;David 数据库和 R 语言分别分析和可视化这些因素的功能。此外,STRING 数据库和 Cytoscape 软件进行蛋白质-蛋白质相互作用网络和 miRNA-mRNA 网络,以识别 GSE69470 和 GSE12685 中的枢纽节点。结果表明,在 GSE12685 中发现了 834 个 DEGs,在 GSE69470 中发现了 37 个 miRNAs。此外,37 个 miRNAs 的靶标富集在 PI3K/AKT、P53、Wnt/-catenin 和 TGF-途径中,与骨骼系统发育和细胞生长有关。此外,通过网络分析,发现 miR-22-3p、miR-154-5p、miR-34a-5p、miR-485-3p、miR-93-5p 和 miR-9-5p 等 miRNAs 以及 LEF1、RUNX2、CSF1R、CDKN1A 和 FBN1 等基因被鉴定为网络分析中的枢纽节点。总之,本研究表明,miR-22-3p、miR-154-5p、miR-34a-5p、miR-485-3p、miR-93-5p 和 miR-9-5p 等 miRNAs 以及 LEF1、RUNX2、CSF1R、CDKN1A 和 FBN1 等基因可能作为骨肉瘤进展的关键因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc00/8941547/d1187f98eb8b/JHE2022-8055052.001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验