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基于生物信息学分析探究血清外泌体微小RNA在结直肠癌中的潜在分子机制。

Investigating potential molecular mechanisms of serum exosomal miRNAs in colorectal cancer based on bioinformatics analysis.

作者信息

Wang Haifeng, Chen Xiliang, Bao Lingling, Zhang Xuede

机构信息

Department of Hematology and Oncology, Beilun District People's Hospital, Ningbo, Zhejiang.

Department of Clinical Laboratory, Zhangqiu District People's Hospital, Jinan, Shandong, China.

出版信息

Medicine (Baltimore). 2020 Sep 11;99(37):e22199. doi: 10.1097/MD.0000000000022199.

DOI:10.1097/MD.0000000000022199
PMID:32925795
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7489663/
Abstract

Colorectal cancer (CRC) is the most common malignant gastrointestinal tumor worldwide. Serum exosomal microRNAs (miRNAs) play a critical role in tumor progression and metastasis. However, the underlying molecular mechanisms are poorly understood.The miRNAs expression profile (GSE39833) was downloaded from Gene Expression Omnibus (GEO) database. GEO2R was applied to screen the differentially expressed miRNAs (DEmiRNAs) between healthy and CRC serum exosome samples. The target genes of DEmiRNAs were predicted by starBase v3.0 online tool. The gene ontology (GO) and Kyoto Encyclopedia of Genomes pathway (KEGG) enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. The protein-protein interaction (PPI) network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) visualized using Cytoscape software. Molecular Complex Detection (MCODE) and cytohubba plug-in were used to screen hub genes and gene modules.In total, 102 DEmiRNAs were identified including 67 upregulated and 35 downregulated DEmiRNAs, and 1437 target genes were predicted. GO analysis showed target genes of upregulated DEmiRNAs were significantly enriched in transcription regulation, protein binding, and ubiquitin protein ligase activity. While the target genes of downregulated DEmiRNAs were mainly involved in transcription from RNA polymerase II promoter, SMAD binding, and DNA binding. The KEGG pathway enrichment analyses showed target genes of upregulated DEmiRNAs were significantly enriched in proteoglycans in cancer, microRNAs in cancer, and phosphatidylinositol-3 kinases/Akt (PI3K-Akt) signaling pathway, while target genes of downregulated DEmiRNAs were mainly enriched in transforming growth factor-beta (TGF-beta) signaling pathway and proteoglycans in cancer. The genes of the top 3 modules were mainly enriched in ubiquitin mediated proteolysis, spliceosome, and mRNA surveillance pathway. According to the cytohubba plugin, 37 hub genes were selected, and 4 hub genes including phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), SRC, cell division cycle 42 (CDC42), E1A binding protein p300 (EP300) were identified by combining 8 ranked methods of cytohubba.The study provides a comprehensive analysis of exosomal DEmiRNAs and target genes regulatory network in CRC, which can better understand the roles of exosomal miRNAs in the development of CRC. However, these findings require further experimental validation in future studies.

摘要

结直肠癌(CRC)是全球最常见的恶性胃肠道肿瘤。血清外泌体微小RNA(miRNA)在肿瘤进展和转移中起关键作用。然而,其潜在的分子机制尚不清楚。

从基因表达综合数据库(GEO)下载miRNA表达谱(GSE39833)。应用GEO2R筛选健康人和CRC血清外泌体样本之间差异表达的miRNA(DEmiRNA)。通过starBase v3.0在线工具预测DEmiRNA的靶基因。使用注释、可视化和综合发现数据库(DAVID)在线工具进行基因本体(GO)和京都基因与基因组百科全书通路(KEGG)富集分析。通过检索相互作用基因的搜索工具(STRING)建立蛋白质-蛋白质相互作用(PPI)网络,并使用Cytoscape软件进行可视化。使用分子复合物检测(MCODE)和cytohubba插件筛选枢纽基因和基因模块。

共鉴定出102个DEmiRNA,其中67个上调,35个下调,并预测了1437个靶基因。GO分析显示,上调的DEmiRNA的靶基因在转录调控、蛋白质结合和泛素蛋白连接酶活性方面显著富集。而下调的DEmiRNA的靶基因主要参与RNA聚合酶II启动子的转录、SMAD结合和DNA结合。KEGG通路富集分析显示,上调的DEmiRNA的靶基因在癌症中的蛋白聚糖、癌症中的miRNA和磷脂酰肌醇-3激酶/Akt(PI3K-Akt)信号通路中显著富集,而下调的DEmiRNA的靶基因主要富集在转化生长因子-β(TGF-β)信号通路和癌症中的蛋白聚糖。前3个模块的基因主要富集在泛素介导的蛋白水解、剪接体和mRNA监测通路。根据cytohubba插件,选择了37个枢纽基因,并结合cytohubba的8种排序方法鉴定出4个枢纽基因,包括磷酸肌醇-3激酶调节亚基1(PIK3R1)、SRC、细胞分裂周期42(CDC42)、E1A结合蛋白p300(EP300)。

该研究对CRC中外泌体DEmiRNA和靶基因调控网络进行了全面分析,有助于更好地理解外泌体miRNA在CRC发生发展中的作用。然而,这些发现需要在未来的研究中进一步进行实验验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/b14f5c841a9f/medi-99-e22199-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/cdb04c8e68b2/medi-99-e22199-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/4a850cc79e8a/medi-99-e22199-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/eb85a66e43db/medi-99-e22199-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/b14f5c841a9f/medi-99-e22199-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/cdb04c8e68b2/medi-99-e22199-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/4a850cc79e8a/medi-99-e22199-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/eb85a66e43db/medi-99-e22199-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40a4/7489663/b14f5c841a9f/medi-99-e22199-g009.jpg

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