Bioinformatics Analysis of mRNAs and miRNAs for Identifying Potential Biomarkers in Lung Adenosquamous Carcinoma.
Bioinformatics Analysis of mRNAs and miRNAs for Identifying Potential Biomarkers in Lung Adenosquamous Carcinoma.
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DOI：
10.1155/2022/5851269
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发表时间：
2022
影响因子：
--
通讯作者：
Liu D
中科院分区：
文献类型：
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作者：
Nie J;Gong L;Li Z;Ou D;Zhang L;Liu Y;Zhang J;Liu D
肺腺鳞癌（LASC）是一种特殊类型的肺癌。 LASC是一种侵袭性强、预后差的恶性肿瘤。此前的研究表明，microRNA（miRNA）通过靶向mRNA广泛参与肿瘤的发生发展。本研究旨在鉴定 LASC 的关键 mRNA 和 miRNA，并构建 miRNA-mRNA 网络以深入理解潜在的分子机制。 从基因表达综合 (GEO) 数据库中提取并下载 mRNA 数据集 (GSE51852) 和 miRNA 数据集 (GSE51853)。通过GEO2R网络工具挑选出差异表达基因（DEG）和差异表达miRNA（DEM）。在DAVID数据库中进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）功能富集分析。分别使用STRING数据库和Cytoscape软件进行和分析蛋白质-蛋白质相互作用（PPI）网络。 TransmiR v2.0 用于预测 miRNA 的潜在转录因子。 DEM 的靶基因在 miRWalk 数据库中预测。 与正常组织相比，LASC组织中总共筛选出1458个DEG（511个上调和947个下调）和13个DEM（5个上调和8个下调）。 DEG 的 PPI 网络显示了 5 个关键模块和 17 个中心基因。预测了 DEM 的 6 个靶基因，并建立了 5 个必需的 miRNA-mRNA 调控对。因此，目标基因之一CENPF也是GSE51852的枢纽基因，该基因从MCODE和cytoHubba获得并受hsa-miR-205调控。 我们构建了 miRNA-mRNA 调控对，这有助于研究 LASC 的潜在调控机制并找到有前景的诊断生物标志物和治疗靶点。
Lung adenosquamous carcinoma (LASC) is a special type of lung cancer. LASC is a malignant tumor with strong aggressiveness and a poor prognosis. Previous studies have revealed that microRNAs (miRNAs) are widely involved in the development of tumors by targeting mRNA. This study is aimed at identifying the key mRNAs and miRNAs of LASC and constructing miRNA-mRNA networks for deeply comprehending the latent molecular mechanisms. mRNA dataset (GSE51852) and miRNA dataset (GSE51853) were extracted and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were picked out by the GEO2R web tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted in the DAVID database. The protein-protein interaction (PPI) network was performed and analyzed by using the STRING database and Cytoscape software, respectively. TransmiR v2.0 was applied to predict potential transcription factors of miRNAs. The target genes of DEMs were predicted in the miRWalk database. In comparison to normal tissues, a total of 1458 DEGs (511 upregulated and 947 downregulated) and 13 DEMs (5 upregulated and 8 downregulated) were screened out in LASC tissues. The PPI network of the DEGs displayed five key modules and seventeen hub genes. Six target genes of the DEMs were predicted, and five essential miRNA-mRNA regulatory pairs were established. Ensuingly, CENPF, one of the target genes, was also the hub genes of GSE51852, which was obtained from MCODE and cytoHubba and regulated by hsa-miR-205. We constructed the miRNA-mRNA regulatory pairs, which are helpful to study the potential regulatory mechanisms and find out promising diagnosis biomarkers and therapeutic targets for LASC.