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基于生物信息学分析探索2019冠状病毒病与肺癌之间的潜在联系、核心基因及潜在药物

Exploration of the Potential Link, Hub Genes, and Potential Drugs for Coronavirus Disease 2019 and Lung Cancer Based on Bioinformatics Analysis.

作者信息

Wang Ye, Li Qing, Zhang Jianfang, Xie Hui

机构信息

Department of Thoracic Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou 423000, Hunan Province, China.

School of Medical Imaging, Laboratory Science and Rehabilitation, Xiangnan University, Chenzhou 423000, Hunan Province, China.

出版信息

J Oncol. 2022 Sep 26;2022:8124673. doi: 10.1155/2022/8124673. eCollection 2022.

Abstract

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has a huge influence on global public health and the economy. Lung cancer is one of the high-risk factors of COVID-19, but the molecular mechanism of lung cancer and COVID-19 is still unclear, and further research is needed. Therefore, we used the transcriptome information of the public database and adopted bioinformatics methods to identify the common pathways and molecular biomarkers of lung cancer and COVID-19 to further understand the connection between them. The two RNA-seq data sets in this study-GSE147507 (COVID-19) and GSE33532 (lung cancer)-were both derived from the Gene Expression Omnibus (GEO) database and identified differentially expressed genes (DEGs) for lung cancer and COVID-19 patients. We conducted Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis and found some common features between lung cancer and COVID-19. We also performed TFs-gene, miRNAs-gene, and gene-drug analyses. In total, 32 DEGs were found. A protein-protein interaction (PPI) network was constructed by DEGs, and 10 hub genes were screened. Finally, the identified drugs may be helpful for COVID-19 treatment.

摘要

2019冠状病毒病(COVID-19)的持续流行对全球公共卫生和经济产生了巨大影响。肺癌是COVID-19的高危因素之一,但肺癌与COVID-19的分子机制仍不清楚,需要进一步研究。因此,我们利用公共数据库的转录组信息,采用生物信息学方法来识别肺癌与COVID-19的共同通路和分子生物标志物,以进一步了解它们之间的联系。本研究中的两个RNA测序数据集——GSE147507(COVID-19)和GSE33532(肺癌)——均来自基因表达综合数据库(GEO),并确定了肺癌患者和COVID-19患者的差异表达基因(DEG)。我们进行了基因本体(GO)功能和京都基因与基因组百科全书(KEGG)通路富集分析,发现肺癌和COVID-19之间存在一些共同特征。我们还进行了转录因子-基因、微小RNA-基因和基因-药物分析。总共发现了32个差异表达基因。通过差异表达基因构建了蛋白质-蛋白质相互作用(PPI)网络,并筛选出10个核心基因。最后,所确定的药物可能有助于COVID-19的治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6a8a/9529395/e671b2f2b24e/JO2022-8124673.001.jpg

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