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

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.

Integration of Omics Data and Network Models to Unveil Negative Aspects of SARS-CoV-2, from Pathogenic Mechanisms to Drug Repurposing

“…The completeness of the omics profiles used to reconstruct the network models can certainly impact the consistency of the models themselves and the outcomes of their functional and topological analysis. As for COVID-19 investigation, these strategies have been much more widely adopted and exploited in combination with RNAseq data [ 23 , 25 , 26 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 ], and specifically in the context of network pharmacology studies. As a result of using traditional medicine to treat COVID-19 patients, the number of retrospective studies aimed at discovering bioactive compounds and potential gene targets for therapy has clearly emerged.…”

“…Most of these studies were based on a similar pipeline relying on network topology. The identification of protein hubs has proven useful in prioritizing the candidate targets for drug treatments in which to invest time for further study and validation [ 23 , 24 , 25 , 26 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 89 , 90 , 91 , 92 , 93 , 94 ]. The saving of time certainly represents a vitally important element in emergency situations, such as the one experienced due to COVID-19.…”

“…The latter have been selected among hubs found by processing topologically the PPI network models reconstructed from experimental omics profiles ( Figure 4 ). However, most of them have used differentially expressed genes (DEGs) [ 23 , 25 , 26 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 ], while few have relied on proteomics [ 86 ] or metabolomics data [ 87 ]. Interestingly, similar strategies have been used for network pharmacology studies to evaluate comorbidities.…”

“…Nodes with a high value of this centrality maintain communication with groups of nodes and control the information flow that passes through them. In other words, this hub or bottleneck represents a fundamental element of connection in signaling pathways, thus becoming a candidate drug target, as reported in several studies focused on SARS-CoV-2 investigation [ 23 , 24 , 25 , 26 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 89 , 90 , 91 , 92 , 93 , 94 ].…”

“…Interestingly, similar strategies have been used for network pharmacology studies to evaluate comorbidities. As a matter of fact, SARS-CoV-2 infection has been investigated in correlation with mucormycosis [88], influenza [24], diabetic kidney disease [83], multiple myeloma [84], cardiomyopathy [77,89,90], non-alcoholic fatty liver disease (NAFLD) [79], pulmonary fibrosis [91], colon cancer [92], lung cancer [82,85], glioblastoma [93] and HIV [94]. Starting with herbal mixtures, the authors retrieved the bioactive compounds present there and the corresponding genes that they target.…”