Research article Special Issues

To investigate the internal association between SARS-CoV-2 infections and cancer through bioinformatics


  • Received: 10 May 2022 Revised: 25 July 2022 Accepted: 27 July 2022 Published: 04 August 2022
  • Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), also known as COVID-19, is currently prevalent worldwide and poses a significant threat to human health. Individuals with cancer may have an elevated risk for SARS-CoV-2 infections and adverse outcomes. Therefore, it is necessary to explore the internal relationship between these two diseases. In this study, transcriptome analyses were performed to detect mutual pathways and molecular biomarkers in three types of common cancers of the breast, liver, colon, and COVID-19. Such analyses could offer a valuable understanding of the association between COVID-19 and cancer patients. In an analysis of RNA sequencing datasets for three types of cancers and COVID-19, we identified a sum of 38 common differentially expressed genes (DEGs). A variety of combinational statistical approaches and bioinformatics techniques were utilized to generate the protein-protein interaction (PPI) network. Subsequently, hub genes and critical modules were found using this network. In addition, a functional analysis was conducted using ontologies keywords, and pathway analysis was also performed. Some common associations between cancer and the risk and prognosis of COVID-19 were discovered. The datasets also revealed transcriptional factors-gene interplay, protein-drug interaction, and a DEGs-miRNAs coregulatory network with common DEGs. The potential medications discovered in this investigation could be useful in treating cancer and COVID-19.

    Citation: Qinyan shen, Jiang wang, Liangying zhao. To investigate the internal association between SARS-CoV-2 infections and cancer through bioinformatics[J]. Mathematical Biosciences and Engineering, 2022, 19(11): 11172-11194. doi: 10.3934/mbe.2022521

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  • Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), also known as COVID-19, is currently prevalent worldwide and poses a significant threat to human health. Individuals with cancer may have an elevated risk for SARS-CoV-2 infections and adverse outcomes. Therefore, it is necessary to explore the internal relationship between these two diseases. In this study, transcriptome analyses were performed to detect mutual pathways and molecular biomarkers in three types of common cancers of the breast, liver, colon, and COVID-19. Such analyses could offer a valuable understanding of the association between COVID-19 and cancer patients. In an analysis of RNA sequencing datasets for three types of cancers and COVID-19, we identified a sum of 38 common differentially expressed genes (DEGs). A variety of combinational statistical approaches and bioinformatics techniques were utilized to generate the protein-protein interaction (PPI) network. Subsequently, hub genes and critical modules were found using this network. In addition, a functional analysis was conducted using ontologies keywords, and pathway analysis was also performed. Some common associations between cancer and the risk and prognosis of COVID-19 were discovered. The datasets also revealed transcriptional factors-gene interplay, protein-drug interaction, and a DEGs-miRNAs coregulatory network with common DEGs. The potential medications discovered in this investigation could be useful in treating cancer and COVID-19.



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