Identification of potential biomarkers and inhibitors for SARS-CoV-2 infection

Abstract The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has overwhelmed many health systems globally. Here, we aim to identify biological markers and associated biological processes of COVID-19 using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profile of the GSE152418 dataset was originally produced by using the high-throughput Illumina NovaSeq 6000. Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and Gene Ontology (GO) enrichment analyses were applied to identify functional categories and biochemical pathways. KEGG and GO results suggested that biological pathways such as “Cancer pathways” and “Insulin pathways” were mostly affected in the development of COVID-19. Moreover, we identified several genes including EP300, CREBBP, and POLR2A were involved in the virus activities in COVID-19 patients. We further predicted that some inhibitors may have the potential to block the SARS-CoV-2 infection based on the L1000FWD analysis. Therefore, our study provides further insights into the underlying pathogenesis of COVID-19.