The coronavirus-related signaling pathway networks and prediction modeling with activity plots.

Abstract

The network of coronavirus-related signaling pathways is activated in coronavirus pathogenesis. To reveal the network pathways in coronavirus pathogenesis, public gene expression data were analyzed in Ingenuity Pathway Analysis (IPA). The molecular networks and gene expression in diffuse- and intestinal-type gastric cancer (GC) have been analyzed as well. Among more than 90,000 analyses and datasets, 106 analyses and 106 datasets were related to SARS coronavirus 2. The 49 analyses were involved in SARS coronavirus 2 and human, which comprise of 27 analyses including 9 analyses on tissue "skin" GSE156754 and 22 analyses on lung adenocarcinoma. FOS and JUN in the coronavirus pathogenesis pathway were activated in SARS-CoV-2 infected lung adenocarcinoma. Coronavirus pathogenesis pathway was activated in SARS-CoV-2 infected iPS cell-derived cardiomyocytes. Coronavirus pathogenesis pathway was activated in diffuse-type GC and inactivated in intestinal-type GC. Activity plots of the coronavirus pathogenesis pathway included 17352 analyses, among which top 50 and bottom 50 analyses in Z-score were utilized for machine-learning prediction modeling. Elastic-Net Classifier model had an accuracy of 1 to discriminate the activation state of the coronavirus pathogenesis pathway as evaluated with additional 20 datasets. Coronavirus replication pathways, as well as possible pathways, are currently in the investigation.