Understanding the molecular basis of fibrosis, the lethal complication of COVID-19, is urgent. By the analysis of RNA-sequencing data of SARS-CoV-2-infected cells combined with data mining we identified genes involved in COVID-19 progression. To characterize their implication in the fibrosis development we established a correlation matrix based on the transcriptomic data of patients with idiopathic pulmonary fibrosis. With this method, we have identified a cluster of genes responsible for SARS-CoV-2-fibrosis including its entry receptor ACE2 and epidermal growth factor EGF. Then, we developed Vi-Fi scoring—a novel drug repurposing approach and simultaneously quantified antiviral and antifibrotic activities of the drugs based on their transcriptomic signatures. We revealed the strong dual antifibrotic and antiviral activity of EGFR/ErbB inhibitors. Before the in vitro validation, we have clustered 277 cell lines and revealed distinct COVID-19 transcriptomic signatures of the cells with similar phenotypes that defines their suitability for COVID-19 research. By ERK activity monitoring in living lung cells, we show that the drugs with predicted antifibrotic activity downregulate ERK in the host lung cells. Overall, our study provides novel insights on SARS-CoV-2 dependence on EGFR/ERK signaling and demonstrates the utility of EGFR/ErbB inhibitors for COVID-19 treatment.
【저자키워드】 Drug discovery, machine learning, Virtual drug screening, Data mining, imaging, Data processing, Cell signalling, 【초록키워드】 COVID-19, Treatment, SARS-CoV-2, ACE2, Antiviral, pulmonary fibrosis, fibrosis, drug, in vitro, antiviral activity, inhibitors, Idiopathic pulmonary fibrosis, activity, COVID-19 treatment, Patient, Cluster, understanding, phenotype, transcriptomic data, EGFR, correlation, inhibitor, utility, RNA-sequencing, Signaling, Analysis, dual, the cells, epidermal growth factor, COVID-19 progression, infected cells, entry receptor, molecular basis, SARS-CoV-2-infected cells, sequencing data, growth factor, cell line, ErbB, COVID-19 research, lung cells, complication of COVID-19, Host, ERK, transcriptomic, approach, Cell, EGF, responsible, predicted, involved, provide, downregulate, quantified, epidermal, cluster of gene, SARS-CoV-2-infected cell, 【제목키워드】 COVID-19, MAPK,