The Coronavirus Disease 2019 (COVID-19) pandemic has infected >5.5 million people globally and carries a relatively high mortality rate. Currently, there is no effective vaccine or therapy approved for the treatment COVID-19, though many such therapeutics are being evaluated in clinical trials. Using the unique profiles of altered gene expression found in NHBE, A549_ACE2 and Calu3 human lung epithelial cells after Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, we conducted a computational analysis to identify dysfunctional signaling pathways within infected cells. Using these data, potential therapeutic targets were identified and matched with existing medications to develop a theoretical approach to pharmacologic repurposing and inform clinical trial decisions. Specifically, signaling pathways upregulated by SARS-CoV-2 infection and their associated gene ontologies (GOs) were extracted and clustered to generate 10 super-GOs. The genes associated with the identified signaling pathways and the super-GOs were used as gene signatures to identify drugs that can potentially inhibit these signaling cascades. In these results, interesting signaling pathways and GOs such as  JAK-STAT, IRF7-NFkB signaling, and MYD88/CXCR6 immune signaling were identified. Many drugs were identified with downstream inhibition of these signaling pathways and GOs, and many of which are currently undergoing clinical trial evaluation. The analysis results can be potentially helpful to facilitate the future clinical trial design. Rigorous clinical trial and experimental validations are needed to validate these results, considering the limitation of pure computational data analysis based on the noisy and limited data. some of these drugs might have harmful effects and cautions .
The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate. There are many therapeutics undergoing clinical trials, but there is no effective vaccine or therapy for treatment thus far. After affected by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) , molecular signaling of host cells plays critical roles during the life cycle of SARS-CoV-2. Thus, it is significant to identify the involved molecular signaling pathways within the host cells, and drugs targeting these molecular signaling pathways could be potentially effective for COVID-19 treatment. In this study, we aimed to identify these potential molecular signaling pathways, and repurpose existing drugs as a potentially effective treatment of COVID-19 to facilitate the therapeutic discovery, based on the transcriptional response of host cells. We first identified dysfunctional signaling pathways associated with the infection caused SARS-CoV-2 in human lung epithelial cells through analysis of the altered gene expression profiles. In addition to the signaling pathway analysis, the activated gene ontologies (GOs) and super gene ontologies were identified. Signaling pathways and GOs such as MAPK, JNK, STAT, ERK, JAK-STAT, IRF7-NFkB signaling, and MYD88/CXCR6 immune signaling were particularly identified. Based on the identified signaling pathways and GOs, a set of potentially effective drugs were repurposed by integrating the drug-target and reverse gene expression data resources. The dexamethasone was top-ranked in the prediction, which was the first reported drug to be able to significantly reduce the death rate of COVID-19 patients receiving respiratory support. The results can be helpful to understand the associated molecular signaling pathways within host cells, and facilitate the discovery of effective drugs for COVID-19 treatment .
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approved for the treatment COVID-19, though many such therapeutics are being evaluated in clinical trials. Using the unique profiles of altered gene expression found in NHBE, A549_ACE2 and Calu3 human lung epithelial cells after
for treatment thus far. After affected by the
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infection, we conducted a computational analysis to identify dysfunctional
, molecular signaling of host cells plays critical roles during the life cycle of SARS-CoV-2. Thus, it is significant to identify the involved molecular
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infected cells. Using these data, potential therapeutic targets were identified and matched with existing medications to develop a theoretical approach to pharmacologic repurposing and inform clinical trial decisions. Specifically, signaling pathways upregulated by
the host cells, and drugs targeting these molecular signaling pathways could be potentially effective for COVID-19 treatment. In this study, we aimed to identify these potential molecular signaling pathways, and repurpose existing drugs as a potentially effective treatment of COVID-19 to facilitate the therapeutic discovery, based on the transcriptional response of host cells. We first identified dysfunctional signaling pathways associated with the infection caused
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infection and their associated gene
in human lung epithelial cells through analysis of the altered gene expression profiles. In addition to the signaling pathway analysis, the activated gene
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were extracted and clustered to generate 10 super-GOs. The genes associated with the identified signaling pathways and the super-GOs were used as gene signatures to identify drugs that can potentially inhibit these signaling cascades. In these results, interesting signaling
and super gene ontologies were identified. Signaling
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MAPK, JNK, STAT, ERK,
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identified. Many drugs were identified with downstream inhibition of these
particularly identified. Based on the identified
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and many of which are currently undergoing clinical trial evaluation. The analysis
a set of potentially effective drugs were repurposed by integrating the drug-target and reverse gene expression data resources. The dexamethasone was top-ranked in the prediction, which was the first reported drug to be able to significantly reduce the death rate of COVID-19 patients receiving respiratory support. The
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potentially helpful to facilitate the future clinical trial design. Rigorous clinical trial and experimental validations are needed to validate these results, considering the limitation of pure computational data analysis based on the noisy and limited data. some of these drugs might have harmful effects and cautions
helpful to understand the associated molecular signaling pathways within host cells, and facilitate the discovery of effective drugs for COVID-19 treatment