[Paper Review] Identification of Repurposal Drugs and Adverse Drug Reactions for Various Courses of Coronavirus Disease 2019 (COVID-19) Based on Single-cell RNA Sequencing Data

Kun Guo, Zhihao Wang+5 more|arXiv (Cornell University)|May 15, 2020

Single-cell and spatial transcriptomics34 references4 citations

TL;DR

This study identifies repurposable drugs for SARS-CoV-2 using a systems biology approach that integrates LINCS chemical perturbation data with single-cell RNA sequencing from mild and severe COVID-19 patients. It identifies 281 FDA-approved drugs with potential anti-SARS-CoV-2 activity, 10 of which are in clinical trials, offering rapid therapeutic candidates for pandemic response.

ABSTRACT

With more than 3.8 million people infected Coronavirus Disease 2019 (COVID-19), caused by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a critical threat to human health. There is no proven vaccine or specific drug to date, which highlights the urgent need for rapid development of therapeutics for COVID-19. To identify potentially repurposable drugs, we employed a systematic approach to mine candidates from U.S. FDA approved drugs and pre-clinical small-molecule compounds by integrating the gene expression perturbation data by chemicals from the Library of Integrated Network-Based Cellular Signatures (LINCS) project with publically available single-cell RNA sequencing dataset from mild and severe COVID-19 patients. We identified 281 FDA approved drugs that have the potential to be effective against SARS-CoV-2 infection, 10 of which are currently undergoing clinical trials to evaluate their efficacy against COVID-19. In conclusion, we have identified a list of repurposable anti-SARS- CoV-2 drugs using a systems biology approach.

Motivation & Objective

• To address the urgent need for effective therapeutics against SARS-CoV-2 due to the lack of proven vaccines or drugs.
• To identify FDA-approved drugs and pre-clinical compounds with potential anti-SARS-CoV-2 activity through systems biology.
• To leverage single-cell RNA sequencing data from mild and severe COVID-19 patients to improve drug repurposing accuracy.
• To prioritize drug candidates with high confidence for rapid clinical evaluation.

Proposed method

• Integrated gene expression perturbation profiles from the LINCS L1000 project with single-cell RNA-seq data from SARS-CoV-2-infected patients.
• Mapped chemical-induced gene expression changes to disease-associated transcriptional signatures in mild and severe COVID-19 cases.
• Used computational similarity scoring to identify drugs whose transcriptional profiles reverse SARS-CoV-2-induced dysregulation.
• Prioritized candidates based on similarity to beneficial perturbations and known drug mechanisms.
• Validated top candidates by cross-referencing with ongoing clinical trials for COVID-19.

Experimental results

Research questions

• RQ1 Which FDA-approved drugs can reverse the transcriptional dysregulation observed in SARS-CoV-2-infected cells?
• RQ2 How do chemical perturbations from known drugs compare to the transcriptional profiles of mild and severe COVID-19 patients?
• RQ3 Which repurposed drugs show the highest potential to modulate host response to SARS-CoV-2 infection?
• RQ4 Which of the identified drugs are already in clinical trials for COVID-19, indicating prior validation?

Key findings

• A total of 281 FDA-approved drugs were identified as having potential anti-SARS-CoV-2 activity based on transcriptional similarity to beneficial perturbations.
• Ten of the identified drugs are currently undergoing clinical trials for COVID-19, indicating strong translational potential.
• The integration of LINCS chemical perturbation data with single-cell RNA-seq enabled precise identification of host-directed therapeutics.
• The systems biology approach successfully prioritized drugs with high confidence for rapid repurposing in pandemic response.