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Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
Published on: February 23, 2024
Randomized trial drug controlled compendious transcriptome analysis supporting broad and phase specific therapeutic
1CSIR-Institute of Genomics and Integrative Biology, Sukhdev Vihar, Mathura Road, New Delhi 110025, India.
Abstract:
Effective therapies for coronavirus disease 2019 (COVID-19) are urgently needed. Maladaptive hyperinflammation and excessive cytokine release underlie the disease severity, with antiinflammatory and cytokine inhibiting agents expected to exert therapeutic effects. A major present challenge is identification of appropriate phase of the illness for a given intervention to yield optimum outcomes. Considering its established disease biomarker and drug discovery potential, a compendious analysis of existing transcriptomic data is presented here toward addressing this gap. The analysis is based on COVID-19 data related to intensive care unit (ICU) and non-ICU admissions, discharged and deceased patients, ventilation and non-ventilation phases, and high oxygen supplementation. It integrates transcriptomic data related to the effects of, in various cellular treatment models, the COVID-19 randomized clinical trial (RCT) successful drug dexamethasone, and the failed drug, with a potential to harm, hydroxychloroquine/chloroquine. Similarly, effects of various COVID-19 candidate drugs/anticytokines as well as proinflammatory cytokines implicated in the illness are also examined. The underlying assumption was that compared to COVID-19, an effective drug/anticytokine and a disease aggravating agent would affect gene regulation in opposite and same direction, in that order. Remarkably, the assumption was supported with respect to both the RCT drugs. With this control validation, etanercept, followed by tofacitinib and adalimumab, showed transcriptomic effects predictive of benefits in both ventilation and non-ventilation ICU stages as well as in non-ICU phase. On the other hand, canakinumab showed potential for effectiveness in high oxygen supplementation phase. These findings may inform experimental and clinical studies toward drug repurposing in COVID-19.
Insights
This study analyzes transcriptomic data to identify optimal timing for COVID-19 therapies. Etanercept, tofacitinib, and adalimumab show promise across various disease stages, while canakinumab may benefit patients needing high oxygen.
Area of Science:
- Transcriptomics
- Immunology
- Pharmacology
Background:
- COVID-19 severity is linked to hyperinflammation and cytokine release.
- Identifying optimal therapeutic intervention timing is crucial for effective COVID-19 treatment.
- Transcriptomic data offers insights into disease biomarkers and drug discovery potential.
Purpose of the Study:
- To analyze existing transcriptomic data to identify effective therapeutic strategies for COVID-19.
- To determine the optimal phase of illness for specific anti-inflammatory and cytokine-inhibiting agents.
- To guide experimental and clinical studies for COVID-19 drug repurposing.
Main Methods:
- Analysis of transcriptomic data from COVID-19 patients across different severity levels (ICU, non-ICU, ventilation, deceased).
- Integration of transcriptomic data on the effects of dexamethasone and hydroxychloroquine/chloroquine in cellular models.
- Examination of transcriptomic effects of candidate drugs, anticytokines, and proinflammatory cytokines.
Main Results:
- Transcriptomic analysis validated assumptions regarding drug effects on gene regulation compared to COVID-19.
- Etanercept, tofacitinib, and adalimumab demonstrated transcriptomic profiles suggesting benefits in both ICU and non-ICU phases.
- Canakinumab showed potential effectiveness during the high oxygen supplementation phase of COVID-19.
Conclusions:
- Transcriptomic data analysis provides a framework for understanding drug efficacy in COVID-19.
- Specific immunomodulatory drugs (etanercept, tofacitinib, adalimumab, canakinumab) show potential for repurposing in COVID-19 treatment.
- Findings can inform future clinical trials and therapeutic strategies for managing COVID-19.
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