Weather the Cytokine Storm: A Report of Successful Management of a Colon Cancer Survivor and a Critically Ill Patient with COVID-19

Khalid, Mansoor; Dernaika, Tarek A.; Jacob, Lirin; Annamaraju, Pavan; Guddati, Achuta Kumar

doi:10.1159/000509507

Cited by 3 publications

(2 citation statements)

References 19 publications

(25 reference statements)

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“…As shown in Tab. II, we find some evidence to confirm ten therapeutic associations, For example, One SARS-CoV-2 patient was treated with Ceftriaxone, and his cough, fever, and fatigue were improved gradually, he completed the 5day course of hydroxychloroquine and azithromycin, 7 days of ceftriaxone [8]. As reported in [9], ciprofloxacin and glycyrrhizic acid were selected based on their reported antiviral activity, safety, availability, affordability and subjected for Molecular Dynamics (MD) simulation.…”

Section: Sars-cov-2 Potential Drug Predictionmentioning

confidence: 97%

Drug Repositioning for SARS-CoV-2 Based on Graph Neural Network

Liu

Lin

Shen

et al. 2020

2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the strain of coronavirus that causes coronavirus disease 2019 (COVID-19), which leads to over 800,000 deaths and is still no specific medicines. Drug repositioning aiming to infer potential drugs for diseases and achieve much attention during the SARS-CoV-2 epidemic. However, find a specific drug of SARS-CoV-2 is still a large challenge that cannot be addressed well with current methods. To overcome this problem, we present a novel drug repositioning framework of heterogeneous graph convolutional networks for SARS-CoV-2. The deep2CoV model can effectively search the potential drugs for SARS-CoV-2, which reduce the number of clinical trials and drug development cycles. The experimental results demonstrate the effectiveness and feasibility of our proposed deep2CoV framework.

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Section: Sars-cov-2 Potential Drug Predictionmentioning

confidence: 97%

Drug Repositioning for SARS-CoV-2 Based on Graph Neural Network

Liu

Lin

Shen

et al. 2020

2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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“…Since proinflammatory cytokines negatively influence host immunity against infection, a natural cytokine treatment has both advantages and disadvantages (Rider et al 2016 ). The SARS-CoV-2 infection in cancer patients exhibits an aggravated cytokine response, contributing to increased mortality rates (Turnquist et al 2020 ; Khalid et al 2020 ; Weatherford et al 2020 ). Hence, interfering with the cytokine storm appears to be a prerogative response against virus-infected cancer patients.…”

Section: Sars-cov-2 and Cytokine Stormmentioning

confidence: 99%

Cancer vs. SARS-CoV-2 induced inflammation, overlapping functions, and pharmacological targeting

Subbarao

2021

Inflammopharmacol

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Inflammation is an intrinsic defence mechanism triggered by the immune system against infection or injury. Chronic inflammation allows the host to recover or adapt through cellular and humoral responses, whereas acute inflammation leads to cytokine storms resulting in tissue damage. In this review, we present the overlapping outcomes of cancer inflammation with virus-induced inflammation. The study emphasises how anti-inflammatory drugs that work against cancer inflammation may work against the inflammation caused by the viral infection. It is established that the cytokine storm induced in response to SARS-CoV-2 infection contributes to disease-associated mortality. While cancer remains the second among the diseases associated with mortality worldwide, cancer patients' mortality rates are often observed upon extended periods after illness, usually ranging from months to years. However, the mortality rates associated with COVID-19 disease are robust. The cytokine storm induced by SARS-CoV-2 infection appeared to be responsible for the multi-organ failure and increased mortality rates. Since both cancer and COVID-19 disease share overlapping inflammatory mechanisms, repurposing some anticancer and anti-inflammatory drugs for COVID-19 may lower mortality rates. Here, we review some of these inflammatory mechanisms and propose some potential chemotherapeutic agents to intervene in them. We also discuss the repercussions of anti-inflammatory drugs such as glucocorticoids and hydroxychloroquine with zinc or antiviral drugs such as ivermectin and remdesivir against SARS-CoV-2 induced cytokine storm. In this review, we emphasise on various possibilities to reduce SARS-CoV-2 induced cytokine storm.

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A network representation approach for COVID-19 drug recommendation

Liu

Lin

Shen

et al. 2022

Methods

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The coronavirus disease 2019 (COVID-19) has outbreak since early December 2019, and COVID-19 has caused over 100 million cases and 2 million deaths around the world. After one year of the COVID-19 outbreak, there is no certain and approve medicine against it. Drug repositioning has become one line of scientific research that is being pursued to develop an effective drug. However, due to the lack of COVID-19 data, there is still no specific drug repositioning targeting the COVID-19. In this paper, we propose a framework for COVID-19 drug repositioning. This framework has several advantages that can be exploited: one is that a local graph aggregating representation is used across a heterogeneous network to address the data sparsity problem; another is the multi-hop neighbors of the heterogeneous graph are aggregated to recall as many COVID-19 potential drugs as possible. Our experimental results show that our COVDR framework performs significantly better thanbaseline methods, and the docking simulation verifies that our three potential drugs have the ability to against COVID-19 disease.

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Weather the Cytokine Storm: A Report of Successful Management of a Colon Cancer Survivor and a Critically Ill Patient with COVID-19

Cited by 3 publications

References 19 publications

Drug Repositioning for SARS-CoV-2 Based on Graph Neural Network

Drug Repositioning for SARS-CoV-2 Based on Graph Neural Network

Cancer vs. SARS-CoV-2 induced inflammation, overlapping functions, and pharmacological targeting

A network representation approach for COVID-19 drug recommendation

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