A High-Content Screen for Mucin-1-Reducing Compounds Identifies Fostamatinib as a Candidate for Rapid Repurposing for Acute Lung Injury

Predictive biomarkers of disease progression in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial disease that cannot be cured, and treatment options for IPF are very limited. Early diagnosis, close monitoring of disease progression, and timely treatment are therefore the best options for patients due to the irreversibility of IPF. Effective markers help doctors judge the development and prognosis of disease. Recent research on traditional biomarkers (KL-6, SP-D, MMP-7, TIMPs, CCL18) has provided novel ideas for predicting disease progression and prognosis. Some emerging biomarkers (HE4, GDF15, PRDX4, inflammatory cells, G-CSF) also provide more possibilities for disease prediction. In addition to markers in serum and bronchoalveolar lavage fluid (BALF), some improvements related to the GAP model and chest HRCT also show good predictive ability for disease prognosis.

Identification of new drugs to counteract anti-spike IgG-induced hyperinflammation in severe COVID-19

Previously, we and others have shown that SARS-CoV-2 spike-specific IgG antibodies play a major role in disease severity in COVID-19 by triggering macrophage hyperactivation, disrupting endothelial barrier integrity, and inducing thrombus formation. This hyperinflammation is dependent on high levels of anti-spike IgG with aberrant Fc tail glycosylation, leading to Fcγ receptor hyperactivation. For development of immune-regulatory therapeutics, drug specificity is crucial to counteract excessive inflammation whereas simultaneously minimizing the inhibition of antiviral immunity. We here developed an in vitro activation assay to screen for small molecule drugs that specifically counteract antibody-induced pathology. We identified that anti-spike-induced inflammation is specifically blocked by small molecule inhibitors against SYK and PI3K. We identified SYK inhibitor entospletinib as the most promising candidate drug, which also counteracted anti-spike-induced endothelial dysfunction and thrombus formation. Moreover, entospletinib blocked inflammation by different SARS-CoV-2 variants of concern. Combined, these data identify entospletinib as a promising treatment for severe COVID-19.

Investigation of the Host Kinome Response to Coronavirus Infection Reveals PI3K/mTOR Inhibitors as Betacoronavirus Antivirals

Host kinases play essential roles in the host cell cycle, innate immune signaling, the stress response to viral infection, and inflammation. Previous work has demonstrated that coronaviruses specifically target kinase cascades to subvert host cell responses to infection and rely upon host kinase activity to phosphorylate viral proteins to enhance replication. Given the number of kinase inhibitors that are already FDA approved to treat cancers, fibrosis, and other human disease, they represent an attractive class of compounds to repurpose for host-targeted therapies against emerging coronavirus infections. To further understand the host kinome response to betacoronavirus infection, we employed multiplex inhibitory bead mass spectrometry (MIB-MS) following MERS-CoV and SARS-CoV-2 infection of human lung epithelial cell lines. Our MIB-MS analyses revealed activation of mTOR and MAPK signaling following MERS-CoV and SARS-CoV-2 infection, respectively. SARS-CoV-2 host kinome responses were further characterized using paired phosphoproteomics, which identified activation of MAPK, PI3K, and mTOR signaling. Through chemogenomic screening, we found that clinically relevant PI3K/mTOR inhibitors were able to inhibit coronavirus replication at nanomolar concentrations similar to direct-acting antivirals. This study lays the groundwork for identifying broad-acting, host-targeted therapies to reduce betacoronavirus replication that can be rapidly repurposed during future outbreaks and epidemics. The proteomics, phosphoproteomics, and MIB-MS datasets generated in this study are available in the Proteomics Identification Database (PRIDE) repository under project identifiers PXD040897 and PXD040901.

Total network controllability analysis discovers explainable drugs for Covid-19 treatment

BACKGROUND

The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets.

RESULTS

We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach's effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients.

CONCLUSIONS

Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases.

Total network controllability analysis discovers explainable drugs for Covid-19 treatment

Background The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural control capability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets. Results We developed an efficient algorithm to identify all control hubs, applying it to the largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach's effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients. Conclusions Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Idiopathic pulmonary fibrosis and the role of genetics in the era of precision medicine

Idiopathic pulmonary fibrosis (IPF) is a chronic, rare progressive lung disease, characterized by lung scarring and the irreversible loss of lung function. Two anti-fibrotic drugs, nintedanib and pirfenidone, have been demonstrated to slow down disease progression, although IPF mortality remains a challenge and the patients die after a few years from diagnosis. Rare pathogenic variants in genes that are involved in the surfactant metabolism and telomere maintenance, among others, have a high penetrance and tend to co-segregate with the disease in families. Common recurrent variants in the population with modest effect sizes have been also associated with the disease risk and progression. Genome-wide association studies (GWAS) support at least 23 genetic risk loci, linking the disease pathogenesis with unexpected molecular pathways including cellular adhesion and signaling, wound healing, barrier function, airway clearance, and innate immunity and host defense, besides the surfactant metabolism and telomere biology. As the cost of high-throughput genomic technologies continuously decreases and new technologies and approaches arise, their widespread use by clinicians and researchers is efficiently contributing to a better understanding of the pathogenesis of progressive pulmonary fibrosis. Here we provide an overview of the genetic factors known to be involved in IPF pathogenesis and discuss how they will continue to further advance in this field. We also discuss how genomic technologies could help to further improve IPF diagnosis and prognosis as well as for assessing genetic risk in unaffected relatives. The development and validation of evidence-based guidelines for genetic-based screening of IPF will allow redefining and classifying this disease relying on molecular characteristics and contribute to the implementation of precision medicine approaches.

Vir2Drug: a drug repurposing framework based on protein similarities between pathogens

We draw from the assumption that similarities between pathogens at both pathogen protein and host protein level, may provide the appropriate framework to identify and rank candidate drugs to be used against a specific pathogen. Vir2Drug is a drug repurposing tool that uses network-based approaches to identify and rank candidate drugs for a specific pathogen, combining information obtained from: (a) ranked pathogen-to-pathogen networks based on protein similarities between pathogens, (b) taxonomy distance between pathogens and (c) drugs targeting specific pathogen's and host proteins. The underlying pathogen networks are used to screen drugs by means of specific methodologies that account for either the host or pathogen's protein targets. Vir2Drug is a useful and yet informative tool for drug repurposing against known or unknown pathogens especially in periods where the emergence for repurposed drugs plays significant role in handling viral outbreaks, until reaching a vaccine. The web tool is available at: https://bioinformatics.cing.ac.cy/vir2drug, https://vir2drug.cing-big.hpcf.cyi.ac.cy.

Progress, pitfalls, and path forward of drug repurposing for COVID-19 treatment

On 30 January 2020, the World Health Organization (WHO) declared the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic a public health emergency of international concern. The viral outbreak led in turn to an exponential growth of coronavirus disease 2019 (COVID-19) cases, that is, a multiorgan disease that has led to more than 6.3 million deaths worldwide, as of June 2022. There are currently few effective drugs approved for treatment of SARS-CoV-2/COVID-19 patients. Many of the compounds tested so far have been selected through a drug repurposing approach, that is, by identifying novel indications for drugs already approved for other conditions. We here present an up-to-date review of the main Food and Drug Administration (FDA)-approved drugs repurposed against SARS-CoV-2 infection, discussing their mechanism of action and their most important preclinical and clinical results. Reviewed compounds were chosen to privilege those that have been approved for use in SARS-CoV-2 patients or that have completed phase III clinical trials. Moreover, we also summarize the evidence on some novel and promising repurposed drugs in the pipeline. Finally, we discuss the current stage and possible steps toward the development of broadly effective drug combinations to suppress the onset or progression of COVID-19.

KL-6 in ARDS and COVID-19 Patients

The Acute Respiratory Distress Syndrome (ARDS) is a common, devastating clinical pattern characterized by life-threatening respiratory failure. In ARDS there is an uncontrolled inflammatory response that results in alveolar damage, with the exudation of protein-rich pulmonary-edema fluid in the alveolar space. Although severe COVID-19 lung failure (CARDS) often meets diagnostic criteria of traditional ARDS, additional features have been reported, such as delayed onset, binary pulmonary compliant states, and hypercoagulable profile. Increased levels of Krebs von den Lungen 6 (KL-6, also known as MUC1) have been reported in both ARDS and CARDS. KL-6 is a transmembrane protein expressed on the apical membrane of most mucosal epithelial cells and it plays a critical role in lining the airway lumen. Abnormalities in mucus production contribute to severe pulmonary complications and death from respiratory failure in patients with diseases such as cystic fibrosis, chronic obstructive pulmonary disease, and acute lung injury due to viral pathogens. Nevertheless, it is not clear what role KL-6 plays in ARDS/CARDS pathophysiology. KL-6 may exert anti-inflammatory effects through the intracellular segment, as proven in animal models of ARDS, while its extracellular segment will enter the blood circulation through the alveolar space when the alveolar epithelial cells are damaged. Therefore, changes in plasma KL-6 levels may be useful in ARDS and CARDS phenotyping, and KL-6 might guide future clinical trials in 'personalized medicine' settings.

Krebs von den Lungen 6 (KL-6) levels in COVID-19 ICU patients are associated with mortality

Background

Krebs von den Lungen 6 (KL-6) is a high-molecular-weight mucin-like glycoprotein, which is also known as MUC1. KL-6 is mainly produced by type 2 pneumocytes and bronchial epithelial cells, and, therefore, elevated circulating KL-6 levels may denote disorders of the alveolar epithelial lining.

The objective of this study is to verify if KL-6 serum level might support ICU physicians in predicting mortality, risk stratifying and triaging severe COVID-19 patients.

Methods

A retrospective cohort study, including all the COVID-19 patients who measured KL-6 serum values at least once during their ICU stay, was performed. The study sample, 122 patients, was divided in two groups, according to the median KL-6 value at ICU admission (median log-transformed KL-6 value: 6.73 U/ml; group A: KL-6 lower than the median and group B: KL-6 higher than the median).

Results

One-hundred twenty-two ICU patients were included in this study. Mortality was higher in group B than in group A (80 versus 46%; p < 0.001); both linear and logistic multivariate analyses showed ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (P/F) significantly and inversely related to KL-6 values.

Conclusion

At ICU admission, KL-6 serum level was significantly higher in the most hypoxic COVID-19 patients and independently associated with ICU mortality.

Clinical Pharmacokinetics and Pharmacodynamics of Fostamatinib and Its Active Moiety R406

Fostamatinib is the first approved spleen tyrosine kinase inhibitor for chronic immune thrombocytopenia. This review summarizes the clinical development, pharmacokinetics, pharmacodynamics, drug–drug interactions, adverse events, and comprehensive analyses of fostamatinib. While integrating these findings, we discuss the fostering and improvement of fostamatinib for further clinical applications. Fostamatinib is designed as a prodrug and cleavage of its active moiety R406 in the intestine. As R406 is the major product in the blood, this review mainly discusses the pharmacokinetics and pharmacodynamics of R406. It is metabolized by cytochrome 3A4 and UGT1A9 in the liver and is dominantly excreted in feces after anaerobic modification by the gut microbiota. As fostamatinib and R406 strongly inhibit the breast cancer resistance protein, the interaction with those substrates, particularly statins, should be carefully monitored. In patients with immune thrombocytopenia, fostamatinib administration started at 100 mg twice daily, and most patients increased to 150 mg twice daily in the clinical trial. Although responders showed a higher R406 concentration than non-responders, the correlation between R406 exposure and achievement of the platelet count as a pharmacodynamic marker was uncertain in the pharmacokinetic/pharmacodynamic analysis. Additionally, R406 concentration was almost halved in patients with a heavy body weight; hence, the exposure-efficacy study for suitable dosing should be continued with post-marketing data. In contrast, the pharmacokinetic/pharmacodynamic analysis for exposure safety revealed that R406 exposure significantly correlated with the incidence of hypertension. Even though the influence of elevated exposure on other toxicities, including diarrhea and neutropenia, is still unclear, careful management is required with dose escalation to avoid toxicity-related discontinuation.

Detecting Drug–Target Interactions with Feature Similarity Fusion and Molecular Graphs

Simple Summary

Accurate identification of potential targets for drugs to interact with can accelerate drug development. The identification of drug–target interactions can provide insights into hidden drug efficacy. This paper presents a prediction model based on feature similarity fusion that can identify crucial features of drugs and targets to help predict drug–target interactions.

Abstract

The key to drug discovery is the identification of a target and a corresponding drug compound. Effective identification of drug–target interactions facilitates the development of drug discovery. In this paper, drug similarity and target similarity are considered, and graphical representations are used to extract internal structural information and intermolecular interaction information about drugs and targets. First, drug similarity and target similarity are fused using the similarity network fusion (SNF) method. Then, the graph isomorphic network (GIN) is used to extract the features with information about the internal structure of drug molecules. For target proteins, feature extraction is carried out using TextCNN to efficiently capture the features of target protein sequences. Three different divisions (CVD, CVP, CVT) are used on the standard dataset, and experiments are carried out separately to validate the performance of the model for drug–target interaction prediction. The experimental results show that our method achieves better results on AUC and AUPR. The docking results also show the superiority of the proposed model in predicting drug–target interactions.

Evaluating fostamatinib disodium as a treatment option for immune thrombocytopenia in adult patients

INTRODUCTION

Immune thrombocytopenia (ITP) is an autoimmune bleeding disorder characterized by increased platelet destruction and decreased platelet production, leading to thrombocytopenia with or without bleeding manifestations. The majority of patients experiencing treatment need will eventually need secondary treatment following first line therapy with steroids. In 2018, the oral spleen tyrosine kinase inhibitor fostamatinib received US Food and Drug Administration approval for ITP patients with an insufficient response to a previous treatment.

AREAS COVERED

This review outlines pharmacological characteristics of fostamatinib and provides an overview of its efficacy and safety results in phase II and III trials, followed by the expert opinion of the authors.

EXPERT OPINION

Increasing knowledge on the role of different players and mechanisms in the pathophysiology of autoimmune disorders in general and of ITP in particular, has led to the development of several new treatment options, as illustrated by the introduction of fostamatinib in the treatment of ITP. However, lacking direct comparison with other recent treatment options (in particular thrombopoietin receptor agonists), its use should be evaluated critically taking into account the unique toxicity and potential drug-drug interaction profile.

Identification of broad anti-coronavirus chemical agents for repurposing against SARS-CoV-2 and variants of concern

Endemic human coronaviruses (hCoVs) 229E and OC43 cause respiratory disease with recurrent infections, while severe acute respiratory syndrome (SARS)-CoV-2 spreads across the world with impact on health and societies. Here, we report an image-based multicycle infection procedure with α-coronavirus hCoV-229E-eGFP in an arrayed chemical library screen of 5440 clinical and preclinical compounds. Toxicity counter selection and challenge with the β-coronaviruses OC43 and SARS-CoV-2 in tissue culture and human airway epithelial explant cultures (HAEEC) identified four FDA-approved compounds with oral availability. Methylene blue (MB, used for the treatment of methemoglobinemia), Mycophenolic acid (MPA, used in organ transplantation) and the anti-fungal agent Posaconazole (POS) had the broadest anti-CoV spectrum. They inhibited the shedding of SARS-CoV-2 and variants-of-concern (alpha, beta, gamma, delta) from HAEEC in either pre- or post exposure regimens at clinically relevant concentrations. Co-treatment of cultured cells with MB and the FDA-approved SARS-CoV-2 RNA-polymerase inhibitor Remdesivir reduced the effective anti-viral concentrations of MB by 2-fold, and Remdesivir by 4 to 10-fold, indicated by BLISS independence synergy modelling. Neither MB, nor MPA, nor POS affected the cell delivery of SARS-CoV-2 or OC43 (+)sense RNA, but blocked subsequent viral RNA accumulation in cells. Unlike Remdesivir, MB, MPA or POS did not reduce the release of viral RNA in post exposure regimen, thus indicating infection inhibition at a post-replicating step as well. In summary, the data emphasize the power of unbiased, full cycle compound screens to identify and repurpose broadly acting drugs against coronaviruses.

Machine learning and network medicine approaches for drug repositioning for COVID-19

We present two machine learning approaches for drug repurposing. While we have developed them for COVID-19, they are disease-agnostic. The two methodologies are complementary, targeting SARS-CoV-2 and host factors, respectively. Our first approach consists of a matrix factorization algorithm to rank broad-spectrum antivirals. Our second approach, based on network medicine, uses graph kernels to rank drugs according to the perturbation they induce on a subnetwork of the human interactome that is crucial for SARS-CoV-2 infection/replication. Our experiments show that our top predicted broad-spectrum antivirals include drugs indicated for compassionate use in COVID-19 patients; and that the ranking obtained by our kernel-based approach aligns with experimental data. Finally, we present the COVID-19 repositioning explorer (CoREx), an interactive online tool to explore the interplay between drugs and SARS-CoV-2 host proteins in the context of biological networks, protein function, drug clinical use, and Connectivity Map. CoREx is freely available at: https://paccanarolab.org/corex/.

Genome-Wide RNAi Screening Identifies Novel Pathways/Genes Involved in Oxidative Stress and Repurposable Drugs to Preserve Cystic Fibrosis Airway Epithelial Cell Integrity

Recurrent infection-inflammation cycles in cystic fibrosis (CF) patients generate a highly oxidative environment, leading to progressive destruction of the airway epithelia. The identification of novel modifier genes involved in oxidative stress susceptibility in the CF airways might contribute to devise new therapeutic approaches. We performed an unbiased genome-wide RNAi screen using a randomized siRNA library to identify oxidative stress modulators in CF airway epithelial cells. We monitored changes in cell viability after a lethal dose of hydrogen peroxide. Local similarity and protein-protein interaction network analyses uncovered siRNA target genes/pathways involved in oxidative stress. Further mining against public drug databases allowed identifying and validating commercially available drugs conferring oxidative stress resistance. Accordingly, a catalog of 167 siRNAs able to confer oxidative stress resistance in CF submucosal gland cells targeted 444 host genes and multiple circuitries involved in oxidative stress. The most significant processes were related to alternative splicing and cell communication, motility, and remodeling (impacting cilia structure/function, and cell guidance complexes). Other relevant pathways included DNA repair and PI3K/AKT/mTOR signaling. The mTOR inhibitor everolimus, the α1-adrenergic receptor antagonist doxazosin, and the Syk inhibitor fostamatinib significantly increased the viability of CF submucosal gland cells under strong oxidative stress pressure. Thus, novel therapeutic strategies to preserve airway cell integrity from the harsh oxidative milieu of CF airways could stem from a deep understanding of the complex consequences of oxidative stress at the molecular level, followed by a rational repurposing of existing "protective" drugs. This approach could also prove useful to other respiratory pathologies.

Repurposable drugs for SARS-CoV-2 and influenza sepsis with scRNA-seq data targeting post-transcription modifications

Coronavirus disease 2019 (COVID-19) has impacted almost every part of human life worldwide, posing a massive threat to human health. The lack of time for new drug discovery and the urgent need for rapid disease control to reduce mortality have led to a search for quick and effective alternatives to novel therapeutics, for example drug repurposing. To identify potentially repurposable drugs, we employed a systematic approach to mine candidates from U.S. FDA-approved drugs and preclinical small-molecule compounds by integrating gene expression perturbation data for chemicals from the Library of Integrated Network-Based Cellular Signatures project with a publicly available single-cell RNA sequencing dataset from patients with mild and severe COVID-19 (GEO: GSE145926, public data available and accessed on 22 April 2020). We identified 281 FDA-approved drugs that have the potential to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, 16 of which are currently undergoing clinical trials to evaluate their efficacy against COVID-19. We experimentally tested and demonstrated the inhibitory effects of tyrphostin-AG-1478 and brefeldin-a, two chemical inhibitors of glycosylation (a post-translational modification) on the replication of the single-stranded ribonucleic acid (ssRNA) virus influenza A virus as well as on the transcription and translation of host cell cytokines and their regulators (IFNs and ISGs). In conclusion, we have identified and experimentally validated repurposable anti-SARS-CoV-2 and IAV drugs using a systems biology approach, which may have the potential for treating these viral infections and their complications (sepsis).

Integrative Multi-omics Landscape of Non-structural Protein 3 of Severe Acute Respiratory Syndrome Coronaviruses

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently a global pandemic. Extensive investigations have been performed to study the clinical and cellular effects of SARS-CoV-2 infection. Mass spectrometry-based proteomics studies have revealed the cellular changes due to the infection and identified a plethora of interactors for all SARS-CoV-2 components, except for the longest non-structural protein 3 (NSP3). Here, we expressed the full-length NSP3 proteins of SARS-CoV and SARS-CoV-2 to investigate their unique and shared functions using multi-omics methods. We conducted interactome, phosphoproteome, ubiquitylome, transcriptome, and proteome analyses of NSP3-expressing cells. We found that NSP3 plays essential roles in cellular functions such as RNA metabolism and immune response (e.g., NF-κB signal transduction). Interestingly, we showed that SARS-CoV-2 NSP3 has both endoplasmic reticulum and mitochondrial localizations. In addition, SARS-CoV-2 NSP3 is more closely related to mitochondrial ribosomal proteins, whereas SARS-CoV NSP3 is related to the cytosolic ribosomal proteins. In summary, our integrative multi-omics study of NSP3 improves the understanding of the functions of NSP3 and offers potential targets for the development of anti-SARS strategies.

Drug repurposing for coronavirus (SARS-CoV-2) based on gene co-expression network analysis

Severe acute respiratory syndrome (SARS) is a highly contagious viral respiratory illness. This illness is spurred on by a coronavirus known as SARS-associated coronavirus (SARS-CoV). SARS was first detected in Asia in late February 2003. The genome of this virus is very similar to the SARS-CoV-2. Therefore, the study of SARS-CoV disease and the identification of effective drugs to treat this disease can be new clues for the treatment of SARS-Cov-2. This study aimed to discover novel potential drugs for SARS-CoV disease in order to treating SARS-Cov-2 disease based on a novel systems biology approach. To this end, gene co-expression network analysis was applied. First, the gene co-expression network was reconstructed for 1441 genes, and then two gene modules were discovered as significant modules. Next, a list of miRNAs and transcription factors that target gene co-expression modules' genes were gathered from the valid databases, and two sub-networks formed of transcription factors and miRNAs were established. Afterward, the list of the drugs targeting obtained sub-networks' genes was retrieved from the DGIDb database, and two drug-gene and drug-TF interaction networks were reconstructed. Finally, after conducting different network analyses, we proposed five drugs, including FLUOROURACIL, CISPLATIN, SIROLIMUS, CYCLOPHOSPHAMIDE, and METHYLDOPA, as candidate drugs for SARS-CoV-2 coronavirus treatment. Moreover, ten miRNAs including miR-193b, miR-192, miR-215, miR-34a, miR-16, miR-16, miR-92a, miR-30a, miR-7, and miR-26b were found to be significant miRNAs in treating SARS-CoV-2 coronavirus.

Drug repurposing improves disease targeting 11-fold and can be augmented by network module targeting, applied to COVID-19

This analysis presents a systematic evaluation of the extent of therapeutic opportunities that can be obtained from drug repurposing by connecting drug targets with disease genes. When using FDA-approved indications as a reference level we found that drug repurposing can offer an average of an 11-fold increase in disease coverage, with the maximum number of diseases covered per drug being increased from 134 to 167 after extending the drug targets with their high confidence first neighbors. Additionally, by network analysis to connect drugs to disease modules we found that drugs on average target 4 disease modules, yet the similarity between disease modules targeted by the same drug is generally low and the maximum number of disease modules targeted per drug increases from 158 to 229 when drug targets are neighbor-extended. Moreover, our results highlight that drug repurposing is more dependent on target proteins being shared between diseases than on polypharmacological properties of drugs. We apply our drug repurposing and network module analysis to COVID-19 and show that Fostamatinib is the drug with the highest module coverage.

Aberrant glycosylation of anti-SARS-CoV-2 IgG is a pro-thrombotic stimulus for platelets

A subset of patients with COVID-19 become critically ill, suffering from severe respiratory problems and also increased rates of thrombosis. The causes of thrombosis in severely ill COVID-19 patients are still emerging, but the coincidence of critical illness with the timing of the onset of adaptive immunity could implicate an excessive immune response. We hypothesised that platelets might be susceptible to activation by anti-SARS-CoV-2 antibodies and contribute to thrombosis. We found that immune complexes containing recombinant SARS-CoV-2 spike protein and anti-spike IgG enhanced platelet-mediated thrombosis on von Willebrand Factor in vitro, but only when the glycosylation state of the Fc domain was modified to correspond with the aberrant glycosylation previously identified in patients with severe COVID-19. Furthermore, we found that activation was dependent on FcγRIIA and we provide in vitro evidence that this pathogenic platelet activation can be counteracted by therapeutic small molecules R406 (fostamatinib) and ibrutinib that inhibit tyrosine kinases Syk and Btk respectively or by the P2Y12 antagonist cangrelor.

Mesenchymal Stem Cell-Based Therapy as an Alternative to the Treatment of Acute Respiratory Distress Syndrome: Current Evidence and Future Perspectives

Acute respiratory distress syndrome (ARDS) represents a current challenge for medicine due to its incidence, morbidity and mortality and, also, the absence of an optimal treatment. The COVID-19 outbreak only increased the urgent demand for an affordable, safe and effective treatment for this process. Early clinical trials suggest the therapeutic usefulness of mesenchymal stem cells (MSCs) in acute lung injury (ALI) and ARDS. MSC-based therapies show antimicrobial, anti-inflammatory, regenerative, angiogenic, antifibrotic, anti-oxidative stress and anti-apoptotic actions, which can thwart the physiopathological mechanisms engaged in ARDS. In addition, MSC secretome and their derived products, especially exosomes, may reproduce the therapeutic effects of MSC in lung injury. This last strategy of treatment could avoid several safety issues potentially associated with the transplantation of living and proliferative cell populations and may be formulated in different forms. However, the following diverse limitations must be addressed: (i) selection of the optimal MSC, bearing in mind both the heterogeneity among donors and across different histological origins, (ii) massive obtention of these biological products through genetic manipulations of the most appropriate MSC, (iii) bioreactors that allow their growth in 3D, (iv) ideal culture conditions and (v) adequate functional testing of these obtaining biological products before their clinical application.

Precision omics data integration and analysis with interoperable ontologies and their application for COVID-19 research

Omics technologies are widely used in biomedical research. Precision medicine focuses on individual-level disease treatment and prevention. Here, we propose the usage of the term 'precision omics' to represent the combinatorial strategy that applies omics to translate large-scale molecular omics data for precision disease understanding and accurate disease diagnosis, treatment and prevention. Given the complexity of both omics and precision medicine, precision omics requires standardized representation and integration of heterogeneous data types. Ontology has emerged as an important artificial intelligence component to become critical for standard data and metadata representation, standardization and integration. To support precision omics, we propose a precision omics ontology hypothesis, which hypothesizes that the effectiveness of precision omics is positively correlated with the interoperability of ontologies used for data and knowledge integration. Therefore, to make effective precision omics studies, interoperable ontologies are required to standardize and incorporate heterogeneous data and knowledge in a human- and computer-interpretable manner. Methods for efficient development and application of interoperable ontologies are proposed and illustrated. With the interoperable omics data and knowledge, omics tools such as OmicsViz can also be evolved to process, integrate, visualize and analyze various omics data, leading to the identification of new knowledge and hypotheses of molecular mechanisms underlying the outcomes of diseases such as COVID-19. Given extensive COVID-19 omics research, we propose the strategy of precision omics supported by interoperable ontologies, accompanied with ontology-based semantic reasoning and machine learning, leading to systematic disease mechanism understanding and rational design of precision treatment and prevention.

SHORT ABSTRACT

Precision medicine focuses on individual-level disease treatment and prevention. Precision omics is a new strategy that applies omics for precision medicine research, which requires standardized representation and integration of individual genetics and phenotypes, experimental conditions, and data analysis settings. Ontology has emerged as an important artificial intelligence component to become critical for standard data and metadata representation, standardization and integration. To support precision omics, interoperable ontologies are required in order to standardize and incorporate heterogeneous data and knowledge in a human- and computer-interpretable manner. With the interoperable omics data and knowledge, omics tools such as OmicsViz can also be evolved to process, integrate, visualize and analyze various omics data, leading to the identification of new knowledge and hypotheses of molecular mechanisms underlying disease outcomes. The precision COVID-19 omics study is provided as the primary use case to illustrate the rationale and implementation of the precision omics strategy.

The Role of High-Density Lipoprotein in COVID-19

The current Coronavirus disease 2019 (COVID-19) pandemic has become a global challenge. Managing a large number of acutely ill patients in a short time, whilst reducing the fatality rate and dealing with complications, brings unique difficulties. The most striking pathophysiological features of patients with severe COVID-19 are dysregulated immune responses and abnormal coagulation function, which can result in multiple-organ failure and death. Normally metabolized high-density lipoprotein (HDL) performs several functions, including reverse cholesterol transport, direct binding to lipopolysaccharide (LPS) to neutralize LPS activity, regulation of inflammatory response, anti-thrombotic effects, antioxidant, and anti-apoptotic properties. Clinical data shows that significantly decreased HDL levels in patients with COVID-19 are correlated with both disease severity and mortality. However, the role of HDL in COVID-19 and its specific mechanism remain unclear. In this analysis, we review current evidence mainly in the following areas: firstly, the pathophysiological characteristics of COVID-19, secondly, the pleiotropic properties of HDL, thirdly, the changes and clinical significance of HDL in COVID-19, and fourthly the prospect of HDL-targeting therapy in COVID-19 to clarify the role of HDL in the pathogenesis of COVID-19 and discuss the potential of HDL therapy in COVID-19.

Complement activation and increased expression of Syk, mucin-1 and CaMK4 in kidneys of patients with COVID-19

Acute and chronic kidney failure is common in hospitalized patients with COVID-19, yet the mechanism of injury and predisposing factors remain poorly understood. We investigated the role of complement activation by determining the levels of deposited complement components (C1q, C3, FH, C5b-9) and immunoglobulin along with the expression levels of the injury-associated molecules spleen tyrosine kinase (Syk), mucin-1 (MUC1) and calcium/calmodulin-dependent protein kinase IV (CaMK4) in the kidney tissues of people who succumbed to COVID-19. We report increased deposition of C1q, C3, C5b-9, total immunoglobulin, and high expression levels of Syk, MUC1 and CaMK4 in the kidneys of COVID-19 patients. Our study provides strong rationale for the expansion of trials involving the use of inhibitors of these molecules, in particular C1q, C3, Syk, MUC1 and CaMK4 to treat patients with COVID-19.

High titers and low fucosylation of early human anti-SARS-CoV-2 IgG promote inflammation by alveolar macrophages

Patients diagnosed with coronavirus disease 2019 (COVID-19) become critically ill primarily around the time of activation of the adaptive immune response. Here, we provide evidence that antibodies play a role in the worsening of disease at the time of seroconversion. We show that early-phase severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) spike protein-specific immunoglobulin G (IgG) in serum of critically ill COVID-19 patients induces excessive inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for patients with severe COVID-19. First, inflammation is driven by high titers of anti-spike IgG, a hallmark of severe disease. Second, we found that anti-spike IgG from patients with severe COVID-19 is intrinsically more proinflammatory because of different glycosylation, particularly low fucosylation, of the antibody Fc tail. Low fucosylation of anti-spike IgG was normalized in a few weeks after initial infection with SARS-CoV-2, indicating that the increased antibody-dependent inflammation mainly occurs at the time of seroconversion. We identified Fcγ receptor (FcγR) IIa and FcγRIII as the two primary IgG receptors that are responsible for the induction of key COVID-19-associated cytokines such as interleukin-6 and tumor necrosis factor. In addition, we show that anti-spike IgG-activated human macrophages can subsequently break pulmonary endothelial barrier integrity and induce microvascular thrombosis in vitro. Last, we demonstrate that the inflammatory response induced by anti-spike IgG can be specifically counteracted by fostamatinib, an FDA- and EMA-approved therapeutic small-molecule inhibitor of Syk kinase.

Protective effects of notoginsenoside R1 on acute lung injury in rats with sepsis

Background

To clarify the mechanism of notoginsenoside R1 in the treatment of septic acute lung injury (ALI) based on network pharmacological analysis, and to verify it in the model of septic ALI in rats.

Methods

Based on database searching, the related targets of notoginsenoside R1 and ALI were identified, and the component-disease-target network was constructed. The core targets were screened by protein-protein interaction (PPI), and the functional enrichment of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was analyzed. The rat model of septic ALI was further established to investigate the pharmacological effects of notoginsenoside R1.

Results

Notoginsenoside R1 possibly affected ALI through 150 targets, of which 36 were core targets. GO semantic similarity analysis showed that notoginsenoside R1 might play a role in regulating interleukin 17 (IL-17) signal pathway, tumor necrosis factor (TNF) signal pathway and other key links by regulating MAPK1, MAPK3, IL-1β and other targets. The results of pharmacological experiments showed that notoginsenoside R1 could significantly reduce the wet:dry ratio of the lung in an animal model of ALI, improve the pathological injury of the lung, and reduce the content of IL-1β in serum and in bronchoalveolar lavage fluid (BALF) of experimental animals.

Conclusions

Notoginsenoside R1 can inhibit pulmonary edema, reduce inflammation, and improve lung lesions through multiple targets and pathways to achieve the pharmacological effects in the treatment of septic ALI.

Integrative web-based analysis of omics data for study of drugs against SARS-CoV-2

Research on drugs against SARS-CoV-2 (cause of COVID-19) has been one of the major world concerns at present. There have been abundant research data and findings in this field. The interference of drugs on gene expression in cell lines, drug-target, protein-virus receptor networks, and immune cell infiltration of the host may provide useful information for anti-SARS-CoV-2 drug research. To simplify the complex bioinformatics analysis and facilitate the evaluation of the latest research data, we developed OmiczViz ( http://medcode.link/omicsviz ), a web tool that has integrated drug-cell line interference data, virus-host protein-protein interactions, and drug-target interactions. To demonstrate the usages of OmiczViz, we analyzed the gene expression data from cell lines treated with chloroquine and ruxolitinib, the drug-target protein networks of 48 anti-coronavirus drugs and drugs bound with ACE2, and the profiles of immune cell infiltration between different COVID-19 patient groups. Our research shows that chloroquine had a regulatory role of the immune response in renal cell line but not in lung cell line. The anti-coronavirus drug-target network analysis suggested that antihistamine of promethaziney and dietary supplement of Zinc might be beneficial when used jointly with antiviral drugs. The immune infiltration analysis indicated that both the COVID-19 patients admitted to the ICU and the elderly with infection showed immune exhaustion status, yet with different molecular mechanisms. The interactive graphic interface of OmiczViz also makes it easier to analyze newly discovered and user-uploaded data, leading to an in-depth understanding of existing findings and an expansion of existing knowledge of SARS-CoV-2. Collectively, OmicsViz is web program that promotes the research on medical agents against SARS-CoV-2 and supports the evaluation of the latest research findings.

Practical Recommendations for the Management of Patients with ITP During the COVID-19 Pandemic

The current COVID-19 pandemic requires revisiting our current approach to major blood disorders, including ITP (Immune Thrombocytopenia), stirring up the production of several disease-specific practical guidelines. This report describes an updated version of consensus-based practical guidelines on the management of ITP, adapted to the Italian health system and social context. It highlights the role of the hematologist in offering guidance for choosing differentiated approaches in relation to specific circumstances and is intended to provide them with a useful tool for sharing the decision-making process with their patients.

Probably, the greatest risk to avoid for a patient with suspected, ongoing or relapsed ITP - that is not severe enough to place him or her at risk for major bleeding - is to be infected in non-hospital and hospital healthcare settings. This risk must be carefully considered when adapting the diagnostic and therapeutic approach.

More in detail, the document first addresses the appropriate management for COVID-19 negative patients with newly diagnosed ITP or who experience a relapse of previous ITP, according to first and second lines of treatment and then the management of COVID-19 positive patients according to their severity, from paucisymptomatic to those requiring admission to Intensive Cure Units (ICU). The pros and cons of the different treatments required to correct platelet count are discussed, as are some specific situations, including chronic ITP, splenectomy, thromboembolic complication and anti COVID-19 vaccination.

Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics

Since coronavirus disease 2019 (COVID-19) is a serious new worldwide public health crisis with significant morbidity and mortality, effective therapeutic treatments are urgently needed. Drug repurposing is an efficient and cost-effective strategy with minimum risk for identifying novel potential treatment options by repositioning therapies that were previously approved for other clinical outcomes. Here, we used an integrated network-based pharmacologic and transcriptomic approach to screen drug candidates novel for COVID-19 treatment. Network-based proximity scores were calculated to identify the drug-disease pharmacological effect between drug-target relationship modules and COVID-19 related genes. Gene set enrichment analysis (GSEA) was then performed to determine whether drug candidates influence the expression of COVID-19 related genes and examine the sensitivity of the repurposing drug treatment to peripheral immune cell types. Moreover, we used the complementary exposure model to recommend potential synergistic drug combinations. We identified 18 individual drug candidates including nicardipine, orantinib, tipifarnib and promethazine which have not previously been proposed as possible treatments for COVID-19. Additionally, 30 synergistic drug pairs were ultimately recommended including fostamatinib plus tretinoin and orantinib plus valproic acid. Differential expression genes of most repurposing drugs were enriched significantly in B cells. The findings may potentially accelerate the discovery and establishment of an effective therapeutic treatment plan for COVID-19 patients.

Fostamatinib Inhibits Neutrophils Extracellular Traps Induced by COVID-19 Patient Plasma: A Potential Therapeutic

Neutrophil extracellular traps (NETs) contribute to immunothrombosis and have been associated with mortality in coronavirus disease 2019 (COVID-19). We stimulated donor neutrophils with plasma from patients with COVID-19 and demonstrated that R406 can abrogate the release of NETs. These data provide evidence for how fostamatinib may mitigate neutrophil-associated mechanisms contributing to COVID-19 immunopathogenesis.

In silico Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19

Background: There is pressing urgency to identify therapeutic targets and drugs that allow treating COVID-19 patients effectively. Methods: We performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19. Results: We screened 1,584 high-confidence immune system proteins in ACE2 and TMPRSS2 co-expressing cells, finding 25 potential therapeutic targets significantly overexpressed in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs, obtaining several approved drugs, compounds under investigation, and experimental compounds with the highest area under the receiver operating characteristics. Conclusion: After being effectively analyzed in clinical trials, these drugs can be considered for treatment of severe COVID-19 patients. Scripts can be downloaded at https://github.com/muntisa/immuno-drug-repurposing-COVID-19.

Kinase inhibitors developed for treatment of hematologic malignancies: implications for immune modulation in COVID-19

Tyrosine kinase inhibitors (TKIs) are used to target dysregulated signaling pathways in virtually all hematologic malignancies. Many of the targeted signaling pathways are also essential in nonmalignant immune cells. The current coronavirus severe acute respiratory syndrome coronavirus 2 pandemic catalyzed clinical exploration of TKIs in the treatment of the various stages of COVID-19, which are characterized by distinct immune-related complications. Most of the reported effects of TKIs on immune regulation have been explored in vitro, with different class-specific drugs having nonoverlapping target affinities. Moreover, many of the reported in vivo effects are based on artificial animal models or on observations made in symptomatic patients with a hematologic malignancy who often already suffer from disturbed immune regulation. Based on in vitro and clinical observations, we attempt to decipher the impact of the main TKIs approved or in late-stage development for the treatment of hematological malignancies, including inhibitors of Bruton’s tyrosine kinase, spleen tyrosine kinase, BCR-Abl, phosphatidylinositol 3-kinase/ mammalian target of rapamycin, JAK/STAT, and FMS-like tyrosine kinase 3, to provide a rationale for how such inhibitors could modify clinical courses of diseases, such as COVID-19.

Technological Advancements in Monoclonal Antibodies

Biopharmaceuticals are innovative solutions that have revolutionized the treatment of important chronic diseases and malignancies. The approval of biosimilar products has become a complex and balanced process, and there are versions of drugs with established biosimilarity that can offer a more accessible treatment option to patients. The objective of this work was to identify the advancement of these technologies by means of patent and article analysis based on technological and scientific prospection. In patent document recovery, Derwent Innovation Index (DWPI) and PatentInspiration databases were used. The research was based on the search of the selected terms in the title, summary, and claims of the documents through a search strategy containing IPC code and keywords. In articles recovery, the Web of Science tool was used in the search of scientific publications dated from the last 5 years. The search resulted in a total of 2295 individual patent documents and 467 families using DWPI database, 769 individual patents and 205 families using PatentInspiration, and 2602 articles using Web of Science database. Additionally, this work describes the number of organizations that contribute to this area, where they are, how much development they have undergone, and the inventors/authors involved. Based on the number of publications registered, there is an important prominence for scientific research in mAbs. In terms of innovation, it is expected that several therapeutic drugs are already under regulatory review, which will allow drugs to be approved over the next few years and will thus generate a continuous flow of new products based on immunotherapies, mAbs, and biosimilar drugs. These drugs have become essential weapons for the treatment of significant diseases, and the increasing trend in the number of related scientific and technological publications contributes to making these therapies available to the greatest number of people.

Identification of Repurposable Drugs and Adverse Drug Reactions for Various Courses of COVID-19 Based on Single-Cell RNA Sequencing Data

Coronavirus disease 2019 (COVID-19) has impacted almost every part of human life worldwide, posing a massive threat to human health. There is no specific drug for COVID-19, highlighting the urgent need for the development of effective therapeutics. To identify potentially repurposable drugs, we employed a systematic approach to mine candidates from U.S. FDA-approved drugs and preclinical small-molecule compounds by integrating the gene expression perturbation data for chemicals from the Library of Integrated Network-Based Cellular Signatures project with a publicly 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, 16 of which are currently undergoing clinical trials to evaluate their efficacy against COVID-19. We experimentally tested the inhibitory effects of tyrphostin-AG-1478 and brefeldin-a on the replication of the single-stranded ribonucleic acid (ssRNA) virus influenza A virus. In conclusion, we have identified a list of repurposable anti-SARS-CoV-2 drugs using a systems biology approach.