The Role of EGFR in Influenza Pathogenicity: Multiple Network-Based Approaches to Identify a Key Regulator of Non-lethal Infections

Design, synthesis and biological evaluation of potent epidermal growth factor receptor tyrosine kinase (EGFR-TK) inhibitors against resistance mutation for lung cancer treatment

In this study, we identified a newly synthesized compound 7o with potent inhibition on EGFR primary mutants (L858R, Del19) and drug-resistant mutant T790M with nanomolar IC50 values. 7o showed strong antiproliferative effects against EGFR mutant-driven non-small cell lung cancer (NSCLC) cells such as H1975, PC-9 and HCC827, over cells expressing EGFRWT. Molecular docking was performed to investigate the possible binding modes of 7o inside the binding site of EGFRL858R/T790M and EGFRWT. Analysis of cell cycle evidenced that 7o induced cell cycle arrest in G1 phases in the EGFR mutant cells, H1975 and PC-9, which resulted in decreased S-phase populations. Moreover, compound 7o induced cancer cell apoptosis in in vitro assays. In addition, 7o inhibited cellular phosphorylation of EGFR. In vivo, oral administration of 7o caused rapid tumor regression in H1975 xenograft model. Therefore, 7o might deserve further optimization as cancer treatment agent for EGFR mutant-driven NSCLC.

Hubs and Bottlenecks in Protein-Protein Interaction Networks

Protein-protein interaction networks (PPINs) represent the physical interactions among proteins in a cell. These interactions are critical in all cellular processes, including signal transduction, metabolic regulation, and gene expression. In PPINs, centrality measures are widely used to identify the most critical nodes. The two most commonly used centrality measures in networks are degree and betweenness centralities. Degree centrality is the number of connections a node has in the network, and betweenness centrality is the measure of the extent to which a node lies on the shortest paths between pairs of other nodes in the network. In PPINs, proteins with high degree and betweenness centrality are referred to as hubs and bottlenecks respectively. Hubs and bottlenecks are topologically and functionally essential proteins that play crucial roles in maintaining the network's structure and function. This article comprehensively reviews essential literature on hubs and bottlenecks, including their properties and functions.

Pathogenicity and virulence of influenza

Influenza viruses, including four major types (A, B, C, and D), can cause mild-to-severe and lethal diseases in humans and animals. Influenza viruses evolve rapidly through antigenic drift (mutation) and shift (reassortment of the segmented viral genome). New variants, strains, and subtypes have emerged frequently, causing epidemic, zoonotic, and pandemic infections, despite currently available vaccines and antiviral drugs. In recent years, avian influenza viruses, such as H5 and H7 subtypes, have caused hundreds to thousands of zoonotic infections in humans with high case fatality rates. The likelihood of these animal influenza viruses acquiring airborne transmission in humans through viral evolution poses great concern for the next pandemic. Severe influenza viral disease is caused by both direct viral cytopathic effects and exacerbated host immune response against high viral loads. Studies have identified various mutations in viral genes that increase viral replication and transmission, alter tissue tropism or species specificity, and evade antivirals or pre-existing immunity. Significant progress has also been made in identifying and characterizing the host components that mediate antiviral responses, pro-viral functions, or immunopathogenesis following influenza viral infections. This review summarizes the current knowledge on viral determinants of influenza virulence and pathogenicity, protective and immunopathogenic aspects of host innate and adaptive immune responses, and antiviral and pro-viral roles of host factors and cellular signalling pathways. Understanding the molecular mechanisms of viral virulence factors and virus-host interactions is critical for the development of preventive and therapeutic measures against influenza diseases.

Hijacking of GPCRs and RTKs by pathogens

Pathogens exploit multiple cellular and molecular pathways in the host organisms for their entry, survival and dissemination. The cell surface receptors such as G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs) constitute the targets of many pathogens. This is due to the ubiquitous expression of these two receptor families in the organism and their pivotal role in various cellular and physiological processes. At the molecular level, receptor hijacking implies either direct or indirect interactions between pathogens' effectors or toxins with GPCRs and RTKs at the cell surface thereby interfering with their activation and their downstream signaling pathways inside the host cells. As a result, the pathogens manipulate and redirect GPCR/RTK-mediated signaling pathways and different aspects of cell function for their benefit. The review presents a compilation of the major examples of pathogen infections where GPCRs and RTKs and their related intracellular signaling pathways are targeted. This provides a molecular basis for pathogens hijacking cell signaling and their virulence. Our understanding of such complex host-pathogen interactions at the molecular level will open new opportunities to develop new prophylactic and therapeutic approaches against infections. In this context, the pharmacological targeting of GPCRs and RTKs may be a promising approach.

Pathobiological alterations affecting the distinct clinical courses of pediatric versus adult COVID-19 syndrome

Background/aim

The clinical presentation of pediatric coronavirus disease 2019 (COVID-19) is associated with a milder disease course than the adult COVID-19 syndrome. The disease course of COVID-19 has three clinicobiological phases: initiation, propagation, and complication. This study aimed to assess the pathobiological alterations affecting the distinct clinical courses of COVID-19 in pediatric age groups versus the adult population. We hypothesized that critical biogenomic marker expressions drive the mild clinical presentations of pediatric COVID-19.

Materials and methods

Blood samples were obtained from 72 patients with COVID-19 hospitalized at Ankara City Hospital between March and July 2021. Peripheral blood mononuclear cells were isolated using Ficoll-Paque and density-gradient sedimentation. The groups were compared using a t-test and limma analyses. Mean standardized gene expression levels were used to hierarchically cluster genes employing Euclidean Gene Cluster 3.0. The expression levels of identified genes were determined using reverse transcription-polymerase chain reaction.

Results

This study found that ANPEP gene expression was significantly downregulated in the pediatric group (p < 0.05, FC: 1.57) and IGF2R gene expression was significantly upregulated in the adult group (p < 0.05, FC: 2.98). The study results indicated that the expression of critical biogenomic markers, such as the first-phase (ACE2 and ANPEP) and second-phase (EGFR and IGF2R) receptor genes, was crucial in the genesis of mild clinical presentations of pediatric COVID-19. ANPEP gene expression was lower in pediatric COVID-19.

Conclusion

The interrelationship between the ANPEP and ACE2 genes may prevent the progression of COVID-19 from initiation to the propagating phase in pediatric patients. High IGF2R gene expression could potentially contribute to a protective effect and may be a contributing factor for the mild clinical course observed in pediatric patients.

The SARS-CoV-2 Spike Protein Activates the Epidermal Growth Factor Receptor-Mediated Signaling

The coronavirus disease-19 (COVID-19) pandemic is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At the molecular and cellular levels, the SARS-CoV-2 uses its envelope glycoprotein, the spike S protein, to infect the target cells in the lungs via binding with their transmembrane receptor, the angiotensin-converting enzyme 2 (ACE2). Here, we wanted to investigate if other molecular targets and pathways may be used by SARS-CoV-2. We investigated the possibility of the spike 1 S protein and its receptor-binding domain (RBD) to target the epidermal growth factor receptor (EGFR) and its downstream signaling pathway in vitro using the lung cancer cell line (A549 cells). Protein expression and phosphorylation were examined upon cell treatment with the recombinant full spike 1 S protein or RBD. We demonstrate for the first time the activation of EGFR by the Spike 1 protein associated with the phosphorylation of the canonical Extracellular signal-regulated kinase1/2 (ERK1/2) and AKT kinases and an increase in survivin expression controlling the survival pathway. Our study suggests the putative implication of EGFR and its related signaling pathways in SARS-CoV-2 infectivity and COVID-19 pathology. This may open new perspectives in the treatment of COVID-19 patients by targeting EGFR.

FDA-Approved Inhibitors of RTK/Raf Signaling Potently Impair Multiple Steps of In Vitro and Ex Vivo Influenza A Virus Infections

Influenza virus (IV) infections pose a burden on global public health with significant morbidity and mortality. The limited range of currently licensed IV antiviral drugs is susceptible to the rapid rise of resistant viruses. In contrast, FDA-approved kinase inhibitors can be repurposed as fast-tracked host-targeted antivirals with a higher barrier of resistance. Extending our recent studies, we screened 21 FDA-approved small-molecule kinase inhibitors (SMKIs) and identified seven candidates as potent inhibitors of pandemic and seasonal IV infections. These SMKIs were further validated in a biologically and clinically relevant ex vivo model of human precision-cut lung slices. We identified steps of the virus infection cycle affected by these inhibitors (entry, replication, egress) and found that most SMKIs affected both entry and egress. Based on defined and overlapping targets of these inhibitors, the candidate SMKIs target receptor tyrosine kinase (RTK)-mediated activation of Raf/MEK/ERK pathways to limit influenza A virus infection. Our data and the established safety profiles of these SMKIs support further clinical investigations and repurposing of these SMKIs as host-targeted influenza therapeutics.

Dependency of EGFR activation in vanadium-based sensitization to oncolytic virotherapy

Oncolytic virotherapy is a clinically validated approach to treat cancers such as melanoma; however, tumor resistance to virus makes its efficacy variable. Compounds such as sodium orthovanadate (vanadate) can overcome viral resistance and synergize with RNA-based oncolytic viruses. In this study, we explored the basis of vanadate mode of action and identified key cellular components in vanadate’s oncolytic virus-enhancing mechanism using a high-throughput kinase inhibitor screen. We found that several kinase inhibitors affecting signaling downstream of the epidermal growth factor receptor (EGFR) pathway abrogated the oncolytic virus-enhancing effects of vanadate. EGFR pathway inhibitors such as gefitinib negated vanadate-associated changes in the phosphorylation and localization of STAT1/2 as well as NF-κB signaling. Moreover, gefitinib treatment could abrogate the viral sensitizing response of vanadium compounds in vivo. Together, we demonstrate that EGFR signaling plays an integral role in vanadium viral sensitization and that pharmacological EGFR blockade can counteract vanadium/oncolytic virus combination therapy.

Thrombosis-related circulating miR-16-5p is associated with disease severity in patients hospitalised for COVID-19

SARS-CoV-2 tropism for the ACE2 receptor, along with the multifaceted inflammatory reaction, is likely to drive the generalized hypercoagulable and thrombotic state seen in patients with COVID-19. Using the original bioinformatic workflow and network medicine approaches we reanalysed four coronavirus-related expression datasets and performed co-expression analysis focused on thrombosis and ACE2 related genes. We identified microRNAs (miRNAs) which play role in ACE2-related thrombosis in coronavirus infection and further, we validated the expressions of precisely selected miRNAs-related to thrombosis (miR-16-5p, miR-27a-3p, let-7b-5p and miR-155-5p) in 79 hospitalized COVID-19 patients and 32 healthy volunteers by qRT-PCR. Consequently, we aimed to unravel whether bioinformatic prioritization could guide selection of miRNAs with a potential of diagnostic and prognostic biomarkers associated with disease severity in patients hospitalized for COVID-19. In bioinformatic analysis, we identified EGFR, HSP90AA1, APP, TP53, PTEN, UBC, FN1, ELAVL1 and CALM1 as regulatory genes which could play a pivotal role in COVID-19 related thrombosis. We also found miR-16-5p, miR-27a-3p, let-7b-5p and miR-155-5p as regulators in the coagulation and thrombosis process. In silico predictions were further confirmed in patients hospitalized for COVID-19. The expression levels of miR-16-5p and let-7b in COVID-19 patients were lower at baseline, 7-days and 21-day after admission compared to the healthy controls (p < 0.0001 for all time points for both miRNAs). The expression levels of miR-27a-3p and miR-155-5p in COVID-19 patients were higher at day 21 compared to the healthy controls (p = 0.007 and p < 0.001, respectively). A low baseline miR-16-5p expression presents predictive utility in assessment of the hospital length of stay or death in follow-up as a composite endpoint (AUC:0.810, 95% CI, 0.71-0.91, p < 0.0001) and low baseline expression of miR-16-5p and diabetes mellitus are independent predictors of increased length of stay or death according to a multivariate analysis (OR: 9.417; 95% CI, 2.647-33.506; p = 0.0005 and OR: 6.257; 95% CI, 1.049-37.316; p = 0.044, respectively). This study enabled us to better characterize changes in gene expression and signalling pathways related to hypercoagulable and thrombotic conditions in COVID-19. In this study we identified and validated miRNAs which could serve as novel, thrombosis-related predictive biomarkers of the COVID-19 complications, and can be used for early stratification of patients and prediction of severity of infection development in an individual.Abbreviations: ACE2, angiotensin-converting enzyme 2AF, atrial fibrillationAPP, Amyloid Beta Precursor ProteinaPTT, activated partial thromboplastin timeAUC, Area under the curveAβ, amyloid betaBMI, body mass indexCAD, coronary artery diseaseCALM1, Calmodulin 1 geneCaM, calmodulinCCND1, Cyclin D1CI, confidence intervalCOPD, chronic obstructive pulmonary diseaseCOVID-19, Coronavirus disease 2019CRP, C-reactive proteinCV, CardiovascularCVDs, cardiovascular diseasesDE, differentially expressedDM, diabetes mellitusEGFR, Epithelial growth factor receptorELAVL1, ELAV Like RNA Binding Protein 1FLNA, Filamin AFN1, Fibronectin 1GEO, Gene Expression OmnibushiPSC-CMs, Human induced pluripotent stem cell-derived cardiomyocytesHSP90AA1, Heat Shock Protein 90 Alpha Family Class A Member 1Hsp90α, heat shock protein 90αICU, intensive care unitIL, interleukinIQR, interquartile rangelncRNAs, long non-coding RNAsMI, myocardial infarctionMiRNA, MiR, microRNAmRNA, messenger RNAncRNA, non-coding RNANERI, network-medicine based integrative approachNF-kB, nuclear factor kappa-light-chain-enhancer of activated B cellsNPV, negative predictive valueNXF, nuclear export factorPBMCs, Peripheral blood mononuclear cellsPCT, procalcitoninPPI, Protein-protein interactionsPPV, positive predictive valuePTEN, phosphatase and tensin homologqPCR, quantitative polymerase chain reactionROC, receiver operating characteristicSARS-CoV-2, severe acute respiratory syndrome coronavirus 2SD, standard deviationTLR4, Toll-like receptor 4TM, thrombomodulinTP53, Tumour protein P53UBC, Ubiquitin CWBC, white blood cells.

Beyond the List: Bioagent-Agnostic Signatures Could Enable a More Flexible and Resilient Biodefense Posture Than an Approach Based on Priority Agent Lists Alone

As of 2021, the biothreat policy and research communities organize their efforts around lists of priority agents, which elides consideration of novel pathogens and biotoxins. For example, the Select Agents and Toxins list is composed of agents that historic biological warfare programs had weaponized or that have previously caused great harm during natural outbreaks. Similarly, lists of priority agents promulgated by the World Health Organization and the National Institute of Allergy and Infectious Diseases are composed of previously known pathogens and biotoxins. To fill this gap, we argue that the research/scientific and biodefense/biosecurity communities should categorize agents based on how they impact their hosts to augment current list-based paradigms. Specifically, we propose integrating the results of multi-omics studies to identify bioagent-agnostic signatures (BASs) of disease-namely, patterns of biomarkers that accurately and reproducibly predict the impacts of infection or intoxication without prior knowledge of the causative agent. Here, we highlight three pathways that investigators might exploit as sources of signals to construct BASs and their applicability to this framework. The research community will need to forge robust interdisciplinary teams to surmount substantial experimental, technical, and data analytic challenges that stand in the way of our long-term vision. However, if successful, our functionality-based BAS model could present a means to more effectively surveil for and treat known and novel agents alike.

On Deep Landscape Exploration of COVID-19 Patients Cells and Severity Markers

COVID-19 is a disease with a spectrum of clinical responses ranging from moderate to critical. To study and control its effects, a large number of researchers are focused on two substantial aims. On the one hand, the discovery of diverse biomarkers to classify and potentially anticipate the disease severity of patients. These biomarkers could serve as a medical criterion to prioritize attention to those patients with higher prone to severe responses. On the other hand, understanding how the immune system orchestrates its responses in this spectrum of disease severities is a fundamental issue required to design new and optimized therapeutic strategies. In this work, using single-cell RNAseq of bronchoalveolar lavage fluid of nine patients with COVID-19 and three healthy controls, we contribute to both aspects. First, we presented computational supervised machine-learning models with high accuracy in classifying the disease severity (moderate and severe) in patients with COVID-19 starting from single-cell data from bronchoalveolar lavage fluid. Second, we identified regulatory mechanisms from the heterogeneous cell populations in the lungs microenvironment that correlated with different clinical responses. Given the results, patients with moderate COVID-19 symptoms showed an activation/inactivation profile for their analyzed cells leading to a sequential and innocuous immune response. In comparison, severe patients might be promoting cytotoxic and pro-inflammatory responses in a systemic fashion involving epithelial and immune cells without the possibility to develop viral clearance and immune memory. Consequently, we present an in-depth landscape analysis of how transcriptional factors and pathways from these heterogeneous populations can regulate their expression to promote or restrain an effective immune response directly linked to the patients prognosis.

Applied Proteomics in 'One Health'

‘One Health’ summarises the idea that human health and animal health are interdependent and bound to the health of ecosystems. The purpose of proteomics methodologies and studies is to determine proteins present in samples of interest and to quantify changes in protein expression during pathological conditions. The objectives of this paper are to review the application of proteomics technologies within the One Health concept and to appraise their role in the elucidation of diseases and situations relevant to One Health. The paper develops in three sections. Proteomics Applications in Zoonotic Infections part discusses proteomics applications in zoonotic infections and explores the use of proteomics for studying pathogenetic pathways, transmission dynamics, diagnostic biomarkers and novel vaccines in prion, viral, bacterial, protozoan and metazoan zoonotic infections. Proteomics Applications in Antibiotic Resistance part discusses proteomics applications in mechanisms of resistance development and discovery of novel treatments for antibiotic resistance. Proteomics Applications in Food Safety part discusses the detection of allergens, exposure of adulteration, identification of pathogens and toxins, study of product traits and characterisation of proteins in food safety. Sensitive analysis of proteins, including low-abundant ones in complex biological samples, will be achieved in the future, thus enabling implementation of targeted proteomics in clinical settings, shedding light on biomarker research and promoting the One Health concept.

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Background

Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets.

Results

We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality.

Conclusions

Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04197-2.

ACE2 Interaction Networks in COVID-19: A Physiological Framework for Prediction of Outcome in Patients with Cardiovascular Risk Factors

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease 2019; COVID-19) is associated with adverse outcomes in patients with cardiovascular disease (CVD). The aim of the study was to characterize the interaction between SARS-CoV-2 and Angiotensin-Converting Enzyme 2 (ACE2) functional networks with a focus on CVD.

METHODS

Using the network medicine approach and publicly available datasets, we investigated ACE2 tissue expression and described ACE2 interaction networks that could be affected by SARS-CoV-2 infection in the heart, lungs and nervous system. We compared them with changes in ACE-2 networks following SARS-CoV-2 infection by analyzing public data of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). This analysis was performed using the Network by Relative Importance (NERI) algorithm, which integrates protein-protein interaction with co-expression networks. We also performed miRNA-target predictions to identify which miRNAs regulate ACE2-related networks and could play a role in the COVID19 outcome. Finally, we performed enrichment analysis for identifying the main COVID-19 risk groups.

RESULTS

We found similar ACE2 expression confidence levels in respiratory and cardiovascular systems, supporting that heart tissue is a potential target of SARS-CoV-2. Analysis of ACE2 interaction networks in infected hiPSC-CMs identified multiple hub genes with corrupted signaling which can be responsible for cardiovascular symptoms. The most affected genes were EGFR (Epidermal Growth Factor Receptor), FN1 (Fibronectin 1), TP53, HSP90AA1, and APP (Amyloid Beta Precursor Protein), while the most affected interactions were associated with MAST2 and CALM1 (Calmodulin 1). Enrichment analysis revealed multiple diseases associated with the interaction networks of ACE2, especially cancerous diseases, obesity, hypertensive disease, Alzheimer's disease, non-insulin-dependent diabetes mellitus, and congestive heart failure. Among affected ACE2-network components connected with the SARS-Cov-2 interactome, we identified AGT (Angiotensinogen), CAT (Catalase), DPP4 (Dipeptidyl Peptidase 4), CCL2 (C-C Motif Chemokine Ligand 2), TFRC (Transferrin Receptor) and CAV1 (Caveolin-1), associated with cardiovascular risk factors. We described for the first time miRNAs which were common regulators of ACE2 networks and virus-related proteins in all analyzed datasets. The top miRNAs regulating ACE2 networks were miR-27a-3p, miR-26b-5p, miR-10b-5p, miR-302c-5p, hsa-miR-587, hsa-miR-1305, hsa-miR-200b-3p, hsa-miR-124-3p, and hsa-miR-16-5p.

CONCLUSION

Our study provides a complete mechanistic framework for investigating the ACE2 network which was validated by expression data. This framework predicted risk groups, including the established ones, thus providing reliable novel information regarding the complexity of signaling pathways affected by SARS-CoV-2. It also identified miRNAs that could be used in personalized diagnosis in COVID-19.

How Different Substitution Positions of F, Cl Atoms in Benzene Ring of 5-Methylpyrimidine Pyridine Derivatives Affect the Inhibition Ability of EGFRL858R/T790M/C797S Inhibitors: A Molecular Dynamics Simulation Study

Lung cancer is the most frequent cause of cancer-related deaths worldwide, and mutations in the kinase domain of the epidermal growth factor receptor (EGFR) are a common cause of non-small-cell lung cancers, which is a major subtype of lung cancers. Recently, a series of 5-methylpyrimidine-pyridinone derivatives have been designed and synthesized as novel selective inhibitors of EGFR and EGFR mutants. However, the binding-based inhibition mechanism has not yet been determined. In this study, we carried out molecular dynamic simulations and free-energy calculations for EGFR derivatives to fill this gap. Based on the investigation, the three factors that influence the inhibitory effect of inhibitors are as follows: (1) The substitution site of the Cl atom is the main factor influencing the activity through steric effect; (2) The secondary factors are repulsion between the F atom (present in the inhibitor) and Glu762, and the blocking effect of Lys745 on the phenyl ring of the inhibitor. (3) The two factors function synergistically to influence the inhibitory capacity of the inhibitor. The theoretical results of this study can provide further insights that will aid the design of oncogenic EGFR inhibitors with high selectivity.