SPEED2: inferring upstream pathway activity from differential gene expression

Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system

The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge-gathered from decades of detailed biochemical studies-allows us to obtain functional insights, focusing on gene regulatory processes and cell-cell interactions. We present diverse applications in immunology and critically assess underlying assumptions and limitations. Finally, we offer a perspective on the ongoing technological and algorithmic developments that promise to get us closer to a systemic mechanistic understanding of the immune system.

Bronchial epithelial transcriptomics and experimental validation reveal asthma severity-related neutrophilc signatures and potential treatments

Airway epithelial transcriptome analysis of asthma patients with different severity was used to disentangle the immune infiltration mechanisms affecting asthma exacerbation, which may be advantageous to asthma treatment. Here we introduce various bioinformatics methods and develop two models: an OVA/CFA-induced neutrophil asthma mouse model and an LPS-induced human bronchial epithelial cell damage model. Our objective is to investigate the molecular mechanisms, potential targets, and therapeutic strategies associated with asthma severity. Multiple bioinformatics methods identify meaningful differences in the degree of neutrophil infiltration in asthma patients with different severity. Then, PTPRC, TLR2, MMP9, FCGR3B, TYROBP, CXCR1, S100A12, FPR1, CCR1 and CXCR2 are identified as the hub genes. Furthermore, the mRNA expression of 10 hub genes is determined in vivo and in vitro models. Reperixin is identified as a pivotal drug targeting CXCR1, CXCR2 and MMP9. We further test the potential efficiency of Reperixin in 16HBE cells, and conclude that Reperixin can attenuate LPS-induced cellular damage and inhibit the expression of them. In this study, we successfully identify and validate several neutrophilic signatures and targets associated with asthma severity. Notably, Reperixin displays the ability to target CXCR1, CXCR2, and MMP9, suggesting its potential therapeutic value for managing deteriorating asthma.

Time-of-day-dependent variation of the human liver transcriptome and metabolome is disrupted in MASLD

Background & Aims

Liver homeostasis is ensured in part by time-of-day-dependent processes, many of them being paced by the molecular circadian clock. Liver functions are compromised in metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), and clock disruption increases susceptibility to MASLD progression in rodent models. We therefore investigated whether the time-of-day-dependent transcriptome and metabolome are significantly altered in human steatotic and MASH livers.

Methods

Liver biopsies, collected within an 8 h-window from a carefully phenotyped cohort of 290 patients and histologically diagnosed to be either normal, steatotic or MASH hepatic tissues, were analyzed by RNA sequencing and unbiased metabolomic approaches. Time-of-day-dependent gene expression patterns and metabolomes were identified and compared between histologically normal, steatotic and MASH livers.

Results

Herein, we provide a first-of-its-kind report of a daytime-resolved human liver transcriptome-metabolome and associated alterations in MASLD. Transcriptomic analysis showed a robustness of core molecular clock components in steatotic and MASH livers. It also revealed stage-specific, time-of-day-dependent alterations of hundreds of transcripts involved in cell-to-cell communication, intracellular signaling and metabolism. Similarly, rhythmic amino acid and lipid metabolomes were affected in pathological livers. Both TNFα and PPARγ signaling were predicted as important contributors to altered rhythmicity.

Conclusion

MASLD progression to MASH perturbs time-of-day-dependent processes in human livers, while the differential expression of core molecular clock components is maintained.

Impact and implications

This work characterizes the rhythmic patterns of the transcriptome and metabolome in the human liver. Using a cohort of well-phenotyped patients (n = 290) for whom the time-of-day at biopsy collection was known, we show that time-of-day variations observed in histologically normal livers are gradually perturbed in liver steatosis and metabolic dysfunction-associated steatohepatitis. Importantly, these observations, albeit obtained across a restricted time window, provide further support for preclinical studies demonstrating alterations of rhythmic patterns in diseased livers. On a practical note, this study indicates the importance of considering time-of-day as a critical biological variable which may significantly affect data interpretation in animal and human studies of liver diseases.

Quercetin is a Potential Therapy for Rheumatoid Arthritis via Targeting Caspase-8 Through Ferroptosis and Pyroptosis

Background

Rheumatoid arthritis (RA) is one of the most common chronic inflammatory autoimmune diseases. However, the underlying molecular mechanisms of its pathogenesis are unknown. This study aimed to identify the common biomarkers of ferroptosis and pyroptosis in RA and screen potential drugs.

Methods

The RA-related differentially expressed genes (DEGs) in GSE55235 were screened by R software and intersected with ferroptosis and pyroptosis gene libraries to obtain differentially expressed ferroptosis-related genes (DEFRGs) and differentially expressed pyroptosis-related genes (DEPRGs). We performed Gene Ontology (GO), Kyoto Encyclopedia of the Genome (KEGG), ClueGO, and Protein-Protein Interaction (PPI) analysis for DEFRGs and DEPRGs and validated them by machine learning. The microRNA/transcription factor (TF)-hub genes regulatory network was further constructed. The key gene was validated using the GSE77298 validation set, cellular validation was performed in in vitro experiments, and immune infiltration analysis was performed using CIBERSORT. Network pharmacology was used to find key gene-targeting drugs, followed by molecular docking and molecular dynamics simulations to analyze the binding stability between small-molecule drugs and large-molecule proteins.

Results

Three hub genes (CASP8, PTGS2, and JUN) were screened via bioinformatics, and the key gene (CASP8) was validated and obtained through the validation set, and the diagnostic efficacy was verified to be excellent through the receiver operating characteristic (ROC) curves. The ferroptosis and pyroptosis phenotypes were constructed by fibroblast-like synoviocytes (FLS), and caspase-8 was detected and validated as a common biomarker for ferroptosis and pyroptosis in RA, and quercetin can reduce caspase-8 levels. Quercetin was found to be a potential target drug for caspase-8 by network pharmacology, and the stability of their binding was further verified using molecular docking and molecular dynamics simulations.

Conclusion

Caspase-8 is an important biomarker for ferroptosis and pyroptosis in RA, and quercetin is a potential therapy for RA via targeting caspase-8 through ferroptosis and pyroptosis.

Neurodevelopmental disorders and cancer networks share pathways, but differ in mechanisms, signaling strength, and outcome

Epidemiological studies suggest that individuals with neurodevelopmental disorders (NDDs) are more prone to develop certain types of cancer. Notably, however, the case statistics can be impacted by late discovery of cancer in individuals afflicted with NDDs, such as intellectual disorders, autism, and schizophrenia, which may bias the numbers. As to NDD-associated mutations, in most cases, they are germline while cancer mutations are sporadic, emerging during life. However, somatic mosaicism can spur NDDs, and cancer-related mutations can be germline. NDDs and cancer share proteins, pathways, and mutations. Here we ask (i) exactly which features they share, and (ii) how, despite their commonalities, they differ in clinical outcomes. To tackle these questions, we employed a statistical framework followed by network analysis. Our thorough exploration of the mutations, reconstructed disease-specific networks, pathways, and transcriptome levels and profiles of autism spectrum disorder (ASD) and cancers, point to signaling strength as the key factor: strong signaling promotes cell proliferation in cancer, and weaker (moderate) signaling impacts differentiation in ASD. Thus, we suggest that signaling strength, not activating mutations, can decide clinical outcome.

Study of kaempferol in the treatment of COVID-19 combined with Chikungunya co-infection by network pharmacology and molecular docking technology

Chikungunya (CHIK) patients may be vulnerable to coronavirus disease (COVID-19). However, presently there are no anti-COVID-19/CHIK therapeutic alternatives available. The purpose of this research was to determine the pharmacological mechanism through which kaempferol functions in the treatment of COVID-19-associated CHIK co-infection. We have used a series of network pharmacology and computational analysis-based techniques to decipher and define the binding capacity, biological functions, pharmacological targets, and treatment processes in COVID-19-mediated CHIK co-infection. We identified key therapeutic targets for COVID-19/CHIK, including TP53, MAPK1, MAPK3, MAPK8, TNF, IL6 and NFKB1. Gene ontology, molecular and upstream pathway analysis of kaempferol against COVID-19 and CHIK showed that DEGs were confined mainly to the cytokine-mediated signalling pathway, MAP kinase activity, negative regulation of the apoptotic process, lipid and atherosclerosis, TNF signalling pathway, hepatitis B, toll-like receptor signaling, IL-17 and IL-18 signaling pathways. The study of the gene regulatory network revealed several significant TFs including KLF16, GATA2, YY1 and FOXC1 and miRNAs such as let-7b-5p, mir-16-5p, mir-34a-5p, and mir-155-5p that target differential-expressed genes (DEG). According to the molecular coupling results, kaempferol exhibited a high affinity for 5 receptor proteins (TP53, MAPK1, MAPK3, MAPK8, and TNF) compared to control inhibitors. In combination, our results identified significant targets and pharmacological mechanisms of kaempferol in the treatment of COVID-19/CHIK and recommended that core targets be used as potential biomarkers against COVID-19/CHIK viruses. Before conducting clinical studies for the intervention of COVID-19 and CHIK, kaempferol might be evaluated in wet lab tests at the molecular level.

Glucocorticoid activation of anti-inflammatory macrophages protects against insulin resistance

Insulin resistance (IR) during obesity is linked to adipose tissue macrophage (ATM)-driven inflammation of adipose tissue. Whether anti-inflammatory glucocorticoids (GCs) at physiological levels modulate IR is unclear. Here, we report that deletion of the GC receptor (GR) in myeloid cells, including macrophages in mice, aggravates obesity-related IR by enhancing adipose tissue inflammation due to decreased anti-inflammatory ATM leading to exaggerated adipose tissue lipolysis and severe hepatic steatosis. In contrast, GR deletion in Kupffer cells alone does not alter IR. Co-culture experiments show that the absence of GR in macrophages directly causes reduced phospho-AKT and glucose uptake in adipocytes, suggesting an important function of GR in ATM. GR-deficient macrophages are refractory to alternative ATM-inducing IL-4 signaling, due to reduced STAT6 chromatin loading and diminished anti-inflammatory enhancer activation. We demonstrate that GR has an important function in macrophages during obesity by limiting adipose tissue inflammation and lipolysis to promote insulin sensitivity.

Antineoplastic Nature of WWOX in Glioblastoma Is Mainly a Consequence of Reduced Cell Viability and Invasion

Following the discovery of WWOX, research has moved in many directions, including the role of this putative tumor suppressor in the central nervous system and related diseases. The task of determining the nature of WWOX in glioblastoma (GBM) is still considered to be at the initial stage; however, the influence of this gene on the GBM malignant phenotype has already been reported. Because most of the available in vitro research does not consider several cellular GBM models or a wide range of investigated biological assays, the present study aimed to determine the main processes by which WWOX exhibits anticancer properties in GBM, while taking into account the phenotypic heterogeneity between cell lines. Ectopic WWOX overexpression was studied in T98G, DBTRG-05MG, U251MG, and U87MG cell lines that were compared with the use of assays investigating cell viability, proliferation, apoptosis, adhesion, clonogenicity, three-dimensional and anchorage-independent growth, and invasiveness. Observations presenting the antineoplastic properties of WWOX were consistent for T98G, U251MG, and U87MG. Increased proliferation and tumor growth were noted in WWOX-overexpressing DBTRG-05MG cells. A possible explanation for this, arrived at via bioinformatics tools, was linked to the TARDBP transcription factor and expression differences of USP25 and CPNE2 that regulate EGFR surface abundance. Collectively, and despite various cell line-specific circumstances, WWOX exhibits its anticancer nature mainly via a reduction of cell viability and invasiveness of glioblastoma.

SARS-CoV-2 induces "cytokine storm" hyperinflammatory responses in RA patients through pyroptosis

Background

The coronavirus disease (COVID-19) is a pandemic disease that threatens worldwide public health, and rheumatoid arthritis (RA) is the most common autoimmune disease. COVID-19 and RA are each strong risk factors for the other, but their molecular mechanisms are unclear. This study aims to investigate the biomarkers between COVID-19 and RA from the mechanism of pyroptosis and find effective disease-targeting drugs.

Methods

We obtained the common gene shared by COVID-19, RA (GSE55235), and pyroptosis using bioinformatics analysis and then did the principal component analysis(PCA). The Co-genes were evaluated by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ClueGO for functional enrichment, the protein-protein interaction (PPI) network was built by STRING, and the k-means machine learning algorithm was employed for cluster analysis. Modular analysis utilizing Cytoscape to identify hub genes, functional enrichment analysis with Metascape and GeneMANIA, and NetworkAnalyst for gene-drug prediction. Network pharmacology analysis was performed to identify target drug-related genes intersecting with COVID-19, RA, and pyroptosis to acquire Co-hub genes and construct transcription factor (TF)-hub genes and miRNA-hub genes networks by NetworkAnalyst. The Co-hub genes were validated using GSE55457 and GSE93272 to acquire the Key gene, and their efficacy was assessed using receiver operating curves (ROC); SPEED2 was then used to determine the upstream pathway. Immune cell infiltration was analyzed using CIBERSORT and validated by the HPA database. Molecular docking, molecular dynamics simulation, and molecular mechanics-generalized born surface area (MM-GBSA) were used to explore and validate drug-gene relationships through computer-aided drug design.

Results

COVID-19, RA, and pyroptosis-related genes were enriched in pyroptosis and pro-inflammatory pathways(the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome complex, death-inducing signaling complex, regulation of interleukin production), natural immune pathways (Network map of SARS-CoV-2 signaling pathway, activation of NLRP3 inflammasome by SARS-CoV-2) and COVID-19-and RA-related cytokine storm pathways (IL, nuclear factor-kappa B (NF-κB), TNF signaling pathway and regulation of cytokine-mediated signaling). Of these, CASP1 is the most involved pathway and is closely related to minocycline. YY1, hsa-mir-429, and hsa-mir-34a-5p play an important role in the expression of CASP1. Monocytes are high-caspase-1-expressing sentinel cells. Minocycline can generate a highly stable state for biochemical activity by docking closely with the active region of caspase-1.

Conclusions

Caspase-1 is a common biomarker for COVID-19, RA, and pyroptosis, and it may be an important mediator of the excessive inflammatory response induced by SARS-CoV-2 in RA patients through pyroptosis. Minocycline may counteract cytokine storm inflammation in patients with COVID-19 combined with RA by inhibiting caspase-1 expression.

Anti-asthmatic fraction screening and mechanisms prediction of Schisandrae Sphenantherae Fructus based on a combined approach

Objective: Schisandrae Sphenantherae Fructus (SSF) is a traditional Chinese medicine used to treat coughs and pulmonary inflammatory diseases. However, the pharmacodynamic material basis and mechanisms for SSF in asthma treatment remain unclear. This study aims to screen the anti-asthmatic fraction and verify the pharmacodynamic material basis, predict the potential mechanism, and verify the interaction ability between compounds and core targets.

Methods: First, three fractions from SSF were compared in terms of composition, comparison, and anti-asthmatic effects. Then, the ultra-performance liquid chromatography-quadrupole/time-of-flight-mass spectrometry/mass spectrometry (UPLC-Q/TOF-MS/MS) strategy was used to identify the compounds from the active fraction, and the anti-asthmatic efficacy of the active fraction was further studied by the ovalbumin (OVA)-induced asthma murine model. Finally, network pharmacology and molecular methods were used to study the relationships between active compounds, core targets, and key pathways of PEF in asthma treatments.

Results: The petroleum ether fraction (PEF) of SSF showed better effects and could significantly diminish lung inflammation and mitigate the level of serum immunoglobulin E (IgE), interleukin (IL)-4, IL-5, IL-6, IL-13, and IL-17 in mice. A total of 26 compounds from the PEF were identified, among which the main compounds are lignans and triterpenes. Moreover, 21 active compounds, 129 overlap-ping targets, and 10 pathways were screened by network pharmacology tools. The top five core targets may play a great role in asthma treatment. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that the PEF can treat asthma by acting on multiple asthma pathological processes, including the IL-17 signaling pathway, T helper (Th) 17 cell differentiation, and the calcium signaling pathway. Molecular docking was performed to evaluate the interactions of the protein–ligand binding, and most docked complexes had a good binding ability.

Conclusion: The present results might contribute to exploring the active compounds with anti-asthmatic activity.

Insights into potential mechanisms of asthma patients with COVID-19: A study based on the gene expression profiling of bronchoalveolar lavage fluid

Background

The 2019 novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a major challenge threatening the global healthcare system. Respiratory virus infection is the most common cause of asthma attacks, and thus COVID-19 may contribute to an increase in asthma exacerbations. However, the mechanisms of COVID-19/asthma comorbidity remain unclear.

Methods

The “Limma” package or “DESeq2” package was used to screen differentially expressed genes (DEGs). Alveolar lavage fluid datasets of COVID-19 and asthma were obtained from the GEO and GSV database. A series of analyses of common host factors for COVID-19 and asthma were conducted, including PPI network construction, module analysis, enrichment analysis, inference of the upstream pathway activity of host factors, tissue-specific analysis and drug candidate prediction. Finally, the key host factors were verified in the GSE152418 and GSE164805 datasets.

Results

192 overlapping host factors were obtained by analyzing the intersection of asthma and COVID-19. FN1, UBA52, EEF1A1, ITGB1, XPO1, NPM1, EGR1, EIF4E, SRSF1, CCR5, PXN, IRF8 and DDX5 as host factors were tightly connected in the PPI network. Module analysis identified five modules with different biological functions and pathways. According to the degree values ranking in the PPI network, EEF1A1, EGR1, UBA52, DDX5 and IRF8 were considered as the key cohost factors for COVID-19 and asthma. The H₂O₂, VEGF, IL-1 and Wnt signaling pathways had the strongest activities in the upstream pathways. Tissue-specific enrichment analysis revealed the different expression levels of the five critical host factors. LY294002, wortmannin, PD98059 and heparin might have great potential to evolve into therapeutic drugs for COVID-19 and asthma comorbidity. Finally, the validation dataset confirmed that the expression of five key host factors were statistically significant among COVID-19 groups with different severity and healthy control subjects.

Conclusions

This study constructed a network of common host factors between asthma and COVID-19 and predicted several drugs with therapeutic potential. Therefore, this study is likely to provide a reference for the management and treatment for COVID-19/asthma comorbidity.

Exploring Pathway-Based Group Lasso for Cancer Survival Analysis: A Special Case of Multi-Task Learning

Motivation: The Cox proportional hazard models are widely used in the study of cancer survival. However, these models often meet challenges such as the large number of features and small sample sizes of cancer data sets. While this issue can be partially solved by applying regularization techniques such as lasso, the models still suffer from unsatisfactory predictive power and low stability.

Methods: Here, we investigated two methods to improve survival models. Firstly, we leveraged the biological knowledge that groups of genes act together in pathways and regularized both at the group and gene level using latent group lasso penalty term. Secondly, we designed and applied a multi-task learning penalty that allowed us leveraging the relationship between survival models for different cancers.

Results: We observed modest improvements over the simple lasso model with the inclusion of latent group lasso penalty for six of the 16 cancer types tested. The addition of a multi-task penalty, which penalized coefficients in pairs of cancers from diverging too greatly, significantly improved accuracy for a single cancer, lung squamous cell carcinoma, while having minimal effect on other cancer types.

Conclusion: While the use of pathway information and multi-tasking shows some promise, these methods do not provide a substantial improvement when compared with standard methods.

Regulation of Long Non-coding RNA KCNQ1OT1 Network in Colorectal Cancer Immunity

Over the past few decades, researchers have become aware of the importance of non-coding RNA, which makes up the vast majority of the transcriptome. Long non-coding RNAs (lncRNAs) in turn constitute the largest fraction of non-coding transcripts. Increasing evidence has been found for the crucial roles of lncRNAs in both tissue homeostasis and development, and for their functional contributions to and regulation of the development and progression of various human diseases such as cancers. However, so far, only few findings with regards to functional lncRNAs in cancers have been translated into clinical applications. Based on multiple factors such as binding affinity of miRNAs to their lncRNA sponges, we analyzed the competitive endogenous RNA (ceRNA) network for the colorectal cancer RNA-seq datasets from The Cancer Genome Atlas (TCGA). After performing the ceRNA network construction and survival analysis, the lncRNA KCNQ1OT1 was found to be significantly upregulated in colorectal cancer tissues and associated with the survival of patients. A KCNQ1OT1-related lncRNA-miRNA-mRNA ceRNA network was constructed. A gene set variation analysis (GSVA) indicated that the expression of the KCNQ1OT1 ceRNA network in colorectal cancer tissues and normal tissues were significantly different, not only in the TCGA-COAD dataset but also in three other GEO datasets used as validation. By predicting comprehensive immune cell subsets from gene expression data, in samples grouped by differential expression levels of the KCNQ1OT1 ceRNA network in a cohort of patients, we found that CD4⁺, CD8⁺, and cytotoxic T cells and 14 other immune cell subsets were at different levels in the high- and low-KCNQ1OT1 ceRNA network score groups. These results indicated that the KCNQ1OT1 ceRNA network could be involved in the regulation of the tumor microenvironment, which would provide the rationale to further exploit KCNQ1OT1 as a possible functional contributor to and therapeutic target for colorectal cancer.

Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome - A multi-omics big data study

Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infection and pathogenesis. Recent studies highlight the possible contribution of atmospheric air pollution, specifically particulate matter (PM) exposure as a co-factor in COVID-19 severity. Hence, meaningful translation of suitable omics datasets of SARS-CoV-2 infection and PM exposure is warranted to understand the possible involvement of airborne exposome on COVID-19 outcome. Publicly available transcriptomic data (microarray and RNA-Seq) related to COVID-19 lung biopsy, SARS-CoV-2 infection in epithelial cells and PM exposure (lung tissue, epithelial and endothelial cells) were obtained in addition with proteome and interactome datasets. System-wide pathway/network analysis was done through appropriate software tools and data resources. The primary findings are; 1. There is no robust difference in the expression of SARS-CoV-2 entry factors upon particulate exposure, 2. The upstream pathways associated with upregulated genes during SARS-CoV-2 infection considerably overlap with that of PM exposure, 3. Similar pathways were differentially expressed during SARS-CoV-2 infection and PM exposure, 4. SARS-CoV-2 interacting host factors were predicted to be associated with the molecular impact of PM exposure and 5. Differentially expressed pathways during PM exposure may increase COVID-19 severity. Based on the observed molecular mechanisms (direct and indirect effects) the current study suggests that airborne PM exposure has to be considered as an additional co-factor in the outcome of COVID-19.

Identification of COVID-19 and Dengue Host Factor Interaction Networks Based on Integrative Bioinformatics Analyses

Background

The outbreak of Coronavirus disease 2019 (COVID-19) has become an international public health crisis, and the number of cases with dengue co-infection has raised concerns. Unfortunately, treatment options are currently limited or even unavailable. Thus, the aim of our study was to explore the underlying mechanisms and identify potential therapeutic targets for co-infection.

Methods

To further understand the mechanisms underlying co-infection, we used a series of bioinformatics analyses to build host factor interaction networks and elucidate biological process and molecular function categories, pathway activity, tissue-specific enrichment, and potential therapeutic agents.

Results

We explored the pathologic mechanisms of COVID-19 and dengue co-infection, including predisposing genes, significant pathways, biological functions, and possible drugs for intervention. In total, 460 shared host factors were collected; among them, CCL4 and AhR targets were important. To further analyze biological functions, we created a protein-protein interaction (PPI) network and performed Molecular Complex Detection (MCODE) analysis. In addition, common signaling pathways were acquired, and the toll-like receptor and NOD-like receptor signaling pathways exerted a significant effect on the interaction. Upregulated genes were identified based on the activity score of dysregulated genes, such as IL-1, Hippo, and TNF-α. We also conducted tissue-specific enrichment analysis and found ICAM-1 and CCL2 to be highly expressed in the lung. Finally, candidate drugs were screened, including resveratrol, genistein, and dexamethasone.

Conclusions

This study probes host factor interaction networks for COVID-19 and dengue and provides potential drugs for clinical practice. Although the findings need to be verified, they contribute to the treatment of co-infection and the management of respiratory disease.

Glycyrrhizic Acid for COVID-19: Findings of Targeting Pivotal Inflammatory Pathways Triggered by SARS-CoV-2

Background: Coronavirus disease 2019 (COVID-19) is now a worldwide public health crisis. The causative pathogen is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Novel therapeutic agents are desperately needed. Because of the frequent mutations in the virus and its ability to cause cytokine storms, targeting the viral proteins has some drawbacks. Targeting cellular factors or pivotal inflammatory pathways triggered by SARS-CoV-2 may produce a broader range of therapies. Glycyrrhizic acid (GA) might be beneficial against SARS-CoV-2 because of its anti-inflammatory and antiviral characteristics and possible ability to regulate crucial host factors. However, the mechanism underlying how GA regulates host factors remains to be determined.

Methods: In our report, we conducted a bioinformatics analysis to identify possible GA targets, biological functions, protein-protein interactions, transcription-factor-gene interactions, transcription-factor-miRNA coregulatory networks, and the signaling pathways of GA against COVID-19.

Results: Protein-protein interactions and network analysis showed that ICAM1, MMP9, TLR2, and SOCS3 had higher degree values, which may be key targets of GA for COVID-19. GO analysis indicated that the response to reactive oxygen species was significantly enriched. Pathway enrichment analysis showed that the IL-17, IL-6, TNF-α, IFN signals, complement system, and growth factor receptor signaling are the main pathways. The interactions of TF genes and miRNA with common targets and the activity of TFs were also recognized.

Conclusions: GA may inhibit COVID-19 through its anti-oxidant, anti-viral, and anti-inflammatory effects, and its ability to activate the immune system, and targeted therapy for those pathways is a predominant strategy to inhibit the cytokine storms triggered by SARS-CoV-2 infection.

Quercetin for COVID-19 and DENGUE co-infection: a potential therapeutic strategy of targeting critical host signal pathways triggered by SARS-CoV-2 and DENV

Background

The clinical consequences of SARS-CoV-2 and DENGUE virus co-infection are not promising. However, their treatment options are currently unavailable. Current studies have shown that quercetin is both resistant to COVID-19 and DENGUE; this study aimed to evaluate the possible functional roles and underlying mechanisms of action of quercetin as a potential molecular candidate against COVID-19 and DENGUE co-infection.

Methods

We used a series of bioinformatics analyses to understand and characterize the biological functions, pharmacological targets and therapeutic mechanisms of quercetin in COVID-19 and DENGUE co-infection.

Results

We revealed the clinical characteristics of COVID-19 and DENGUE, including pathological mechanisms, key inflammatory pathways and possible methods of intervention, 60 overlapping targets related to the co-infection and the drug were identified, the protein–protein interaction (PPI) was constructed and TNFα, CCL-2 and CXCL8 could become potential drug targets. Furthermore, we disclosed the signaling pathways, biological functions and upstream pathway activity of quercetin in COVID-19 and DENGUE. The analysis indicated that quercetin could inhibit cytokines release, alleviate excessive immune responses and eliminate inflammation, through NF-κB, IL-17 and Toll-like receptor signaling pathway.

Conclusions

This study is the first to reveal quercetin as a pharmacological drug for COVID-19 and DENGUE co-infection. COVID-19 and DENGUE co-infection remain a potential threat to the world’s public health system. Therefore, we need innovative thinking to provide admissible evidence for quercetin as a potential molecule drug for the treatment of COVID-19 and DENGUE, but the findings have not been verified in actual patients, so further clinical drug trials are needed.

Comprehensive Integration of Genome-Wide Association and Gene Expression Studies Reveals Novel Gene Signatures and Potential Therapeutic Targets for Helicobacter pylori-Induced Gastric Disease

Helicobacter pylori is a gram-negative bacterium that colonizes the human gastric mucosa and can lead to gastric inflammation, ulcers, and stomach cancer. Due to the increase in H. pylori antimicrobial resistance new methods to identify the molecular mechanisms of H. pylori-induced pathology are urgently needed. Here we utilized a computational biology approach, harnessing genome-wide association and gene expression studies to identify genes and pathways determining disease development. We mined gene expression data related to H. pylori-infection and its complications from publicly available databases to identify four human datasets as discovery datasets and used two different multi-cohort analysis pipelines to define a H. pylori-induced gene signature. An initial Helicobacter-signature was curated using the MetaIntegrator pipeline and validated in cell line model datasets. With this approach we identified cell line models that best match gene regulation in human pathology. A second analysis pipeline through NetworkAnalyst was used to refine our initial signature. This approach defined a 55-gene signature that is stably deregulated in disease conditions. The 55-gene signature was validated in datasets from human gastric adenocarcinomas and could separate tumor from normal tissue. As only a small number of H. pylori patients develop cancer, this gene-signature must interact with other host and environmental factors to initiate tumorigenesis. We tested for possible interactions between our curated gene signature and host genomic background mutations and polymorphisms by integrating genome-wide association studies (GWAS) and known oncogenes. We analyzed public databases to identify genes harboring single nucleotide polymorphisms (SNPs) associated with gastric pathologies and driver genes in gastric cancers. Using this approach, we identified 37 genes from GWA studies and 61 oncogenes, which were used with our 55-gene signature to map gene-gene interaction networks. In conclusion, our analysis defines a unique gene signature driven by H. pylori-infection at early phases and that remains relevant through different stages of pathology up to gastric cancer, a stage where H. pylori itself is rarely detectable. Furthermore, this signature elucidates many factors of host gene and pathway regulation in infection and can be used as a target for drug repurposing and testing of infection models suitability to investigate human infection.

Derivation and Application of Molecular Signatures to Prostate Cancer: Opportunities and Challenges

Prostate cancer is a high-incidence cancer that requires improved patient stratification to ensure accurate predictions of risk and treatment response. Due to the significant contributions of transcription factors and epigenetic regulators to prostate cancer progression, there has been considerable progress made in developing gene signatures that may achieve this. Some of these are aligned to activities of key drivers such as the androgen receptor, whilst others are more agnostic. In this review, we present an overview of these signatures, the strategies for their derivation, and future perspectives on their continued development and evolution.