CTD Anatomy: analyzing chemical-induced phenotypes and exposures from an anatomical perspective, with implications for environmental health studies

Discovery of natural multi-targets neuraminidase inhibitor glycosides compounds against influenza A virus through network pharmacology, virtual screening, molecular dynamics simulation, and in vitro experiment

Influenza virus continually challenges both human and animal health. Moreover, influenza viruses are easy to mutate. In a certain degree, vaccines may not catch up with rapid mutant paces of viruses. Anti-influenza drugs NIs (neuraminidase inhibitors) are one of the best choices. Therefore, based on ADMET properties, eight optimal natural multi-targets NIs glycosides compounds (IC50  = 0.094-97.275 μM) are found from radix glycyrrhizae, flos sophorae, caulis spatholobi, radix astragali, radix glycyrrhizae, semen astragali complanati, and common fenugreek seed through network pharmacology, molecular docking, dynamics simulation, quantum chemistry, and in vitro experiment. Moreover, mechanism research illustrates these natural compounds treat influenza A virus through key targets TLR4, TNF, and IL6 (high fever, acute respiratory distress syndrome), MAPK1, and MAPK3 (MAPK signaling pathway, viral RNP export, and viral protein expression), IL1B (NOD-like receptor signaling pathway, suppressed maturation of pro-IL-1β and pro-IL-18), CASP3 (apoptosis), AKT1 (inhibited premature apoptosis), and EP300 (viral myocarditis, chemoattraction of monocytes and macrophages, T-cell activation antibody response).

Integrative Analysis of Core Genes and Biological Process Involved in Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a common gynecological endocrine disordered disease, affecting the function of the ovaries in women of reproductive age. However, there are limited curative therapies for PCOS due to lack of reliable candidates. Hence, this study aimed to identify hub pathogenic genes and potential therapeutic targets for PCOS using bioinformatics tools. We obtained the expression profiles of 29 PCOS samples and 24 normal samples from three Gene Expression Omnibus (GEO) datasets. Then, the differentially expressed genes (DEGs) were screened, which were subjected to functional enrichment analyses. Moreover, we found 30 ferroptosis-related genes out of the 89 DEGs. Among the top 10 significant ferroptosis-related DEGs, 8 genes showed good predictive performance. We constructed interaction network of top three ferroptosis-related DEGs (SLC38A1, ACO1, DDIT3). Finally, real-time PCR was performed to test the relative expression of these genes. In conclusions, we have identified ferroptosis-related DEGs as core genes and potential therapeutic targets of PCOS based on comprehensive bioinformatics analysis. The findings are conducive to understanding of the pathogenesis of PCOS and paving the way towards curative therapies.

CTD tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health

The molecular mechanisms connecting environmental exposures to adverse endpoints are often unknown, reflecting knowledge gaps. At the Comparative Toxicogenomics Database (CTD), we developed a bioinformatics approach that integrates manually curated, literature-based interactions from CTD to generate a "CGPD-tetramer": a 4-unit block of information organized as a step-wise molecular mechanism linking an initiating Chemical, an interacting Gene, a Phenotype, and a Disease outcome. Here, we describe a novel, user-friendly tool called CTD Tetramers that generates these evidence-based CGPD-tetramers for any curated chemical, gene, phenotype, or disease of interest. Tetramers offer potential solutions for the unknown underlying mechanisms and intermediary phenotypes connecting a chemical exposure to a disease. Additionally, multiple tetramers can be assembled to construct detailed modes-of-action for chemical-induced disease pathways. As well, tetramers can help inform environmental influences on adverse outcome pathways (AOPs). We demonstrate the tool's utility with relevant use cases for a variety of environmental chemicals (eg, perfluoroalkyl substances, bisphenol A), phenotypes (eg, apoptosis, spermatogenesis, inflammatory response), and diseases (eg, asthma, obesity, male infertility). Finally, we map AOP adverse outcome terms to corresponding CTD terms, allowing users to query for tetramers that can help augment AOP pathways with additional stressors, genes, and phenotypes, as well as formulate potential AOP disease networks (eg, liver cirrhosis and prostate cancer). This novel tool, as part of the complete suite of tools offered at CTD, provides users with computational datasets and their supporting evidence to potentially fill exposure knowledge gaps and develop testable hypotheses about environmental health.

Genetic analysis of potential biomarkers and therapeutic targets in neuroinflammation from sporadic Creutzfeldt-Jakob disease

This study aimed to identify hub genes and pathological mechanisms related to neuroinflammation in Sporadic Creutzfeldt-Jakob disease (SCJD) based on comprehensive bioinformatics. SCJD and normal samples were collected from GSE160208. Weighted gene co-expression network analysis (WGCNA) and Limma R package were used to obtain key genes, which were used for enrichment and immune cell infiltration analyses. Protein-protein interaction (PPI) network, cytoHubba, and machine learning were used to screen the central genes of SCJD. The chemicals related to hub genes were predicted and explored by molecular docking. 88 candidate genes were screened. Enrichment analysis showed they were mainly related to bacterial and viral infection and immune cell activation. Immune cell infiltration analysis suggested that immune cell activation and altered activity of the immune system are involved in the progression of SCJD. After identifying hub genes, KIT and SPP1 had higher diagnostic efficacy for SCJD (AUC > 0.9), so they were identified as central genes. The molecular docking results showed hub genes both docked well with Tretinoin. KIT, SPP1, and Tretinoin are essential in developing neuroinflammation in SCJD and may provide new ideas for diagnosing and treating SCJD.

Construction of predictive ceRNA network and identification of the patterns of immune cells infiltrated in Graves ophthalmopathy

OBJECTIVES

Graves' ophthalmopathy (GO) is a multifactorial disease, and the mechanism of non coding RNA interactions and inflammatory cell infiltration patterns are not fully understood. This study aims to construct a competing endogenous RNA (ceRNA) network for this disease and clarify the infiltration patterns of inflammatory cells in orbital tissue to further explore the pathogenesis of GO.

METHODS

The differentially expressed genes were identified using the GEO2R analysis tool. The Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology analysis were used to analyze differential genes. RNA interaction relationships were extracted from the RNA interactome database. Protein-protein interactions were identified using the STRING database and were visualized using Cytoscape. StarBase, miRcode, and DIANA-LncBase Experimental v.2 were used to construct ceRNA networks together with their interacted non-coding RNA. The CIBERSORT algorithm was used to detect the patterns of infiltrating immune cells in GO using R software.

RESULTS

A total of 114 differentially expressed genes for GO and 121 pathways were detected using both the KEGG and gene ontology enrichment analysis. Four hub genes (SRSF6, DDX5, HNRNPC,and HNRNPM) were extracted from protein-protein interaction using cytoHubba in Cytoscape, 104 nodes and 142 edges were extracted, and a ceRNA network was identified (MALAT1-MIR21-DDX5). The results of immune cell analysis showed that in GO, the proportions of CD8+ T cells and CD4+ memory resting T cells were upregulated and downregulated, respectively. The proportion of CD4 memory resting T cells was positively correlated with the expression of MALAT1, MIR21, and DDX5.

CONCLUSIONS

This study has constructed a ceRNA regulatory network (MALAT1-MIR21-DDX5) in GO orbital tissue, clarifying the downregulation of the proportion of CD4+ stationary memory T cells and their positive regulatory relationship with ceRNA components, further revealing the pathogenesis of GO.

Integrative Data Mining Approach: Case Study with Adverse Outcome Pathway Network Leading to Pulmonary Fibrosis

An adverse outcome pathway (AOP) framework can be applied as an efficient tool for the rapid screening of environmental chemicals. For the development of an AOP, a database mining approach can support an expert derivation approach by gathering a wider range of evidence than in a literature review. In this study, data from various databases were integrated and analyzed to supplement the AOP leading to pulmonary fibrosis by analyzing additional evidence using a data mining approach and establishing an application domain for chemicals. First, we collected chemicals, genes, and phenotypes that were studied and related to pulmonary fibrosis through the Comparative Toxicogenomics Database (CTD). CGPD-tetramers constructed by linking each related chemical, gene, phenotype, and disease can provide the basic components for the assembly of putative AOPs. Next, an AOP network was established by connecting eight existing AOPs for pulmonary fibrosis developed by expert derivation from the AOP Wiki. Finally, the pulmonary fibrosis AOP network was proposed by integrating the AOP network from AOP Wiki and the CGPD-tetramers from the CTD. To prioritize potential chemical stressors in the AOP network, 61 chemicals were ranked using the relevance of the chemical to the AOP and chemical exposure information from the CompTox Chemicals Dashboard. The approach proposed in this study can guide the utilization of available evidence from various databases as well as the literature in constructing AOP networks related to specific diseases.

In silico assessment of mixture toxicity mechanisms involved in the pathogenesis of thyroid diseases: the combination of toxic metal(oid)s and decabrominated diphenyl ether

The current study aimed to assess the connection between the mixture of lead (Pb), cadmium (Cd), arsenic (As), methylmercury (MeHg) and decabrominated diphenyl ether (decaBDE) and thyroid function, by using in silico toxicogenomic data-mining approach. To obtain the linkage between investigated toxic mixture and thyroid diseases (TDs), the Comparative Toxicogenomics Database (CTD) was used, while gene ontology (GO) enrichment analysis was performed by ToppGeneSuite portal. The analysis has shown 10 genes connected to all chemicals present in the mixture and TDs (CAT, GSR, IFNG, IL1B, IL4, IL6, MAPK1, SOD2, TGFB1, TNF), most of which were in co-expression (45.68%), or belonged to the same pathway (30.47%). Top 5 biological processes and molecular functions affected by the investigated mixture emphasized the role of two common mechanisms - oxidative stress and inflammation. Cytokines and inflammatory response was listed as the main molecular pathway that may be triggered by simultaneous exposure to toxic metal(oid)s and decaBDE and connected to TDs. The direct relations between Pb/decaBDE and redox status impairment in thyroid tissue was confirmed by our chemical-phenotype interaction analysis, while the strongest linkage between Pb, As and decaBDE and thyroid disorders was found. The obtained results provide better understanding of molecular mechanisms involved in the thyrotoxicity of the investigated mixture, and can be used to direct further research.

Deciphering the protective effect of Buzhong Yiqi Decoction on osteoporotic fracture through network pharmacology and experimental validation

BACKGROUND

Osteoporotic fracture (OPF) is one of the most common skeletal diseases in an aging society. The Chinese medicine formula Buzhong Yiqi Decoction (BZYQD) is commonly used for treating OPF. However, the essential bioactive compounds and the underlying molecular mechanisms that promote fracture repair remain unclear.

METHODS

We used network pharmacology and experimental animal validation to address this issue. First, 147 bioactive BZYQD compounds and 32 target genes for treating OPF were screened and assessed. A BZYQD-bioactive compound-target gene-disease network was constructed using the Cytoscape software. Functional enrichment showed that the candidate target genes were enriched in oxidative stress- and inflammation-related biological processes and multiple pathways, including nuclear factor kappa B (NF-κB), and mitogen-activated protein kinase (MAPK) signaling pathways. Furthermore, an OPF rat model was established and treated with BZYQD.

RESULTS

The results revealed that BZYQD ameliorated OPF characteristics, including femoral microarchitecture, biomechanical properties, and histopathological changes, in a dose-dependent manner. Results of enzyme-linked immunosorbent assay showed that BZYQD reduced the serum's pro-inflammatory cytokines [Tumor necrosis factor-alpha (TNF-α), Interleukin (IL)-1β, and IL-6] and improved oxidative stress-related factors [glutathione (GSH) and superoxide dismutase (SOD)]. BZYQD significantly decreased the protein expression of NF-κB in OPF rat femurs, suppressed NF-κB activation, and activated the nuclear factor-erythroid factor 2-related factor (Nrf2)/heme oxygenase 1 (HO-1) and p38 MAPK as well ERK pathways.

CONCLUSIONS

Our results suggest that BZYQD could improve inflammation and oxidative stress during fracture repair by suppressing NF-κB and activating Nrf2/MAPK signaling pathways.

Systematic evidence map (SEM) template: Report format and methods used for the US EPA Integrated Risk Information System (IRIS) program, Provisional Peer Reviewed Toxicity Value (PPRTV) program, and other "fit for purpose" literature-based human health analyses

BACKGROUND

Systematic evidence maps (SEMs) are gaining visibility in environmental health for their utility to serve as problem formulation tools and assist in decision-making, especially for priority setting. SEMs are now routinely prepared as part of the assessment development process for the US Environmental Protection Agency (EPA) Integrated Risk Information System (IRIS) and Provisional Peer Reviewed Toxicity Value (PPRTV) assessments. SEMs can also be prepared to explore the available literature for an individual chemical or groups of chemicals of emerging interest.

OBJECTIVES

This document describes the typical methods used to produce SEMs for the IRIS and PPRTV Programs, as well as "fit for purpose" applications using a variety of examples drawn from existing analyses. It is intended to serve as an example base template that can be adapted as needed for the specific SEM. The presented methods include workflows intended to facilitate rapid production. The Populations, Exposures, Comparators and Outcomes (PECO) criteria are typically kept broad to identify mammalian animal bioassay and epidemiological studies that could be informative for human hazard identification. In addition, a variety of supplemental content is tracked, e.g., studies presenting information on in vitro model systems, non-mammalian model systems, exposure-level-only studies in humans, pharmacokinetic models, and absorption, distribution, metabolism, and excretion (ADME). The availability of New Approach Methods (NAMs) evidence is also tracked (e.g., high throughput, transcriptomic, in silico, etc.). Genotoxicity studies may be considered as PECO relevant or supplemental material, depending on the topic and context of the review. Standard systematic review practices (e.g., two independent reviewers per record) and specialized software applications are used to search and screen the literature and may include the use of machine learning software. Mammalian bioassay and epidemiological studies that meet the PECO criteria after full-text review are briefly summarized using structured web-based extraction forms with respect to study design and health system(s) assessed. Extracted data is available in interactive visual formats and can be downloaded in open access formats. Methods for conducting study evaluation are also presented which is conducted on a case-by-case basis, depending on the usage of the SEM.

Circulating (Poly)phenol Metabolites: Neuroprotection in a 3D Cell Model of Parkinson's Disease

SCOPE

Diets rich in (poly)phenols have been associated with positive effects on neurodegenerative disorders, such as Parkinson's disease (PD). Several low-molecular weight (poly)phenol metabolites (LMWPM) are found in the plasma after consumption of (poly)phenol-rich food. It is expected that LMWPM, upon reaching the brain, may have beneficial effects against both oxidative stress and neuroinflammation, and possibly attenuate cell death mechanisms relate to the loss of dopaminergic neurons in PD.

METHODS AND RESULTS

This study investigates the neuroprotective potential of two blood-brain barrier permeant LMWPM, catechol-O-sulfate (cat-sulf), and pyrogallol-O-sulfate (pyr-sulf), in a human 3D cell model of PD. Neurospheroids were generated from LUHMES neuronal precursor cells and challenged by 1-methyl-4-phenylpyridinium (MPP⁺ ) to induce neuronal stress. LMWPM pretreatments were differently neuroprotective towards MPP⁺ insult, presenting distinct effects on the neuronal transcriptome. Particularly, cat-sulf pretreatment appeared to boost counter-regulatory defense mechanisms (preconditioning). When MPP⁺ is applied, both LMWPM positively modulated glutathione metabolism and heat-shock response, as also favorably shifting the balance of pro/anti-apoptotic proteins.

CONCLUSIONS

Our findings point to the potential of LMWPM to trigger molecular mechanisms that help dopaminergic neurons to cope with a subsequent toxic insult. They are promising molecules to be further explored in the context of preventing and attenuating parkinsonian neurodegeneration.

A transcriptome-wide association study of uterine fibroids to identify potential genetic markers and toxic chemicals

Uterine fibroid is one of the most prevalent benign tumors in women, with high socioeconomic costs. Although genome-wide association studies (GWAS) have identified several loci associated with uterine fibroid risks, they could not successfully interpret the biological effects of genomic variants at the gene expression levels. To prioritize uterine fibroid susceptibility genes that are biologically interpretable, we conducted a transcriptome-wide association study (TWAS) by integrating GWAS data of uterine fibroid and expression quantitative loci data. We identified nine significant TWAS genes including two novel genes, RP11-282O18.3 and KBTBD7, which may be causal genes for uterine fibroid. We conducted functional enrichment network analyses using the TWAS results to investigate the biological pathways in which the overall TWAS genes were involved. The results demonstrated the immune system process to be a key pathway in uterine fibroid pathogenesis. Finally, we carried out chemical–gene interaction analyses using the TWAS results and the comparative toxicogenomics database to determine the potential risk chemicals for uterine fibroid. We identified five toxic chemicals that were significantly associated with uterine fibroid TWAS genes, suggesting that they may be implicated in the pathogenesis of uterine fibroid. In this study, we performed an integrative analysis covering the broad application of bioinformatics approaches. Our study may provide a deeper understanding of uterine fibroid etiologies and informative notifications about potential risk chemicals for uterine fibroid.

Comparative Toxicogenomics Database (CTD): update 2023

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) harmonizes cross-species heterogeneous data for chemical exposures and their biological repercussions by manually curating and interrelating chemical, gene, phenotype, anatomy, disease, taxa, and exposure content from the published literature. This curated information is integrated to generate inferences, providing potential molecular mediators to develop testable hypotheses and fill in knowledge gaps for environmental health. This dual nature, acting as both a knowledgebase and a discoverybase, makes CTD a unique resource for the scientific community. Here, we report a 20% increase in overall CTD content for 17 100 chemicals, 54 300 genes, 6100 phenotypes, 7270 diseases and 202 000 exposure statements. We also present CTD Tetramers, a novel tool that computationally generates four-unit information blocks connecting a chemical, gene, phenotype, and disease to construct potential molecular mechanistic pathways. Finally, we integrate terms for human biological media used in the CTD Exposure module to corresponding CTD Anatomy pages, allowing users to survey the chemical profiles for any tissue-of-interest and see how these environmental biomarkers are related to phenotypes for any anatomical site. These, and other webpage visual enhancements, continue to promote CTD as a practical, user-friendly, and innovative resource for finding information and generating testable hypotheses about environmental health.

Identifying and characterizing drug sensitivity-related lncRNA-TF-gene regulatory triplets

Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient’s expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment.

Identification of molecular mechanisms underlying the therapeutic effects of Xintong granule in coronary artery disease by a network pharmacology and molecular docking approach

Coronary artery disease (CAD) is a cardiovascular disease characterized by atherosclerosis, angiogenesis, thrombogenesis, inflammation, etc. Xintong granule (XTG) is considered a practical therapeutic strategy in China for CAD. Although its therapeutic role in CAD has been reported, the molecular mechanisms of XTG in CAD have not yet been explored. A network pharmacology approach including drug-likeness (DL) evaluation, oral bioavailability (OB) prediction, protein-protein interaction (PPI) network construction and analysis, and Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses was used to predict the active ingredients, potential targets, and molecular mechanisms of XTG associated with the treatment of CAD. Molecular docking analysis was performed to investigate the interactions between the active compounds and the underlying targets. Fifty-one active ingredients of XTG and 294 CAD-related targets were screened for analysis. Gene Ontology enrichment analysis showed that the therapeutic targets of XTG in CAD are mainly involved in blood circulation and vascular regulation. KEGG pathway analysis indicated that XTG intervenes in CAD mainly through the regulation of fluid shear stress and atherosclerosis, the AGE-RAGE signaling pathway in diabetic complications, and the relaxin signaling pathway. Molecular docking analysis showed that each key active ingredient (quercetin, luteolin, kaempferol, stigmasterol, resveratrol, fisetin, gamma-sitosterol, and beta-sitosterol) of XTG can bind to the core targets of CAD (AKT1, JUN, RELA, MAPK8, NFKB1, EDN1, and NOS3). The present study revealed the CAD treatment-related active ingredients, underlying targets, and potential molecular mechanisms of XTG acting by regulating fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, and relaxin signaling pathway.

Associating diethylhexyl phthalate to gestational diabetes mellitus via adverse outcome pathways using a network-based approach

Gestational diabetes mellitus (GDM) is a common pregnancy complication that is harmful to both the woman and fetus. Several epidemiological studies have found that exposure to diethylhexyl phthalate (DEHP), an endocrine disruptor ubiquitous in the environment, may be associated with GDM. This study aims to investigate the mechanism between DEHP and GDM using the adverse outcome pathway (AOP) framework, which can integrate information from different sources to elucidate the causal pathways between chemicals and adverse outcomes. We applied a network-based workflow to integrate diverse information to generate computational AOPs and accelerate the AOP development. The interactions among DEHP, genes, phenotypes, and GDM were retrieved from several publicly available databases, including the Comparative Toxicogenomics Database (CTD), Computational Toxicology (CompTox) Chemicals Dashboard, DisGeNET, MalaCards, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Based on the above interactions, a DEHP-Gene-Phenotype-GDM network consisting of 52 nodes and 227 edges was formed to support AOP construction. The filtered genes and phenotypes were assembled as molecular initiating events (MIEs) and key events (KEs) according to the upstream and downstream relationships, generating a computational AOP (cAOP) network. Based on the Organization for Economic Co-operation and Development handbook of AOPs, a cAOP was assessed and applied to determine the effects of DEHP on GDM. DEHP could increase TNF-α, downregulate the glucose uptake process, and lead to GDM. Overall, this study revealed the utility of computational methods in integrating a variety of datasets, supporting AOP development, and facilitating a better understanding of the underlying mechanism of exposure to chemicals on human health.

Cleavage Stimulation Factor Subunit 2: Function Across Cancers and Potential Target for Chemotherapeutic Drugs

The cleavage stimulation factor subunit complex is involved in the cleavage and polyadenylation of 3′-end pre-mRNAs that regulate mRNA formation and processing. However, cleavage stimulation factor subunit 2 (CSTF2) was found to play a more critical regulatory role across cancers. General cancer data sets from The Cancer Genome Atlas and Genotype-Tissue Expression project were thus downloaded for differential analysis, and the possible functions and mechanisms of CSTF2 in general cancer were analyzed using the Compartments database, cBioPortal database, Tumor Immune Single-cell Hub database, and Comparative Toxigenomics database using gene set enrichment analysis and R software. The results showed that CSTF2 could affect DNA repair and methylation in tumor cells. In addition, CSTF2 was associated with multiple tumor immune infiltrates in a wide range of cancers, and its high expression was associated with multiple immune checkpoints; therefore, it could serve as a potential target for many drug molecules. We also proved that CSTF2 promotes oral cell proliferation and migration. The high diagnostic efficacy of CSTF2 suggested that this gene may act as a new biomarker and personalized therapeutic target for a variety of tumors.

Using Network Pharmacology to Systematically Decipher the Potential Mechanisms of Jisuikang in the Treatment of Spinal Cord Injury

Objective

To identify the potential pharmacological targets of Jisuikang (JSK) for the treatment of spinal cord injury (SCI) using network pharmacology.

Methods

The bioactive compounds of JSK herbs and their corresponding potential SCI targets were obtained from three traditional Chinese medicine (TCM) databases. SCI-related therapeutic target genes were obtained from the Comparative Toxicogenomics Database and the GeneCards Database. The common target genes between the JSK compounds and SCI-related therapeutic targets were screened using GO/KEGG functional enrichment and protein-protein interaction (PPI) analyses to identify hub genes and their categories of biological function. Gene expression distribution and receiver operating characteristic curve (ROC) analyses were used to identify probable SCI-related target genes. Molecular docking was used to quantify molecular interactions between target genes and the bioactive compounds of JSK.

Results

A total of 183 JSK bioactive compounds and 197 target genes for the treatment of SCI were screened and assessed. The target genes were enriched primarily in drug metabolism and in inflammation-related biological processes. Ten genes with statistical significance were identified as therapeutic SCI-related target genes of JSK. Molecular docking experiments demonstrated that the proteins of these 10 genes docked with binding energies of less than −5 kcal/mol with the bioactive compounds in JSK.

Conclusion

This study showed that the anti-SCI effects of JSK may be mediated through numerous bioactive components, multiple gene targets, and inflammation-related pathways and provided potential novel targets for directed therapies for treating SCI. These results provide a foundation for further experimental investigations into treatment options for SCI.

Comprehensive pan-cancer analysis on CBX3 as a prognostic and immunological biomarker

Background

Increased evidence supports the relationship between chromobox protein homolog 3 (CBX3) and tumorigenesis of some cancers. However, the role of CBX3 in pan-cancers remains poorly defined. In the research, we aimed to investigate the prognostic value and the immunological functions of CBX3.

Results

We explored the potential oncogenic roles of CBX3 in mRNA and protein levels based on the diverse databases, including the expression, the correlation with prognosis, tumor microenvironment (TME), DNA methylation, protein phosphorylation and enrichment analysis across all TCGA tumors. The results show that CBX3 is overexpressed in multiple cancers, and significant correlations exist between high expression and adverse prognosis in most tumor patients. We observed an enhanced phosphorylation level in uterine corpus endometrial carcinoma, colon cancer and lung adenocarcinoma. A distinct relationship was also found between CBX3 expression and TME, including immune infiltration of tumor-infiltrating lymphocytes and cancer-associated fibroblasts, immune score or matrix score, immune checkpoints. The correlative transcription factors and miRNAs of CBX3-binding hub genes were analyzed to investigate the molecular mechanism. Moreover, alcoholism and alteration of DNA cellular biology may be involved in the functional mechanisms of CBX3.

Conclusion

The first pan-cancer study offers a relatively comprehensive cognition on the oncogenic roles of CBX3 as a prognostic and immunological marker in various malignant tumors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01179-y.

Systematic Understanding of Mechanism of Danggui Shaoyao San against Ischemic Stroke Using a Network Pharmacology Approach

Purpose

Danggui Shaoyao San (DSS) was developed to treat the ischemic stroke (IS) in patients and animal models. The purpose of this study was to explore its active compounds and demonstrate its mechanism against IS through network pharmacology, molecular docking, and animal experiment.

Methods

All the components of DSS were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using OMIM, CTD database, and TTD database. The herb-compound-target network was constructed by Cytoscape software. The target protein-protein interaction network was built using the STRING database. The core targets of DSS were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then, we achieved molecular docking between the hub proteins and the key active compounds. Finally, animal experiments were performed to verify the core targets. Triphenyltetrazolium chloride (TTC) staining was used to calculate the infarct size in mice. The protein expression was determined using the Western blot.

Results

Compound-target network mainly contained 51 compounds and 315 corresponding targets. Key targets contained MAPK1, SRC, PIK3R1, HRAS, AKT1, RHOA, RAC1, HSP90AA1, and RXRA FN1. There were 417 GO items in GO enrichment analysis (p < 0.05) and 119 signaling pathways (p < 0.05) in KEGG, mainly including negative regulation of apoptosis, steroid hormone-mediated signaling pathway, neutrophil activation, cellular response to oxidative stress, and VEGF signaling pathway. MAPK1, SRC, and PIK3R1 docked with small molecule compounds. According to the Western blot, the expression of p-MAPK 1, p-AKT, and p-SRC was regulated by DSS.

Conclusions

This study showed that DSS can treat IS through multiple targets and routes and provided new insights to explore the mechanisms of DSS against IS.

Xuanfei Baidu Decoction reduces acute lung injury by regulating infiltration of neutrophils and macrophages via PD-1/IL17A pathway

The pathogenic hyper-inflammatory response has been revealed as the major cause of the severity and death of the Corona Virus Disease 2019 (COVID-19). Xuanfei Baidu Decoction (XFBD) as one of the "three medicines and three prescriptions" for the clinically effective treatment of COVID-19 in China, shows unique advantages in the control of symptomatic transition from moderate to severe disease states. However, the roles of XFBD to against hyper-inflammatory response and its mechanism remain unclear. Here, we established acute lung injury (ALI) model induced by lipopolysaccharide (LPS), presenting a hyperinflammatory process to explore the pharmacodynamic effect and molecular mechanism of XFBD on ALI. The in vitro experiments demonstrated that XFBD inhibited the secretion of IL-6 and TNF-α and iNOS activity in LPS-stimulated RAW264.7 macrophages. In vivo, we confirmed that XFBD improved pulmonary injury via down-regulating the expression of proinflammatory cytokines such as IL-6, TNF-α and IL1-β as well as macrophages and neutrophils infiltration in LPS-induced ALI mice. Mechanically, we revealed that XFBD treated LPS-induced acute lung injury through PD-1/IL17A pathway which regulates the infiltration of neutrophils and macrophages. Additionally, one major compound from XFBD, i.e. glycyrrhizic acid, shows a high binding affinity with IL17A. In conclusion, we demonstrated the therapeutic effects of XFBD, which provides the immune foundations of XFBD and fatherly support its clinical applications.

Identification of immune subtypes of Ph-neg B-ALL with ferroptosis related genes and the potential implementation of Sorafenib

BACKGROUND

The clinical outcome of Philadelphia chromosome-negative B cell acute lymphoblastic leukemia (Ph-neg B-ALL) varies considerably from one person to another after clinical treatment due to lack of targeted therapies and leukemia's heterogeneity. Ferroptosis is a recently discovered programmed cell death strongly correlated with cancers. Nevertheless, few related studies have reported its significance in acute lymphoblastic leukemia.

METHODS

Herein, we collected clinical data of 80 Ph-neg B-ALL patients diagnosed in our center and performed RNA-seq with their initial bone marrow fluid samples. Throughout unsupervised machine learning K-means clustering with 24 ferroptosis related genes (FRGs), the clustered patients were parted into three variant risk groups and were performed with bioinformatics analysis.

RESULTS

As a result, we discovered significant heterogeneity of both immune microenvironment and genomic variance. Furthermore, the immune check point inhibitors response and potential implementation of Sorafenib in Ph-neg B-ALL was also analyzed in our cohort. Lastly, one prognostic model based on 8 FRGs was developed to evaluate the risk of Ph-neg B-ALL patients.

CONCLUSION

Jointly, our study proved the crucial role of ferroptosis in Ph-neg B-ALL and Sorafenib is likely to improve the survival of high-risk Ph-neg B-ALL patients.

Revealing the efficacy-toxicity relationship of Fuzi in treating rheumatoid arthritis by systems pharmacology

In recent decades, herbal medicines have played more and more important roles in the healthcare system in the world because of the good efficacy. However, with the increasing use of herbal medicines, the toxicity induced by herbal medicines has become a global issue. Therefore, it is needed to investigate the mechanism behind the efficacy and toxicity of herbal medicines. In this study, using Aconiti Lateralis Radix Praeparata (Fuzi) as an example, we adopted a systems pharmacology approach to investigate the mechanism of Fuzi in treating rheumatoid arthritis and in inducing cardiac toxicity and neurotoxicity. The results showed that Fuzi has 25 bioactive compounds that act holistically on 61 targets and 27 pathways to treat rheumatoid arthritis, and modulation of inflammation state is one of the main mechanisms of Fuzi. In addition, the toxicity of Fuzi is linked to 32 compounds that act on 187 targets and 4 pathways, and the targets and pathways can directly modulate the flow of Na+, Ca2+, and K+. We also found out that non-toxic compounds such as myristic acid can act on targets of toxic compounds and therefore may influence the toxicity. The results not only reveal the efficacy and toxicity mechanism of Fuzi, but also add new concept for understanding the toxicity of herbal medicines, i.e., the compounds that are not directly toxic may influence the toxicity as well.