Comparative Toxicogenomics Database Research Articles

Role of tumor necrosis factor alpha-induced protein 6 (TNFAIP6) in tumors: A pan-cancer analysis

Abstract Background There is growing evidence that the gene named tumor necrosis factor α–induced protein 6 (TNFAIP6) has an important role in various tumors. However, a systematic pan-cancer analysis of TNFAIP6 is lacking. Here we aimed to analyze the expression of TNFAIP6 across multiple cancers and verify its expression during the progression of colon cancer. Methods We performed a comprehensive bioinformatics analysis to examine the expression of TNFAIP6 across 27 tumor types. GEPIA2 was used to evaluate the effect of TNFAIP6 on clinical cancer prognosis. cBioportal was used to assess TNFAIP6 mutations. The correlation between TNFAIP6 and cancer immune infiltrates was explored using TIMER2.0. The CancerSEA database was used to perform functional analysis of TNFAIP6. Metascape was used to identify TNFAIP6-related gene enrichment pathways. Immunohistochemistry was performed to detect TNFAIP6 protein expression in the colon cancer. In addition, the Comparative Toxicogenomics Database was searched for known and possible antitumor drugs that may be associated with TNFAIP6. Results We found that, in most of the cancers included in this analysis, TNFAIP6 was highly expressed, and there is a distinct relationship between TNFAIP6 expression and cancer prognosis. TNFAIP6 expression is associated with cancer-associated fibroblasts, neutrophils, and endothelial cells. TNFAIP6 and similar genes may also be involved in the PID_VEGF_VEGFR_ pathway. Immunohistochemistry revealed an increasing trend of TNFAIP6 protein expression in normal, adenoma, and colon cancer tissues. Several known and possible antitumor drugs that may be associated with TNFAIP6 were identified in the Comparative Toxicogenomics Database. These results suggest that a number of drugs may target TNFAIP6 during cancer treatment, including cisplatin, irinotecan, resveratrol, U 0126, NSC689534, genistein, NSC668394, oxaliplatin, plerixafor, topotecan, vincristine, flutamide, doxorubicin, MRK 003, folic acid, demecolcine, tunicamycin, zoledronic acid, and schizandrin B. Conclusions TNFAIP6 may function as an oncogene in certain cancers. Furthermore, this study provides evidence that TNFAIP6 is an important factor in colon cancer progression.

Exploring the potential mechanism of Taohong Siwu decoction in the treatment of avascular necrosis of the femoral head based on network pharmacology and molecular docking.

Based on network pharmacology and molecular docking, this study seeks to investigate the mechanism of Taohong Siwu decoction (THSWD) in the treatment of avascular necrosis of the femoral head (AVNFH). The Traditional Chinese Medicine Systems Pharmacology database was used in this investigation to obtain the active ingredients and related targets for each pharmaceutical constituent in THSWD. To find disease-related targets, the terms "avascular necrosis of the femoral head," "necrosis of the femoral head," "steroid-induced necrosis of the femoral head," "osteonecrosis," and "avascular necrosis of the bone" were searched in the databases DisGeNET, GeneCards, Comparative Toxicogenomics Database, and MalaCards. Following the identification of the overlap targets of THSWD and AVNFH, enrichment analysis using gene ontology, Kyoto Encyclopedia of Genes and Genomes, Reactome, and WikiPathways was conducted. The "THSWD-drug-active compound-intersection gene-hub gene-AVNFH" network and protein-protein interaction network were built using Cytoscape 3.9.1 and string, and CytoHubba was used to screen hub genes. The binding activities of hub gene targets and key components were confirmed by molecular docking. 152 prospective therapeutic gene targets were found in the bioinformatics study of ONFH treated with THSWD, including 38 major gene targets and 10 hub gene targets. The enrichment analysis of 38 key therapeutic targets showed that the biological process of gene ontology analysis mainly involved cytokine-mediated signaling pathway, angiogenesis, cellular response to reactive oxygen species, death-inducing signaling complex. The Kyoto Encyclopedia of Genes and Genomes signaling pathway mainly involves TNF signaling pathway, IL-17 signaling pathway, and the Recactome pathway mainly involves Signaling by Interleukins, Apoptosis, and Intrinsic Pathway for Apoptosis. WikiPathways signaling pathway mainly involves TNF-related weak inducer of apoptosis signaling pathway, IL-18 signaling pathway. According to the findings of enrichment analysis, THSWD cured AVNFH by regulating angiogenesis, cellular hypoxia, inflammation, senescence, apoptosis, cytokines, and cellular proliferation through the aforementioned targets and signaling pathways. The primary component of THSWD exhibits a strong binding force with the key protein of AVNFH. This study sheds new light on the biological mechanism of THSWD in treating AVNFH by revealing the multi-component, multi-target, and multi-pathway features and molecular docking mechanism of THSWD.

A comprehensive analysis of mRNA expression profiles of Esophageal Squamous Cell Carcinoma reveals downregulation of Desmoglein 1and crucial genomic targets.

Esophageal Squamous Cell Carcinoma (ESCC) is a histological subtype of esophageal cancer that begins in the squamous cells in the esophagus. In only 19% of the ESCC-diagnosed patients, a five-year survival rate has been seen. This necessitates the identification of high-confidence biomarkers for early diagnosis, prognosis, and potential therapeutic targets for the mitigation of ESCC. We performed a meta-analysis of 10 mRNA datasets and identified consistently perturbed genes across the studies. Then, integrated with ESCC ATLAS to segregate 'core' genes to identify consequences of primary gene perturbation events leading to gene-gene interactions and dysregulated molecular signaling pathways. Further, by integrating with toxicogenomics data, inferences were drawn for gene interaction with environmental exposures, trace elements, chemical carcinogens, and drug chemicals. We also deduce the clinical outcomes of candidate genes based on survival analysis using the ESCC related dataset in The Cancer Genome Atlas. We identified 237 known and 18 novel perturbed candidate genes. Desmoglein 1 (DSG1) is one such gene that we found significantly downregulated (Fold Change =-1.89, p-value = 8.2e-06) in ESCC across six different datasets. Further, we identified 31 'core' genes (that either harbor genetic variants or are regulated by epigenetic modifications) and found regulating key biological pathways via adjoining genes in gene-gene interaction networks. Functional enrichment analysis showed dysregulated biological processes and pathways including "Extracellular matrix", "Collagen trimmer" and "HPV infection" are significantly overrepresented in our candidate genes. Based on the toxicogenomic inferences from Comparative Toxicogenomics Database we report the key genes that interacted with risk factors such as tobacco smoking, zinc, nitroso benzylmethylamine, and drug chemicals such as cisplatin, Fluorouracil, and Mitomycin in relation to ESCC. We also point to the STC2 gene that shows a high risk for mortality in ESCC patients. We identified novel perturbed genes in relation to ESCC and explored their interaction network. DSG1 is one such gene, its association with microbiota and a clinical presentation seen commonly with ESCC hints that it is a good candidate for early diagnostic marker. Besides, in this study we highlight candidate genes and their molecular connections to risk factors, biological pathways, drug chemicals, and the survival probability of ESCC patients.

CAV1 and KRT5 are potential targets for prostate cancer.

Prostate cancer is the most common malignant tumor of male urogenital system that occurs in prostate epithelium. However, relationship between CAV1 and KRT5 and prostate cancer remains unclear. The prostate cancer datasets GSE114740 and GSE200879 were downloaded from Gene Expression Omnibus generated by GPL11154 and GPL32170. De-batch processing was performed, differentially expressed genes (DEGs) were screened, and weighted gene co-expression network analysis. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis. Gene expression heat map was drawn and immune infiltration analysis was performed. Comparative toxicogenomics database analysis were performed to find the disease most related to core gene. In addition, the cell experiment was performed to verify the role of CAV1 and KRT5 by western blot. Divided into 4 groups: control, prostate cancer, prostate cancer-over expression, and prostate cancer- knock out. TargetScan screened miRNAs that regulated central DEGs; 770 DEGs were identified. According to Gene Ontology analysis, they were mainly concentrated in actin binding and G protein coupled receptor binding. In Kyoto Encyclopedia of Gene and Genome analysis, they were mainly concentrated in PI3K-Akt signal pathway, MAPK signal pathway, and ErbB signal pathway. The intersection of enrichment terms of differentially expressed genes and GOKEGG enrichment terms was mainly concentrated in ErbB signaling pathway and MAPK signaling pathway. Three important modules were generated. The protein-protein interaction network obtained 8 core genes (CAV1, BDNF, TGFB3, FGFR1, PRKCA, DLG4, SNAI2, KRT5). Heat map of gene expression showed that core genes (CAV1, TGFB3, FGFR1, SNAI2, KRT5) are highly expressed in prostate cancer tissues and low in normal tissues. Comparative toxicogenomics database analysis showed that core genes (CAV1, TGFB3, FGFR1, SNAI2, KRT5) were associated with prostate tumor, cancer, tumor metastasis, necrosis, and inflammation. CAV1 and KRT5 are up-regulated in prostate cancer. CAV1 and KRT5 are highly expressed in prostate cancer. The higher expression of CAV1 and KRT5, the worse prognosis.

Intercellular adhesion molecule 1 and selectin l play crucial roles in ulcerative colitis.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease that primarily affects the mucosal layer of the colon (large intestine). However, the relationship between Intercellular Adhesion Molecule-1 (ICAM1), SELL and UC is unclear. The UC datasets, GSE87466 and GSE36807, were downloaded from the gene expression omnibus database. The R package limma was utilized to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis was conducted. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis, and comparative toxicogenomics database analysis were performed. TargetScan was employed to screen miRNAs regulating central DEGs. Western blot (WB) was used to verify. A total of 2118 DEGs were identified in our study. Gene ontology analysis indicated their enrichment primarily in immune system processes, cellular responses to chemical stimuli, responses to organic substances, responses to external stimuli, and immune responses. Kyoto Encyclopedia of Genes and Genomes analysis revealed that the target cells were mainly enriched in chemokine signaling pathways and TNF signaling pathways. Gene set enrichment analysis enrichment analysis showed significant enrichment in chemokine signaling pathways and cell adhesion molecules. In the Metascape enrichment project, gene ontology terms included regulation of cell activation and positive regulation of immune response. Through the construction and analysis of a protein-protein interaction network, we identified 11 core genes (ICAM1, SELL, CD44, CD40, CCR7, CXCL8, CD19, CCL4, CD274, IL7R, IL1B). We found that the core genes (ICAM1, SELL) were highly expressed in UC samples and lowly expressed in normal samples, suggesting their potential regulatory roles in UC. These core genes were associated with lymphoproliferative disorders, inflammation and necrosis. WB results confirmed the high expression of ICAM1 and SELL in UC. ICAM1 and SELL are highly expressed in UC, and the higher the ICAM1 and SELL genes, the worse the prognosis.

Comparative Toxicogenomics Database: A tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease

AbstractBackgroundMost human diseases involve interactions between genetic and environmental factors. Although the environment is implicated in most chronic diseases, the etiology and mechanisms of action underlying these diseases remain unclear. It is estimated that more than 80,000 chemicals are currently used in commerce, challenging elucidation about chemical mechanisms‐of‐action and prioritization of environmental health research. Integration of diverse data is required to understand environment‐disease associations, mechanisms of chemical action, toxicity prediction and development of effective therapeutic interventions.MethodThe Comparative Toxicogenomics Database (CTD; http://ctdbase.org) was launched publicly to address an unmet need for a public data resource dedicated exclusively to advancing understanding about environment‐disease connections. CTD provides a combination of richly annotated data describing chemical‐gene‐phenotype‐disease interactions, exposure information, and novel analysis tools that enable user‐driven discoveries about environmental influences on human health.ResultsCurrently, CTD provides >2.5 million manually curated relationships for 16,800 chemicals; 52,000 genes/proteins; 5,500 phenotypes; and 7,200 diseases. The value of CTD has been specifically leveraged for a range of chronic and neurological diseases, including Alzheimer’s disease.ConclusionThere is growing evidence of environmental influences on the etiology of a range of neuropsychiatric syndromes. This presentation will provide an overview of CTD content and functionality and how it can be used to explore environmental influences on the etiology and underlying mechanisms of Alzheimer’s disease and other disorders.

High expression of NADH Ubiquinone Oxidoreductase Subunit B11 induces catheter-associated venous thrombosis on continuous blood purification.

Venous thromboembolism (VTE) is a common vascular disease of venous return disorders, including deep venous thrombosis and pulmonary embolism (PE), with high morbidity and high mortality. However, the relationship between oxidative phosphorylation and NDUFB11 and venous thromboembolism is still unclear. The venous thromboembolism datasets GSE48000 and GSE19151 were downloaded, and the differentially expressed Genes (DEGs) were screened. The protein-protein interaction (PPI) network was constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for functional enrichment analysis. The comparative toxicogenomics database (CTD) was used to identify the diseases most associated with the core genes. TargetScan was used to screen miRNA regulating central DEGs. Western blotting (WB) experiment and real-time quantitative PCR (RT-qPCR) experiment were performed. A total of 500 DEGs were identified. GO analysis showed that the DEGs were mainly enriched in ATP synthesis coupled electron transport, respiratory electron transport chain, cytoplasm, enzyme binding, nonalcoholic fatty liver disease, oxidative phosphorylation, and Alzheimer disease. Enrichment items were similar to GO and KEGG enrichment items of DEGs. The result of CTD showed that 12 genes (RPS24, FAU, RPLP0, RPS15A, RPS29, RPL9, RPL31, RPL27, NDUFB11, RPL34, COX7B, RPS27L) were associated with chemical and drug-induced liver injury, inflammation, kidney disease, and congenital pure red cell aplasia. WB and RT-qPCR results showed that the expression levels of 12 genes in venous thromboembolism were higher than normal whole blood tissue samples. NDUFB11 is highly expressed in catheter-related venous thromboembolism during continuous blood purification, which may lead to the formation of venous thrombosis through oxidative phosphorylation pathway.

Hub biomarkers in ultrasound-guided bladder cancer and osteosarcoma: Myosin light chain kinase and caldesmon.

Bladder cancer and osteosarcoma are 2 types of cancers that originate from epithelial tissues inside the bladder and bone or muscle tissues. Ultrasound-guided biopsies provide crucial support for the diagnosis and treatment of bladder cancer and osteosarcoma. However, the relationship between myosin light chain kinase (MYLK) and caldesmon (CALD1) and bladder cancer and osteosarcoma remains unclear. The bladder cancer datasets GSE65635 and GSE100926, the osteosarcoma dataset GSE39058, were obtained from gene expression omnibus. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis. Gene expression heat map was drawn and immune infiltration analysis was performed. The comparative toxicogenomics database analysis were performed to find disease most related to core gene. Western blotting experiments were performed. TargetScan screened miRNAs that regulated central DEGs. We obtained 54 DEGs. Functional enrichment analysis revealed significant enrichment in terms of cellular differentiation, cartilage development, skeletal development, muscle actin cytoskeleton, actin filament, Rho GTPase binding, DNA binding, fibroblast binding, MAPK signaling pathway, apoptosis, and cancer pathways. Gene set enrichment analysis indicated that DEGs were primarily enriched in terms of skeletal development, cartilage development, muscle actin cytoskeleton, MAPK signaling pathway, and apoptosis. The immune infiltration analysis showed that when T cells regulatory were highly expressed, Eosinophils exhibited a similar high expression, suggesting a strong positive correlation between T cells regulatory and Eosinophils, which might influence the disease progression in osteosarcoma. We identified 6 core genes (SRF, CTSK, MYLK, VCAN, MEF2C, CALD1). MYLK and CALD1 were significantly correlated with survival rate and exhibited lower expression in bladder cancer and osteosarcoma samples compared to normal samples. Comparative toxicogenomics database analysis results indicated associations of core genes with osteosarcoma, bladder tumors, bladder diseases, tumors, inflammation, and necrosis. The results of Western blotting showed that the expression levels of MYLK and CALD1 in bladder cancer and osteosarcoma were lower than those in normal tissues. MYLK and CALD1 likely play a role in regulating muscle contraction and smooth muscle function in bladder cancer and osteosarcoma. The lower expression of MYLK and CALD1 is associated with poorer prognosis.

Investigation of the shared gene signatures and molecular mechanisms between obstructive sleep apnea syndrome and asthma

BackgroundObstructive sleep apnea syndrome (OSAS) is highly related with asthma from the epidemiology to pathogenesis, while the underlying mechanism is still unclear. Herein, we aimed to reveal the shared gene signatures and molecular mechanisms underlying the coexistence of OSAS and asthma and verified relating pathway in mouse models. We downloaded GSE75097 of OSAS and GSE165934 of asthma from GEO database and performed differential expression analysis and functional enrichment analysis to screen differentially expressed genes (DEGs) and potential pathogenic pathway. PPI network was constructed with the STRING database. Hub genes were identified with cytoHubba and immune infiltration analysis was performed with cibersort for further verification. Potential drugs were screened with Comparative Toxicogenomics Database and miRNA-gene network was constructed. Besides, to test the pulmonary function and inflammatory cytokine, mouse models with OSAS and asthma were constructed, followed by validating the involvement of NOD1/NOD2-RIPK2-NF-κB-MCPIP-1 pathway in associated diseases. ResultsIn total, 104 DEGs were identified, in which PLAUR, RIPK2, PELI1, ZC3H12A, and TNFAIP8 are the hub genes, while NOD-like receptor signaling pathway and apoptosis signaling pathway were the potential influential pathways. Increased γδT cells and neutrophils were detected in asthma patients through immune infiltration analysis. Significant difference was detected among genders in OSAS, and acetaminophen is a potential drug in the comorbidity by screening the drugs in the Comparative Toxicogenomics Database. Mice with OSAS and asthma presented with worse pulmonary function and higher levels of inflammatory cytokines. The relative proteins, including NOD1, NOD2, RIPK2, NF-κB, and MCPIP-1, were up-regulated in mice with the OSAS and asthma. ConclusionsThis research firstly elucidates NOD1/NOD2-RIPK2-NF-κB-MCPIP-1 pathway as the shared pathway in the development of OSAS and asthma through bioinformatics and experimental methods. There is an interactive deterioration model between OSAS and asthma. This study may provide some potential biomarkers in the future research of the underlying pathogenesis and treatment of comorbidity of OSAS and asthma.

MYLK and CALD1 as molecular targets in bladder cancer.

Bladder cancer (BC) is a malignant tumor that occurs in bladder mucosa. However, relationship between myosin light chain kinase (MYLK) and CALD1 and BC remains unclear. The BC datasets GSE65635 and GSE100926 were downloaded from gene expression omnibus by GPL14951 and GPL14550. Multiple datasets were merged and batched. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome analysis, gene set enrichment analysis, immune infiltration analysis, survival analysis and Comparative Toxicogenomics Database were performed. TargetScan screened miRNAs that regulated central DEGs. 1026 DEGs were identified. According to GO analysis, DEGs were mainly enriched in cancer pathway, cGMP-PKG signaling pathway, Apelin signaling pathway and proteoglycans in cancer. The enrichment items are similar to GO and Kyoto Encyclopedia of Gene and Genome enrichment projects for DEGs, which were mainly enriched in cancer pathways and leukocyte trans-endothelial cell migration. Among enrichment projects of metascape, GO has regulation of the enzyme-linked receptor protein signaling pathway and silk-based process, as well as an enrichment network stained by enrichment terms and P values. Nine core genes (ACTA2, MYLK, MYH11, MYL9, ACTG2, TPM1, TPM2, TAGLN and CALD1) were obtained, which were highly expressed in tumor tissue samples and lowly expressed in normal tissue samples. Nine genes were associated with necrosis, inflammation, tumor, edema, and ureteral obstruction. MYLK and CALD1 are highly expressed in the BC. The higher expression of MYLK and CALD1, the worse prognosis.

Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

BackgroundDelirium is a prevalent neuropsychiatric medical phenomenon that causes serious emergency outcomes, including mortality and morbidity. It also increases the suffering and the economic burden for families and carers. Unfortunately, the pathophysiology of delirium is still unknown, which is a major obstacle to therapeutic development. The modern network-based system biology and multi-omics analysis approach has been widely used to recover the key drug target biomolecules and signaling pathways associated with disease pathophysiology. This study aimed to identify the major drug target hub-proteins associated with delirium, their regulatory molecules with functional pathways, and repurposable drug candidates for delirium treatment.MethodsWe used a comprehensive proteomic seed dataset derived from a systematic literature review and the Comparative Toxicogenomics Database (CTD). An integrated multi-omics network-based bioinformatics approach was utilized in this study. The STRING database was used to construct the protein-protein interaction (PPI) network. The gene set enrichment and signaling pathways analysis, the regulatory transcription factors and microRNAs were conducted using delirium-associated genes. Finally, hub-proteins associated repurposable drugs were retrieved from CMap database.ResultsWe have distinguished 11 drug targeted hub-proteins (MAPK1, MAPK3, TP53, JUN, STAT3, SRC, RELA, AKT1, MAPK14, HSP90AA1 and DLG4), 5 transcription factors (FOXC1, GATA2, YY1, TFAP2A and SREBF1) and 6 microRNA (miR-375, miR-17-5, miR-17-5p, miR-106a-5p, miR-125b-5p, and miR-125a-5p) associated with delirium. The functional enrichment and pathway analysis revealed the cytokines, inflammation, postoperative pain, oxidative stress-associated pathways, developmental biology, shigellosis and cellular senescence which are closely connected with delirium development and the hallmarks of aging. The hub-proteins associated computationally identified repurposable drugs were retrieved from database. The predicted drug molecules including aspirin, irbesartan, ephedrine-(racemic), nedocromil, and guanidine were characterized as anti-inflammatory, stimulating the central nervous system, neuroprotective medication based on the existing literatures. The drug molecules may play an important role for therapeutic development against delirium if they are investigated more extensively through clinical trials and various wet lab experiments.ConclusionThis study could possibly help future research on investigating the delirium-associated therapeutic target biomarker hub-proteins and repurposed drug compounds. These results will also aid understanding of the molecular mechanisms that underlie the pathophysiology of delirium onset and molecular function.

Joint effect of RRP9 and DDX21 on development of colorectal cancer and keloid.

Colorectal cancer (CRC) is a common malignancy in the gastrointestinal tract. Keloid refers to abnormal scar tissue that forms on the skin or mucous membrane. The relationship between RRP9 and DDX21 and the two diseases is unclear. Download the colorectal cancer dataset GSE134834, GSE206800, GSE209892 and keloid dataset GSE44270 from the GEO database. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. The construction and analysis of protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis (GSEA). Gene expression heat map was drawn. The comparative toxicogenomics database (CTD) analysis was performed to find diseases most related to core genes. TargetScan screened miRNAs that regulated central DEGs. We conducted experimental validation using Western blotting and Polymerase Chain Reaction (PCR). In the colorectal cancer dataset and the scar tissue dataset, we identified 1380 DEGs and 1000 DEGs, respectively. The enrichment pattern for scar tissue was similar to that of colorectal cancer. We identified two core genes, RRP9 and DDX21. CTD analysis indicated that RRP9 and DDX21 are associated with proliferation, scar tissue, colorectal tumors, scleroderma, and inflammation. We found that the core genes (RRP9 and DDX21) were highly expressed in colorectal cancer and scar tissue samples, while their expression was lower in normal samples. This was further validated through Western blotting (WB) and Polymerase Chain Reaction (PCR). The higher the expression of RRP9 and DDX21 in colorectal cancer and keloid, the worse the prognosis.

NDUFB11 and NDUFS3 regulate arterial atherosclerosis and venous thrombosis: Potential markers of atherosclerosis and venous thrombosis.

Atherosclerosis is a chronic disease that thickens the blood vessel walls and narrows the lumen. Venous thrombosis is a blood clot that forms in the body's deep veins or pulmonary arteries. However, the relationship between NDUFB11 and NDUFS3 and atherosclerosis and venous thrombosis is unclear. We employed data files that combined atherosclerosis and chronic stress groups. Subsequently, we conducted differential gene expression analysis (DEGs) and performed weighted gene co-expression network analysis (WGCNA). We constructed and analyzed a protein-protein interaction (PPI) network. Further analyses included functional enrichment analysis, gene set enrichment analysis (GSEA), gene expression heatmaps, immune infiltration analysis, and mRNA analysis. By comparing our findings with the Comparative Toxicogenomics Database (CTD), we identified the most relevant diseases associated with the core genes. Additionally, we utilized TargetScan to screen for miRNAs regulating the central DEGs. To validate our results, we conducted Western Blot experiments at the cellular level. A total of 1747 DEGs were co-identified. According to the Gene Ontology (GO) analysis of differentially expressed genes, they were primarily enriched in mitochondrial gene expression, mitochondrial envelope, organelle membrane, and mitochondrial inner membrane categories. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the target cells were mainly enriched in metabolic pathways, ribosomes, and histidine metabolism. The intersection of enriched terms from both GO and KEGG analyses showed significant enrichment in mitochondrial gene expression, mitochondrial envelope, organelle inner membrane, ribosomal structural constituents, histidine metabolism, and oxidative phosphorylation. Eight core genes were identified, including NDUFS5, UQCRQ, COX6C, COX7B, ATP5ME, NDUFS3, NDUFA3, and NDUFB11. The gene expression heatmap demonstrated that core genes (NDUFB11 and NDUFS3) were downregulated in atherosclerosis with venous thrombosis samples and upregulated in normal samples. CTD analysis revealed that the core genes NDUFB11 and NDUFS3 were associated with pain, arterial diseases, atherosclerosis, arteritis, venous thrombosis formation, and venous thromboembolism. We added Western Blot basic cell experiment for verification. NDUFB11 and NDUFS3 are downregulated in atherosclerosis and venous thrombosis, associated with poorer prognosis, and may serve as potential biomarkers for both diseases.

Screening and identification of hub genes of scar physique via weighted gene co-expression network analysis.

Scar physique refers to the abnormal repair of skin injury in some people, which may easily lead to keloid or hypertrophic scar. However, the mechanism of scar physique is still unclear. GSE108110 was obtained from the gene expression omnibus database. Differently expression genes (DEGs) between normal skin tissue of non-scar physique individuals and normal skin tissue of scar physique individuals were screened by R package "limma". Weighted gene co-expression network analysis was performed to find highly relevant gene modules. Functional annotation of DEGs was made. Protein-protein interaction network was constructed, and the identification and analysis of hub DEGs were performed, including identification of hub DEGs associated with scar diseases, MiRNA of hub DEGs prediction, and functional annotation of miRNA. A total of 1389 up-regulate DEGs and 1672 down-regulate DEGs were screened. weighted gene co-expression network analysis analysis showed that the dendrogram and heatmap were used to quantify module similarity by correlation. The associations between clinic traits and the modules were identified based on the correlation between module and scar physique. Eight common hub genes were obtained. The comparative toxicogenomics database shows common hub genes associated with scar tissue. Gene ontology and Kyoto encyclopedia of genes and genomes analysis were significantly enriched in "fibroblast growth factor receptor signaling pathway", "epidermal growth factor receptor signaling pathway", "G1/S transition of mitotic cell cycle", protein polyubiquitination", and others. The 8 hub genes might be involved in the development of scarring and used as early diagnosis, prevention and treatment of scar physique.

Fgf2 and Ptpn11 play a role in cerebral injury caused by sevoflurane anesthesia.

Sevoflurane is a new inhaled anesthetic, which has better physical properties than the existing inhalational anesthetics, rapid induction, less tissue uptake, and faster recovery. Sevoflurane can directly dilators cerebral blood vessels and increase cerebral blood flow, but it also reduces cerebral oxygen metabolism rate, thereby reducing cerebral blood flow. However, the role of Fgf2 and Ptpn11 in cerebral injury caused by sevoflurane anesthesia remains unclear. The sevoflurane anesthesia brain tissue datasets GSE139220 and GSE141242 were downloaded from gene expression omnibus (GEO). Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Construction and analysis of protein-protein interaction (PPI) Network. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG), comparative toxicogenomics database (CTD) were performed. A heat map of gene expression was drawn. TargetScan was used to screen miRNAs regulating DEGs. 500 DEGs were identified. According to GO, in Biological Process analysis, they were mainly enriched in response to hypoxia, blood vessel development, inner ear development, neural tube closure, and aging. In Cellular Component (CC), they were mainly enriched in plasma membrane, integral component of membrane, and basal lamina. In Molecular Function (MF), they were mainly associated with protein binding, Wnt-activated receptor activity, and organic anion transmembrane transporter activity. In the KEGG analysis, they were mainly enriched in proteoglycans in cancer, pathways in cancer, transcriptional misregulation in cancer, basal cell carcinoma, thyroid hormone signaling pathway. In the Metascape enrichment analysis, the GO enrichment items revealed upregulated regulation of vascular endothelial cell proliferation, platelet-derived growth factor receptor signaling pathway, inner ear development, and response to hypoxia. A total of 20 modules were generated. Gene Expression Heatmap showed that the core genes (Fgf2, Pdgfra, Ptpn11, Slc2a1) were highly expressed in sevoflurane anesthesia brain tissue samples. CTD Analysis showed that the 4 core genes (Fgf2, Pdgfra, Ptpn11, Slc2a1) were associated with neurodegenerative diseases, brain injuries, memory disorders, cognitive disorders, neurotoxicity, drug-induced abnormalities, neurological disorders, developmental disorders, and intellectual disabilities. Fgf2 and Ptpn11 are highly expressed in brain tissue after sevoflurane anesthesia, higher the expression level of Fgf2 and Ptpn11, worse the prognosis.

CALM3 affects the prognosis of leukemia and hemorrhoids.

Leukemia is an abnormal proliferation of white blood cells in the bone marrow, resulting in a large accumulation of abnormal leukemia cells in the blood and bone marrow. Hemorrhoids are dilated and swollen veins in the rectum or anal area. However, the relationship between CALM3 and leukemia and hemorrhoids remains unclear. The hemorrhoids dataset GSE154650 and leukemia dataset GSE26294 were downloaded from GEO databases generated by GPL20301 and GPL571.The R package limma was used to screen differentially expressed genes (DEDs). Weighted gene co-expression network analysis (WGCNA) was performed. The construction and analysis of protein-protein interaction (PPI) network, functional enrichment analysis, Gene Set Enrichment Analysis (GSEA) and comparative toxicogenomics database (CTD) analysis were performed. TargetScan was used to screen miRNAs regulating central DEGs. It was verified by western blot basic cell assay. A total of 125 DEGs were co-identified. According to the GO analysis, they are mainly enriched in small molecule catabolic processes, skin development, and chemokine receptor binding. The KEGG analysis results show that the target cells are mainly enriched in the interaction of cytokines and cytokine receptors, as well as butyric acid metabolism. The GSEA analysis results indicate enrichment in small molecule catabolic processes, skin development, and chemokine receptor binding. Six core genes (CALM3, ACE2, PPARGC1A, XCR1, CFTR, PRKCA) were identified. We found that the core gene CALM3 is highly expressed in hemorrhoid samples, low in leukemia samples, and has low expression in normal samples, which may play a regulatory role in hemorrhoids and leukemia. Immunoinfiltration results showed a higher proportion of T_cells_CD4_memory_resting and a correlation with T_cells_CD8. WB experiment verified the result. CALM3 expression is low in leukemia, and the lower the expression is, the worse the prognosis is. CALM3 is highly expressed in hemorrhoids, and the higher the expression, the worse the prognosis.

Microbe-Disease Association Prediction Using RGCN Through Microbe-Drug-Disease Network.

Accumulating evidence has shown that microbes play significant roles in human health and diseases. Therefore, identifying microbe-disease associations is conducive to disease prevention. In this article, a predictive method called TNRGCN is designed for microbe-disease associations based on Microbe-Drug-Disease Network and Relation Graph Convolutional Network (RGCN). First, considering that indirect links between microbes and diseases will be increased by introducing drug related associations, we construct a Microbe-Drug-Disease tripartite network through data processing from four databases including Human Microbe-Disease Association Database (HMDAD), Disbiome Database, Microbe-Drug Association Database (MDAD) and Comparative Toxicoge-nomics Database (CTD). Second, we construct similarity networks for microbes, diseases and drugs via microbe function similarity, disease semantic similarity and Gaussian interaction profile kernel similarity, respectively. Based on the similarity networks, Principal Component Analysis (PCA) is utilized to extract main features of nodes. These features will be input into the RGCN as initial features. Finally, based on the tripartite network and initial features, we design two-layer RGCN to predict microbe-disease associations. Experimental results indicate that TNRGCN achieves best performance in cross validation compared with other methods. Meanwhile, case studies for Type 2 diabetes (T2D), Bipolar disorder and Autism demonstrate the favorable effectiveness of TNRGCN in association prediction.

Roles of DSCC1 and GINS1 in gastric cancer.

Gastric carcinoma is a common malignant tumor originating from gastric mucosal epithelium. However, role of DS-cell cycle-dependent protein 1 (DSCC1) and GINS1 in gastric carcinoma remains unclear. The gastric carcinoma datasets GSE79973 and GSE118916 were downloaded from gene expression omnibus. Multiple datasets were merged and batched. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. Functional enrichment analysis, gene set enrichment analysis and immune infiltration analysis were performed. Construction and analysis of protein-protein interaction Network. Survival analysis and comparative toxicogenomics database were performed. A heat map of gene expression was drawn. Target Scan screen miRNAs regulating DEGs. Two thousand forty-four DEGs were identified. According to gene ontology analysis, in biological process, they were mainly enriched in cell migration, transforming growth factor β receptor signaling pathway, angiogenesis, and steroid metabolism process. In cellular component, they were mainly enriched in extracellular vesicles, basement membrane, endoplasmic reticulum lumen, and extracellular space. In molecular function, they focused on extracellular matrix structural components, protein binding, platelet-derived growth factor binding, and catalytic activity. In Kyoto encyclopedia of genes and genomes, they were mainly enriched in protein digestion and absorption, metabolic pathways, fatty acid degradation, Glycerophospholipid metabolism, ether lipid metabolism. Gene set enrichment analysis showed that DEGs were mainly enriched in transforming growth factor β receptor signaling pathway, steroid metabolism process, basement membrane, endoplasmic reticulum lumen, structural components of extracellular matrix, platelet-derived growth factor binding, Glycerophospholipid metabolism, ether lipid metabolism. The results of immune infiltration analysis showed that expression of T cell CD4 memory resting was lower in the samples of gastric cancer. The core genes (TRIP13, CHEK1, DSCC1, GINS1) are protective factors, their expression shows a downward trend with increase of risk score. Comparative toxicogenomics database analysis showed that TRIP13, CHEK1, DSCC1, GINS1 were related to gastric tumors, gastric diseases, tumors, inflammation, and necrosis. DSCC1 and GINS1 are highly expressed in gastric cancer. Higher expression levels of DSCC1 and GINS1, worse the prognosis.

Exploring the action mechanism of Jinxin oral liquid on asthma by network pharmacology, molecular docking, and microRNA recognition.

Using network pharmacology, molecular docking, and microRNA recognition, we have elucidated the mechanisms underlying the treatment of asthma by Jinxin oral liquid (JXOL). We began by identifying and normalizing the active compounds in JXOL through searches in the traditional Chinese medicine systems pharmacology database, SwissADME database, encyclopedia of traditional Chinese medicine database, HERB database, and PubChem. Subsequently, we gathered and standardized the targets of these active compounds from sources including the encyclopedia of traditional Chinese medicine database, similarity ensemble approach dataset, UniProt, and other databases. Disease targets were extracted from GeneCards, PharmGKB, OMIM, comparative toxicogenomics database, and DisGeNET. The intersection of targets between JXOL and asthma was determined using a Venn diagram. We visualized a Formula-Herb-Compound-Target-Disease network and a protein-protein interaction network using Cytoscape 3.9.0. Molecular docking studies were performed using Schrodinger software. To identify pathways related to asthma, we conducted gene ontology functional analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis using Metascape. MicroRNAs regulating the hub genes were obtained from the miRTarBase database, and a network linking these targets and miRNAs was constructed. Finally, we found 88 bioactive components in JXOL and 218 common targets with asthma. Molecular docking showed JXOL key compounds strongly bind to HUB targets. According to gene ontology biological process analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis, the PI3K-Akt signaling pathway, the MAPK signaling pathway, or the cAMP signaling pathway play a key role in treating of asthma by JXOL. The HUB target-miRNA network showed that 6 miRNAs were recognized. In our study, we have revealed for the first time the unique components, multiple targets, and diverse pathways in JXOL that underlie its mechanism of action in treating asthma through miRNAs.

The role of CD14 and CSF1R in osteoarthritis and gastritis.

Osteoarthritis (OA) is a non-inflammatory degenerative joint disease that mainly involves articular cartilage damage and involves the whole joint tissue. Gastritis is a common stomach disorder, typically referring to inflammation or lesions of the gastric mucosa. However, the relationship between CD14 and colony stimulating factor-1 receptor (CSF1R) and these 2 diseases is not yet clear. OA datasets GSE46750, GSE82107 and gastritis datasets GSE54043 profiles were downloaded from gene expression omnibus databases generated by GPL10558 and GPL570.The R package limma was used to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. The construction and analysis of protein-protein interaction network, functional enrichment analysis, gene set enrichment analysis and comparative toxicogenomics database analysis were performed. TargetScan was used to screen miRNAs regulating central DEGs. A total of 568 DEGs were identified. According to the gene ontology (GO) and biological processes analysis, they were mainly enriched in ATP metabolism negative regulation, toll-like receptor TLR1:TLR2 signaling pathway, and intracellular transport. The enrichment terms for OA and gastritis were similar to the GO and Kyoto encyclopedia of gene and genome enrichment terms of DEGs, mainly enriched in ATP metabolism negative regulation, secretion granules, transmembrane receptor protein kinase activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, MAPK signaling pathway, and TGF-β signaling pathway. In the Metascape enrichment projects, GO enrichment projects showed functions related to cell-cell receptor interaction, cell secretion, and growth. Two core genes were identified through the construction and analysis of the protein-protein interaction network. The core genes (CD14 and CSF1R) exhibited high expression in OA and gastritis samples and low expression in normal samples. Comparative toxicogenomics database analysis revealed associations between core genes (CD14 and CSF1R) and diseases such as OA, osteoporosis, gastritis, juvenile arthritis, diarrhea, and inflammation. CD14 and CSF1R are highly expressed in OA and gastritis, making them potential therapeutic targets for both diseases.