Identification of differentially expressed genes, associated functional terms pathways, and candidate diagnostic biomarkers in inflammatory bowel diseases by bioinformatics analysis

Exploring shared mechanisms between ulcerative colitis and psoriasis and predicting therapeutic natural compounds through bioinformatics and molecular docking

Introduction

Previous studies have suggested a potential correlation between psoriasis (PS) and ulcerative colitis (UC). However, studies exploring the shared mechanisms of both diseases remain limited. Current treatments primarily involve using immunosuppressive drugs, which can lead to potential side effects and drug resistance. Traditional Chinese medicine has demonstrated favorable efficacy in treating UC and PS with fewer side effects. This study aims to elucidate the shared biological mechanisms underlying UC and PS and to predict natural compounds effective for treating both disorders.

Method

We collected and validated differentially expressed genes associated with UC and PS from the Gene Expression Omnibus database. A protein-protein interaction network was constructed using the STRING database, aiding in identifying core targets. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were utilized to analyze the functions and genomic enrichment of the identified core targets. The CIBERSORT method was employed to assess the correlation of core targets with immune cells. Compounds with potential therapeutic values were selected from the Coremine and TCMSP databases, and their therapeutic efficacy was predicted via molecular docking.

Results

In UC and PS, 20 common core targets were identified, with matrix metalloproteinase 9 (MMP9), matrix metalloproteinase 1 (MMP1), cluster of differentiation 274 (CD274), C-X-C motif chemokine ligand 10 (CXCL10), and topoisomerase II alpha (TOP2A) emerging as the most relevant targets shared between both conditions. Elevated levels of macrophages and dendritic cells were observed in UC and PS, with CXCL10 exhibiting the closest association with macrophages. UC and PS shared common signaling pathways, including IL-17, TNF, and chemokine signaling pathways, among others. Molecular docking revealed that quercetin, baicalen, irisolidone, rutaecarpine, epigallocatechin-3-gallate, and others held potential as natural compounds for treating both disorders.

Conclusion

MMP9, MMP1, and CXCL10, central mediators in the inflammatory pathways of UC and PS, establish a shared mechanism by triggering cytokine and chemokine activation, leading to tissue damage and positioning them as promising therapeutic targets for both conditions. Compounds such as quercetin, luteolin, irisolidone, rutaecarpine, and so on may be key drugs for treating both conditions. These findings suggest the potential advancement of therapeutic strategies and the enhancement of patient care by exploring shared mechanisms and predicting promising natural compounds for treating UC and PS.

UNVEILING THERAPEUTIC TARGETS THROUGH PATHWAY ANALYSIS AND IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN ULCERATIVE COLITIS

Objective: This study utilizes integrated bioinformatics to investigate Differentially Expressed Genes (DEGs) and pathways related to ulcerative colitis (UC). Material and Method: Differentially Expressed Genes were identified from UC patients' colonic mucosal samples and controls using GSE13367 and GSE134025 datasets. Differentially Expressed Genes selection utilized GEO2R and Venn diagrams, followed by functional annotation, pathway analysis, PPI determination via the STRING database, and GO/KEGG enrichment analysis using Metascape. Result and Discussion: Analysis unveiled 197 DEGs, with 76 up-regulated and 121 down-regulated genes. Up-regulated genes were enriched in humoral immune response, peptidoglycan binding, and NADPH oxidase complex, while down-regulated genes were linked to inorganic anion transport, transmitter-gated ion channel activity, and integral plasma membrane components. In the PPI network, up-regulated DEGs formed a dense network (75 nodes, 190 edges), indicating significant interactions, whereas down-regulated DEGs formed a less dense network (114 nodes, 63 edges). Five hub genes (CXCR4, CXCL13, CXCL1, MMP3) were identified among the 197 DEGs. These findings provide new insights into UC's causes and offer promise for more effective therapeutic approaches.

Identification of hub genes and key modules in laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is the prominent cancer in head and neck, which greatly affects life quality of patients. The pathogenesis of LSCC is not clear. Presently, the LSCC treatments include chemotherapy, surgery and radiotherapy; however, these methods have poor efficacy in patients with recurrent and persistent cancer. Therefore, the study identified the hub genes accompanied with LSCC, which may be a potential therapeutic target in the future.

Methods

We extracted whole transcriptome high-throughput sequencing (HTS) LSCC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and calculate differentially expressed genes (DEGs) between LSCC and normal samples using statistical software RStudio. Through weighted gene co-expression network analysis (WGCNA), enrichment examination of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) functions, and examination of protein-protein interaction (PPI) network, we obtained network hub genes and validated the hub genes prognostic value and expression levels of protein.

Results

Through analysis of differential gene expression, from the GEO and TCGA databases 2,139 and 2,774 DEGs were obtained, respectively, 13 and 15 modules were screened from TCGA-LSCC and GSE127165 datasets by WGCNA, respectively. The most significant positive and negative correlation modules in the WGCNA and DEG lists were overlapped, and overall 36 co-expressed overlapping genes were retrieved. Through enrichment analysis of GO and KEGG, it was found that the gene functions were highly concentrated in cell junction assembly, basement membrane, extracellular matrix (ECM) structural constituent etc., and the pathways were mainly concentrated in ECM receptor interaction, focal adhesion, small cell lung cancer, and toxoplasmosis. Through analysis of PPI network analysis, 10 network hub genes (SNAI2, ITGA6, LAMB3, LAMC2, CAV1, COL7A1, GJA1, EHF, OAT, and GPT) were obtained. Finally, survival analysis and protein expression validation of these genes confirmed that low OAT expression and high CAV1 expression remarkably influenced the survival of patient's prognosis with LSCC.

Conclusions

We recognized the hub genes and key modules nearly associated to LSCC and these genes were validated by survival analysis and the database of Human Protein Atlas (HPA), which is of high importance for unveiling the pathogenesis of LSCC and probing for new precise biological marker and potential therapeutic targets.

Alfalfa xenomiR-162 targets G protein subunit gamma 11 to regulate milk protein synthesis in bovine mammary epithelial cells

OBJECTIVE

It was shown that microRNAs (miRNAs) play an important role in milk protein synthesis. However, the post-transcriptional regulation of casein expression by exogenous miRNA (xeno-miRNAs) in ruminants remains unclear. This study explores the regulatory roles of alfalfa xeno-miR162 on casein synthesis in bovine mammary epithelial cells (bMECs).

METHODS

The effects of alfalfa xenomiR-162 and G protein subunit gamma 11 (GNG11) on proliferation and milk protein metabolism of bMECs were detected by 5-Ethynyl-2'-Deoxyuridine (EdU) staining, flow cytometry, cell counting kit-8 (CCK-8), enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blot. Dual-luciferase reporter assay was used to verify the targeting relationship between GNG11 and xenomiR-162.

RESULTS

Results showed that over-expression of xenomiR-162 inhibited cell proliferation but promoted apoptosis, which also up-regulated the expression of several casein coding genes, including CSN1S1, CSN1S2, and CSN3, while decreasing the expression of CSN2. Furthermore, the targeting relationship between GNG11 and xenomiR-162 was determined, and it was confirmed that GNG11 silencing also inhibited cell proliferation but promoted apoptosis and reduced the expression of casein coding genes and genes related to the mammalian target of rapamycin (mTOR) pathway.

CONCLUSION

Alfalfa xenomiR-162 appears to regulate bMECs proliferation and milk protein synthesis via GNG11 in the mTOR pathway, suggesting that this xeno-miRNA could be harnessed to modulate CSN3 expression in dairy cows, and increase κ-casein contents in milk.

Differential Gene Expression Profiles Involved in the Inflammations Due to COVID-19 and Inflammatory Bowel Diseases and the Investigation of Predictive Biomarkers

Gastrointestinal manifestations in COVID-19 were attributed to 74-86% of the hospitalised patients due to severe or prolonged pathogenesis. Though it is a respiratory disease, the impact it elicits on the gastrointestinal tract and brain are intense. Inflammatory bowel disease including Crohn's disease and ulcerative colitis are idiopathic inflammatory disorders of the gastrointestinal tract. The intrinsic mechanisms involved in gut inflammations due to a respiratory viral disease can be deciphered when the gene expression profiles of COVID-19 and IBD are compared. The current study utilises an integrated bioinformatics approach to unravel them. The publicly available gene expression profiles of colon transcriptomes infected with COVID-19, Crohn's disease and Ulcerative colitis were retrieved, integrated and analysed for the identification of differentially expressed genes. The inter-relational analysis along with gene annotation and pathway enrichment detailed the functional and metabolic pathways of the genes during normal and diseased conditions. The protein-protein interactions deduced from the STRING database and the identified hub genes predicted potential biomarker candidates for COVID-19, Crohn's disease and ulcerative colitis. The inflammatory response pathways were upregulated and enrichment of chemokine signalling, altered lipid metabolism, coagulation and complement cascades were seen in all three conditions along with impaired transport mechanisms. CXCL11, MMP10, and CFB are predicted to be overexpressed biomarkers, whilst GUCA2A, SLC13A2, CEACAM, and IGSF9 as downregulated novel biomarker candidates for colon inflammations. The three miRNAs hsa-miR-16-5p, hsa-miR-21-5p, and hsa-miR-27b-5p exhibited significant interactions with the upregulated hub genes and four long non-coding RNAs NEAT1, KCNQ1OT1, and LINC00852 capable of regulating miRNA were also predicted. This study offers significant information on the underlying molecular mechanisms of inflammatory bowel disease with identification of potential biomarkers.

Role of Nox4 in Mitigating Inflammation and Fibrosis in Dextran Sulfate Sodium-Induced Colitis

BACKGROUND & AIMS

Fibrosis development in ulcerative colitis is associated directly with the severity of mucosal inflammation, which increases the risk of colorectal cancer. The transforming growth factor-β (TGF-β) signaling pathway is an important source of tissue fibrogenesis, which is stimulated directly by reactive oxygen species produced from nicotinamide adenine dinucleotide phosphate oxidases (NOX). Among members of the NOX family, NOX4 expression is up-regulated in patients with fibrostenotic Crohn's disease (CD) and in dextran sulfate sodium (DSS)-induced murine colitis. The aim of this study was to determine whether NOX4 plays a role in fibrogenesis during inflammation in the colon using a mouse model.

METHODS

Acute and recovery models of colonic inflammation were performed by DSS administration to newly generated Nox4-/- mice. Pathologic analysis of colon tissues was performed, including detection of immune cells, proliferation, and fibrotic and inflammatory markers. RNA sequencing was performed to detect differentially expressed genes between Nox4-/- and wild-type mice in both the untreated and DSS-treated conditions, followed by functional enrichment analysis to explore the molecular mechanisms contributing to pathologic differences during DSS-induced colitis and after recovery.

RESULTS

Nox4-/- mice showed increased endogenous TGF-β signaling in the colon, increased reactive oxygen species levels, intensive inflammation, and an increased fibrotic region after DSS treatment compared with wild-type mice. Bulk RNA sequencing confirmed involvement of canonical TGF-β signaling in fibrogenesis of the DSS-induced colitis model. Up-regulation of TGF-β signaling affects collagen activation and T-cell lineage commitment, increasing the susceptibility for inflammation.

CONCLUSIONS

Nox4 protects against injury and plays a crucial role in fibrogenesis in DSS-induced colitis through canonical TGF-β signaling regulation, highlighting a new treatment target.

Bioinformatics Analysis of Immune Cell Infiltration and Diagnostic Biomarkers between Ankylosing Spondylitis and Inflammatory Bowel Disease

Background

Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are both autoimmune diseases, and they often occur together in clinical practice, but the pathogenesis is unclear. This study is aimed at identifying the hub genes and explore the related immune molecular mechanisms between AS and IBD by bioinformatics analysis.

Methods

From the public Gene Expression Omnibus (GEO) database, the AS and IBD datasets (GSE73754, GSE59071, GSE25101, and GSE36807) were obtained. The immune cell infiltration in the peripheral blood tissues of GSE73754 and GSE59071 was assessed using the CIBERSORT algorithm. Then, we used the Weighted Gene Coexpression Network Analysis (WGCNA) to identify the Differentially Expressed Genes (DEGs) related to AS and IBD. Then, the immune genes from the ImmPort database intersected with the DEGs to obtain hub genes. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzed the functional correlation of hub genes. Then, hub genes were verified in GSE25101 and GSE36807. The clusterProfiler software and Gene Set Enrichment Analysis (GSEA) were used to conduct functional enrichment and pathway enrichment studies. Finally, the diagnostic efficacy was assessed using Receiver Operating Characteristic (ROC) curve analysis.

Results

The analysis of immune characteristics showed that both AS and IBD were related to immunity, and neutrophils were positively correlated in both diseases. Nine coexpressed genes, including FCGRT, S100A11, IFNGR1, NFKBIZ, JAK2, LYN, PLAUR, ADM, and IL1RN, were linked to immune cells. The GO and KEGG analyses results showed that enrichment analysis was mainly related to cell transport and migration. Finally, the ROC curve was verified with the validation set, and it was found that PLAUR has clinical diagnostic significance and the most excellent specificity and sensitivity, respectively.

Conclusions

PLAUR (uPAR) is a promising biomarker and will be an underlying genetic biomarker for diagnosing AS comorbid IBD. Inflammation and immunological modulation mediated by neutrophil infiltration were important in the development of AS and IBD and may be diagnostic and therapeutic targets.

LncRNA-miRNA-mRNA Network Analysis Reveals the Potential Biomarkers in Crohn’s Disease Rats Treated with Herb-Partitioned Moxibustion

Background

Long noncoding RNA (lncRNA) is receiving growing attention in Crohn’s disease (CD). However, the mechanism by which herb-partitioned moxibustion (HPM) regulates the expression and functions of lncRNAs in CD rats is still unclear. The aim of our study is to identify lncRNA-miRNA-mRNA network potential biological functions in CD.

Methods

RNA sequencing and microRNA (miRNA) sequencing were carried out to analyze lncRNA, miRNA and mRNA expression profiles among the CD rats, normal control rats, and CD rats after HPM treatment and constructed the potential related lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein–protein interaction (PPI) analysis and quantitative real-time polymerase chain reaction (qRT-PCR) were performed to explore potentially important genes in ceRNA networks.

Results

A total of 189 lncRNAs, 32 miRNAs and 463 mRNAs were determined as differentially expressed (DE) genes in CD rats compared to normal control rats, and 161 lncRNAs, 12 miRNAs and 130 mRNAs were identified as remarkably DE genes in CD rats after HPM treatment compared to CD rats. GO analysis indicated that the target genes were most enriched in cAMP and in KEGG pathway analysis the main pathways included adipocytokine, PPAR, AMPK, FoxO and PI3K-Akt signaling pathway. Finally, qRT-PCR results confirmed that lncRNA LOC102550026 sponged miRNA-34c-5p to regulate the intestinal immune inflammatory response by targeting Pck1.

Conclusion

By constructing a ceRNA network with lncRNA-miRNA-mRNA, PCR verification, and KEGG analysis, we revealed that LOC102550026/miRNA-34c-5p/Pck1 axis and adipocytokine, PPAR, AMPK, FoxO, and PI3K-Akt signaling pathways might regulate the intestinal immune-inflammatory response, and HPM may regulate the lncRNA LOC102550026/miR-34c-5p/Pck1 axis and adipocytokine, PPAR, AMPK, FoxO, and PI3K-Akt signaling pathways, thus improving intestinal inflammation in CD. These findings may be novel potential targets in CD.

Machine learning gene expression predicting model for ustekinumab response in patients with Crohn's disease

Background

Recent studies reported the responses of ustekinumab (UST) for the treatment of Crohn's disease (CD) differ among patients, while the cause was unrevealed. The study aimed to develop a prediction model based on the gene transcription profiling of patients with CD in response to UST.

Methods

The GSE112366 dataset, which contains 86 CD and 26 normal samples, was downloaded for analysis. Differentially expressed genes (DEGs) were identified first. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were administered. Least absolute shrinkage and selection operator regression analysis was performed to build a model for UST response prediction.

Results

A total of 122 DEGs were identified. GO and KEGG analyses revealed that immune response pathways are significantly enriched in patients with CD. A multivariate logistic regression equation that comprises four genes (HSD3B1, MUC4, CF1, and CCL11) for UST response prediction was built. The area under the receiver operator characteristic curve for patients in training set and testing set were 0.746 and 0.734, respectively.

Conclusions

This study is the first to build a gene expression prediction model for UST response in patients with CD and provides valuable data sources for further studies.

Leonurine protects against ulcerative colitis by alleviating inflammation and modulating intestinal microflora in mouse models

Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the colon. The aim of the present study was to explore the effects of leonurine (YMJ) on inflammation and intestinal microflora in colonic tissues of a dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) mouse model. Mice were randomly divided into control (n=5), DSS (n=5, treated with DSS) and DSS+YMJ (n=5, treated with DSS and YMJ) groups. Body weight was recorded, disease activity index (DAI) was calculated, and colon histopathology was evaluated using hematoxylin and eosin staining. Serum interleukin (IL)-6, tumor necrosis factor-α (TNF-α) and IL-1β levels were examined using ELISA. Expression levels of nuclear factor-κB (p65) and phosphorylated (p)-p65 were evaluated via western blotting. 16S ribosomal RNA was extracted from mouse feces. Composition or abundance changes of intestinal microflora were analyzed. The results indicated that YMJ treatment (DSS+YMJ group) significantly increased body weight, reduced DAI scores and increased colon length in UC mouse models compared with those in the DSS group (P<0.05). YMJ significantly reduced inflammatory infiltration, significantly decreased serum TNF-α, IL-6 and IL-1β levels (P<0.05) and significantly downregulated the p-p65/p65 ratio compared with the DSS group (P<0.05). YMJ increased the quantity of the intestinal flora and improved intestinal microflora diversity in the mice of the DSS group. Specifically, YMJ partly regulated intestinal microflora in feces, including a reduction of Bifidobacterium, and an increase in Parasutterella and Ackermania. In conclusion, YMJ improved disease outcomes of the UC mice, reduced the levels of serum inflammatory factors and increased the ratio of beneficial bacteria in the intestinal tract.

Identification of hub genes in rheumatoid arthritis through an integrated bioinformatics approach

Background

Rheumatoid arthritis (RA) is a common chronic autoimmune disease characterized by inflammation of the synovial membrane. However, the etiology and underlying molecular events of RA are unclear. Here, we applied bioinformatics analysis to identify the key genes involved in RA.

Methods

GSE77298 was downloaded from the Gene Expression Omnibus (GEO) database. We used the R software screen the differentially expressed genes (DEGs). Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway were analyzed by using the DAVID online tool. The STRING database was used to analyze the interaction of differentially encoded proteins. PPI interaction network was divided into subnetworks using MCODE algorithm and was analyzed using Cytoscape. Gene set enrichment analysis (GSEA) was performed to identify relevant biological functions. qRT-PCR analysis was also performed to verify the expression of identified hub DEGs.

Results

A total of 4062 differentially expressed genes were selected, including 1847 upregulated genes and 2215 downregulated genes. In the biological process, DEGs were mainly concentrated in the fields of muscle filament sliding, muscle contraction, intracellular signal transduction, cardiac muscle contraction, signal transduction, and skeletal muscle tissue development. In the cellular components, DEGs were mainly concentrated in the parts of cytosol, Z disk, membrane, extracellular exosome, mitochondrion, and M band. In molecular functions, DEGs were mainly concentrated in protein binding, structural constituent of muscle, actin binding, and actin filament binding. KEGG pathway analysis shows that DEGs mainly focuses on pathways about lysosome, Wnt/β-catenin signaling pathway, and NF-κB signaling pathway. CXCR3, GNB4, and CXCL16 were identified as the core genes that involved in the progression of RA. By qRT-PCR analysis, we found that CXCR3, GNB4, and CXCL16 were significantly upregulated in RA tissue as compared to healthy controls.

Conclusion

In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the progression of RA, and provide candidate targets for diagnosis and treatment of RA.

Integrated Analysis of Multiple Microarray Studies to Identify Novel Gene Signatures in Ulcerative Colitis

Background: Ulcerative colitis (UC) is a chronic, complicated, inflammatory disease with an increasing incidence and prevalence worldwide. However, the intrinsic molecular mechanisms underlying the pathogenesis of UC have not yet been fully elucidated.

Methods: All UC datasets published in the GEO database were analyzed and summarized. Subsequently, the robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between UC patients and controls. Gene functional annotation and PPI network analysis were performed to illustrate the potential functions of the DEGs. Some important functional modules from the protein-protein interaction (PPI) network were identified by molecular complex detection (MCODE), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG), and analyses were performed. The results of CytoHubba, a plug for integrated algorithm for biomolecular interaction networks combined with RRA analysis, were used to identify the hub genes. Finally, a mouse model of UC was established by dextran sulfate sodium salt (DSS) solution to verify the expression of hub genes.

Results: A total of 6 datasets met the inclusion criteria (GSE38713, GSE59071, GSE73661, GSE75214, GSE87466, GSE92415). The RRA integrated analysis revealed 208 significant DEGs (132 upregulated genes and 76 downregulated genes). After constructing the PPI network by MCODE plug, modules with the top three scores were listed. The CytoHubba app and RRA identified six hub genes: LCN2, CXCL1, MMP3, IDO1, MMP1, and S100A8. We found through enrichment analysis that these functional modules and hub genes were mainly related to cytokine secretion, immune response, and cancer progression. With the mouse model, we found that the expression of all six hub genes in the UC group was higher than that in the control group (P < 0.05).

Conclusion: The hub genes analyzed by the RRA method are highly reliable. These findings improve the understanding of the molecular mechanisms in UC pathogenesis.

Intestinal mucosa-derived DNA methylation signatures in the penetrating intestinal mucosal lesions of Crohn's disease

The purpose of this study was to evaluate genome-wide DNA methylation changes in intestinal mucosa tissue of adult patients with Crohn's disease comprehensively. DNA methylation chip was used to analyze abnormal methylation sites among penetrating and non-penetrating intestinal mucosa tissue of Crohn's disease and normal intestinal mucosa tissue of healthy controls. Methylation abnormalities of different locus were verified by pyrosequencing and quantitative polymerase chain reaction. Differential DNA methylation sites were participated in the positive regulation of apoptosis and the positive regulation of IL-8 production and were enriched in signaling pathways related to inflammatory bowel disease and extracellular matrix receptor interaction signaling pathways. Correlation analysis showed that the methylation abnormalities of HLA-DRB1 (r = - 0.62, P < 0.001), MUC1 (r = - 0.45, P = 0.01), YPEL5 (r = - 0.55, P = 0.001) and CBLB (r = - 0.62, P < 0.001) were significantly negatively correlated with their relative expression levels. The degree of methylation abnormality of MUC1 was negatively correlated with the disease activity score of Crohn's disease (r = - 0.50, P = 0.01). Apoptosis, interleukin-8 production and abnormal extracellular matrix might be involved in the mechanism of penetrating intestinal mucosal lesions in Crohn's disease. The degree of abnormal methylation of MUC1 was negatively correlated with the disease activity of Crohn's disease.

Diagnostic and Predictive Value of Immune-Related Genes in Crohn's Disease

Abnormal immune cell infiltration is associated with the pathogenesis of Crohn’s disease (CD). This study aimed to determine the diagnostic and predictive value of immune-related genes in CD. Seven Gene Expression Omnibus datasets that analyzed the gene expression in CD tissues were downloaded. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate the infiltration of the immune cells in CD tissues. Immune-related genes were screened by overlapping the immune-related genes with differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was used to identify key immune-related DEGs. Diagnostic value of CD and predictive value of anti-TNFα therapy were analyzed. Immunohistochemical (IHC) assay was used to verify gene expression in CD tissues. There were significant differences among CD tissues, paired CD tissues, and normal intestinal tissues regarding the infiltration of immune cells. AQP9, CD27, and HVCN1 were identified as the key genes of the three sub-clusters in the PPI network. AQP9, CD27, and HVCN1 had mild to moderate diagnostic value in CD, and the diagnostic value of AQP9 was better than that of CD27 and HVCN1. AQP9 expression was decreased in CD after patients underwent anti-TNFα therapy, but no obvious changes were observed in non-responders. AQP9 had a moderate predictive value in patients who had undergone treatment. IHC assay confirmed that the expression of AQP9, CD27, and HVCN1 in CD tissues was higher than that in normal intestinal tissues, and AQP9, CD27 was correlated with the activity of CD. Immune-related genes, AQP9, CD27, and HVCN1 may act as auxiliary diagnostic indicators for CD, and AQP9 could serve as a promising predictive indicator in patients who underwent anti-TNF therapy.

Bioinformatics Analysis of Differentially Expressed Genes and Protein-Protein Interaction Networks Associated with Functional Pathways in Ulcerative Colitis

Background

This bioinformatics study aimed to identify differentially expressed genes (DEGs) and protein–protein interaction (PPI) networks associated with functional pathways in ulcerative colitis based on 3 Gene Expression Omnibus (GEO) datasets.

Material/Methods

The GSE87466, GSE75214, and GSE48958 MINiML formatted family files were downloaded from the GEO database. DEGs were identified from the 3 datasets, and volcano maps and heat maps were drawn after R language standardization and analysis, respectively. Venn diagram software was used to identify common DEGs. PPI analysis of common DEGs was performed using the Search Tool for the Retrieval of Interacting Genes. Gene modules and hub genes were visualized in the PPI network using Cytoscape. Enrichment analysis was performed for all common DEGs, module genes, and hub genes.

Results

A total of 90 DEGs were selected, which included 3 functional modules and 1 hub gene module. CXCL8 module genes were mainly enriched in cytokine-mediated signaling pathways and interleukin (IL)-10 signaling. CCL20 module genes were mainly enriched in the IL-17 signaling pathway and cellular response to IL-1. Hub gene modules mainly involved IL-10, IL-4, and IL-13 signaling pathways. CXCL8, CXCL1, and IL-1β were the top 3 hub genes and were mainly involved in IL-10 signaling.

Conclusions

Bioinformatics analysis using 3 GEO datasets identified CXCL8, CXCL1, and IL-1β, which are involved in IL-10 signaling, as the top 3 hub genes in ulcerative colitis. The findings from this study remain to be validated, but they may contribute to the further understanding of the pathogenesis of ulcerative colitis.

Transcriptome Analysis and the Prognostic Role of NUDC in Diffuse and Intestinal Gastric Cancer

INTRODUCTION

There have been few studies about gene differences between patients with diffuse-type gastric cancer and those with intestinal-type gastric cancer. The aim of this study was to compare the transcriptomes of signet ring cell gastric cancer (worst prognosis in diffuse-type) and well-differentiated gastric cancer (best prognosis in intestinal-type); NUDC was identified, and its prognostic role was studied.

MATERIALS AND METHODS

We performed next-generation sequencing with 5 well-differentiated gastric cancers and 3 of signet ring cell gastric cancer surgical samples. We performed gene enrichment and functional annotation analysis using the Database for Annotation, Visualization and Integrated Discovery bioinformatics resources. Immunohistochemistry was used to validate NUDC expression.

RESULTS

Overall, 900 genes showed significantly higher expression, 644 genes showed lower expression in signet ring cell gastric cancer than in well-differentiated gastric cancers, and there was a large difference in adhesion, vascular development, and cell-to-cell junction components between the 2 subtypes. We performed variant analysis and found 52 variants and 30 cancer driver genes, including NUDC. We analyzed NUDC expression in gastric cancer tissue and its relationship with prognosis. Cox proportional hazard analysis identified T stage, N stage, and NUDC expression as independent risk factors for survival (P < 0.05). The overall survival of the NUDC-positive group was significantly higher (53.2 ± 0.92 months) than that of the NUDC-negative group (44.6 ± 3.7 months) (P = 0.001) in Kaplan-Meier survival analysis.

CONCLUSION

We found 30 cancer driver gene candidates and found that the NUDC-positive group showed significantly better survival than the NUDC-negative group via variant analysis.

Identification of Differential Intestinal Mucosa Transcriptomic Biomarkers for Ulcerative Colitis by Bioinformatics Analysis

Background

Ulcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affect mucosal homeostasis and triggers inappropriate immune response. The purpose of the study was to identify significant biomarkers with potential therapeutic targets and the underlying mechanisms.

Methods

The gene expression profiles of GSE48958, GSE73661, and GSE59071 are from the GEO database. Differentially expressed genes (DEGs) were screened by the GEO2R tool. Next, the Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Then, protein-protein interaction (PPI) was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING).

Results

There were a total of 128 common DEGs genes, including 86 upregulated genes enriched in extracellular space, regulation of inflammatory response, chemokine-mediated signaling pathway, response to lipopolysaccharide, and cell proliferation, while 42 downregulated genes enriched in the integral component of the membrane, the integral component of the plasma membrane, apical plasma membrane, symporter activity, and chloride channel activity. The KEGG pathway analysis results demonstrated that DEGs were particularly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, chemokine signaling pathway, pertussis, and rheumatoid arthritis. 18 central modules of the PPI networks were selected with Cytotype MCODE. Furthermore, 18 genes were found to significantly enrich in the extracellular space, inflammatory response, chemokine-mediated signaling pathway, TNF signaling pathway, regulation of cell proliferation, and immune response via reanalysis of DAVID.

Conclusion

The study identified DEGs, key target genes, functional pathways, and pathway analysis of UC, which may provide potential molecular targets and diagnostic biomarkers for UC.

Possible role of microRNA miRNA-IL-25 interaction in mice with ulcerative colitis

Background: The regulatory network of ulcerative colitis (UC)-associated miRNAs is not fully understood. In this study, we aim to investigate the global profile and regulatory network of UC associated miRNAs in the context of dextran sulfate sodium (DSS). Methods: UC was induced in C57BL mice using DSS. Differentially expressed miRNAs were screened by RNA sequencing and subjected to the Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analysis. RT-qPCR was used to verify the differential expression of miRNAs and candidate target mRNA. Luciferase reporter vector bearing a miRNA binding site was constructed to verify the binding site of the miRNA on mRNA. Results:A total of 95 miRNAs (31 were up-regulated and 64 were down regulated) differentially expressed in the colonic tissues of the UC mice. Among the differentially expressed miRNAs, IL-25 pathway genes were enriched. Subsequent RT-qPCR confirmed a decreased expression of IL-25 and a significant up regulation of IL-25 target miRNAs including mmu-miR-135b-5p, mmu-miR-7239-5p and mmu-miR-691 in UC mice. Conclusion: Using the luciferase assay, we verified the biding sites of mmu-miR-135b-5p and mmu-miR-691 to the IL-25 3ʹUTR. In conclusion, mmu-miR-135b-5p:IL-25 and mmu-miR-691:IL-25 interactions are important pathways that may exert a protective role in UC.

Identification of drug targets and potential molecular mechanisms for Wantong Jingu Tablet extract in treatment of rheumatoid arthritis: bioinformatics analysis of fibroblast-like synoviocytes

Background

Rheumatoid arthritis-fibroblast-like synoviocytes (RA-FLSs) play important roles in pathogenesis of rheumatoid arthritis (RA). Wantong Jingu Tablet (WJT), a mixture of traditional Chinese medicine, is a potentially effective therapy for RA, but its underlying mechanism is unclear. In this study, we explore the effects of WJT on human RA-FLSs and the underlying molecular mechanism.

Methods

The major components of WJT were determined using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). Cell proliferative ability was evaluated by CCK-8, colony formation assay, and EdU incorporation assay. Cell apoptotic capacity was examined by caspase-3 and caspase-9 activity test. Protein levels of Bax and Bcl-2 were investigated by western blotting. High-throughput sequencing and bioinformatics analysis were conducted to screen and identify targeted genes, followed by identification by qRT-PCR and western blotting.

Results

In this study, we have identified 346 compounds in WJT. Our results showed that WJT inhibited the RA-FLSs proliferation, and promoted apoptosis in a dose- and time-dependent manner. More importantly, 184 differentially expressed genes (DEGs) has been screened after WJT treatment based on DEGSeq2 and 278 DEGs was identified by DEGSeq2 combined with WGCNA. Then, 10 hub genes were identified based on two different analyses, while the expression levels of only SMC3, THOC1, BUB1, and STAG2 were decreased after WJT treatment, which was identical to the sequencing profiles.

Conclusions

WJT exerted its anti-proliferation and pro-apoptosis effects possibly through suppressing the expression of SMC3, THOC1, BUB1, and STAG2 in RA-FLSs. Thus, therapeutics targeting these genes may be a promising strategy for rescuing RA.

Reduced expression of COVID-19 host receptor, ACE2 is associated with small bowel inflammation, more severe disease, and response to anti-TNF therapy in Crohn's disease

Angiotensin-Converting Enzyme 2 ( ACE2 ) has been identified as the host receptor for SARS-coronavirus 2 (SARS-CoV-2) which has infected millions world-wide and likely caused hundreds of thousands of deaths. Utilizing transcriptomic data from four cohorts taken from Crohn's disease (CD) and non-inflammatory bowel disease (IBD) subjects, we observed evidence of increased ACE2 mRNA in ileum with demographic features that have been associated with poor outcomes in COVID-19 including age and raised BMI. ACE2 was downregulated in CD compared to controls in independent cohorts. Within CD, ACE2 expression was reduced in inflamed ileal tissue and also remarkably, from uninvolved tissue in patients with a worse prognosis in both adult and pediatric cohorts. In active CD, small bowel ACE2 expression was restored by anti-TNF therapy particularly in anti-TNF responders. Collectively our data suggest that ACE2 downregulation is associated with inflammation and worse outcomes in CD.

Identification of breast cancer risk modules via an integrated strategy

Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.