Investigation of Potential Genetic Biomarkers and Molecular Mechanism of Ulcerative Colitis Utilizing Bioinformatics Analysis

Screening and experimental validation of diagnostic gene in ulcerative colitis with anti-TNF-α therapy

In clinical practice, the diagnosis of ulcerative colitis (UC) mainly relies on a comprehensive analysis of a series of signs and symptoms of patients. The current biomarkers for diagnosis of UC and prognostic prediction of anti-TNF-α therapy are inaccurate. The present study aimed to perform an integrative analysis of gene expression profiles in patients with UC. A total of seven datasets from the GEO database that met our strict inclusion criteria were included. After identifying differentially expressed genes (DEGs) between UC patients and healthy individuals, the diagnostic and prognostic utility of the DEGs were then analyzed via least absolute shrinkage and selection operator and support-vector machine recursive feature elimination. Subgroup analyses of the treated and untreated groups, as well as the treatment-response group and non-response group, were also performed. Furthermore, the relationship between the expressions of UC-related genes and infiltration of immune cells in the course of treatment was also investigated. Immunohistochemical (IHC) assay was used to verify the gene expression in inflamed UC tissues. When considering all the applied methods, DUOX2, PI3, S100P, MMP7, and S100A8 had priority to be defined as the characteristic genes among DEGs. The area under curve (AUC) of the five genes, which were all consistently over-expressed, based on an external validation dataset, were all above 0.94 for UC diagnosis. Four of the five genes (DUOX2, PI3, MMP7, and S100A8) were down-regulated between treatment-responsive and nonresponsive patients. A significant difference was also observed concerning the infiltration of immune cells, including macrophage and neutrophil, between the two groups (treatment responsive and nonresponsive). The changes in the expression of DUOX2 and MMP7 based on the IHC assay were highly consistent with the results obtained in the current study. This confirmed the mild to moderate diagnostic and predictive value of DUOX2 and MMP7 in patients with UC. The conducted analyses showed that the expression profile of the five identified biomarkers accurately detects UC, whereas four of the five genes evidently predicted the response to anti-TNF-α therapy.

Potential shared pathogenic mechanisms between endometriosis and inflammatory bowel disease indicate a strong initial effect of immune factors

Introduction

Over the past decades, immune dysregulation has been consistently demonstrated being common charactoristics of endometriosis (EM) and Inflammatory Bowel Disease (IBD) in numerous studies. However, the underlying pathological mechanisms remain unknown. In this study, bioinformatics techniques were used to screen large-scale gene expression data for plausible correlations at the molecular level in order to identify common pathogenic pathways between EM and IBD.

Methods

Based on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and GSE126124, differential gene analysis was performed using the limma package in the R environment. Co-expressed differentially expressed genes were identified, and a protein-protein interaction (PPI) network for the differentially expressed genes was constructed using the 11.5 version of the STRING database. The MCODE tool in Cytoscape facilitated filtering out protein interaction subnetworks. Key genes in the PPI network were identified through two topological analysis algorithms (MCC and Degree) from the CytoHubba plugin. Upset was used for visualization of these key genes. The diagnostic value of gene expression levels for these key genes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) The CIBERSORT algorithm determined the infiltration status of 22 immune cell subtypes, exploring differences between EM and IBD patients in both control and disease groups. Finally, different gene expression trends shared by EM and IBD were input into CMap to identify small molecule compounds with potential therapeutic effects.

Results

113 differentially expressed genes (DEGs) that were co-expressed in EM and IBD have been identified, comprising 28 down-regulated genes and 86 up-regulated genes. The co-expression differential gene of EM and IBD in the functional enrichment analyses focused on immune response activation, circulating immunoglobulin-mediated humoral immune response and humoral immune response. Five hub genes (SERPING1、VCAM1、CLU、C3、CD55) were identified through the Protein-protein Interaction network and MCODE.High Area Under the Curve (AUC) values of Receiver Operating Characteristic (ROC) curves for 5hub genes indicate the predictive ability for disease occurrence.These hub genes could be used as potential biomarkers for the development of EM and IBD. Furthermore, the CMap database identified a total of 9 small molecule compounds (TTNPB、CAY-10577、PD-0325901 etc.) targeting therapeutic genes for EM and IBD.

Discussion

Our research revealed common pathogenic mechanisms between EM and IBD, particularly emphasizing immune regulation and cell signalling, indicating the significance of immune factors in the occurence and progression of both diseases. By elucidating shared mechanisms, our study provides novel avenues for the prevention and treatment of EM and IBD.

Identification and immunoinfiltration analysis of key genes in ulcerative colitis using WGCNA

Objective

Ulcerative colitis (UC) is a chronic non-specific inflammatory bowel disease characterized by an unclear pathogenesis. This study aims to screen out key genes related to UC pathogenesis.

Methods

Bioinformatics analysis was conducted for screening key genes linked to UC pathogenesis, and the expression of the screened key genes was verified by establishing a UC mouse model.

Results

Through bioinformatics analysis, five key genes were obtained. Subsequent infiltration analysis revealed seven significantly different immune cell types between the UC and general samples. Additionally, animal experiment results illustrated markedly decreased body weight, visible colonic shortening and damage, along with a significant increase in the DAI score of the DSS-induced mice in the UC group in comparison with the NC group. In addition, H&E staining results demonstrated histological changes including marked inflammatory cell infiltration, loss of crypts, and epithelial destruction in the colon mucosa epithelium. qRT-PCR analysis indicated a down-regulation of ABCG2 and an up-regulation of IL1RN, REG4, SERPINB5 and TRIM29 in the UC mouse model. Notably, this observed trend showed a significant dependence on the concentration of DSS, with the mouse model of UC induced by 7% DSS demonstrating a more severe disease state compared to that induced by 5% DSS.

Conclusion

ABCG2, IL1RN, REG4, SERPINB5 and TRIM29 were screened out as key genes related to UC by bioinformatics analysis. The expression of ABCG2 was down-regulated, and that of IL1RN, REG4, SERPINB5 and TRIM29 were up-regulated in UC mice as revealed by animal experiments.

Management of ulcerative colitis by dichloroacetate: Impact on NFATC1/NLRP3/IL1B signaling based on bioinformatics analysis combined with in vivo experimental verification

The inflammatory response in ulcerative colitis (UC) could be relieved by the conventional immunomodulatory agents; 5-aminosalicylic acid, corticosteroids, or azathioprine. However, the low remission rates and the intolerance to these agents necessitate investigation of gene expression signature in UC that could influence the therapeutic efficacy of drugs, as well as the interference with persistence genes by novel therapeutic option. Three microarray datasets (GSE66407, GSE38713 and GSE14580) from the NCBI-GEO database were utilized. Differentially expressed genes between samples of patients with UC and healthy ones were analyzed using R software. In addition, in vivo study using oxazolone-induced UC in BALB/c mice was carried out to investigate the proposed therapeutic efficacy of dichloroacetate (DCA). The bioinformatics analysis revealed the persistence of NLRP3, NFATC1, and IL1B in UC despite treatment with common therapeutic agents. DCA administration to oxazolone-treated mice showed remarkable interference with those persistence genes. Western blotting analysis for NLRP3, NFATC1, nuclear/total NF-κB, and cleaved caspase-1 revealed the ability of DCA to reduce the expression levels of these proteins in oxazolone-treated mice. Additionally, the inflammatory cytokines IL-1β and IL-13 were reduced in colonic tissue by DCA treatment. The therapeutic efficacy of DCA was further confirmed by the apparent reduction in histopathological scoring, disease activity index, and the normalization of colon length. Therefore, DCA could be suggested as a novel and promising therapeutic option in UC based on its ability to interfere with the persistence of NFATC1/NLRP3/IL1B signaling. That merits further safety/toxicological pre-clinical assessment and update of bioavailability/metabolism data prior to clinical investigation.

SLC6A14 promotes ulcerative colitis progression by facilitating NLRP3 inflammasome-mediated pyroptosis

BACKGROUND

Ulcerative colitis (UC) is an inflammatory condition with frequent relapse and recurrence. Evidence suggests the involvement of SLC6A14 in UC pathogenesis, but the central regulator remains unknown.

AIM

To explore the role of SLC6A14 in UC-associated pyroptosis.

METHODS

Quantitative real-time polymerase chain reaction (qRT-PCR), immunoblotting, and immunohistochemical were used to assess SLC6A14 in human UC tissues. Lipopolysaccharide (LPS) was used to induce inflammation in FHC and NCM460 cells and model enteritis, and SLC6A14 levels were assessed. Pyroptosis markers were quantified using enzyme-linked immunosorbent assay, Western blotting, and qRT-PCR, and EdU incubation, CCK-8 assays and flow cytometry were used to examine proliferation and apoptosis. Mouse models of UC were used for verification.

RESULTS

SLC6A14 was increased and correlated with NLRP3 in UC tissues. LPS-induced FHC and NCM460 cells showed increased SLC6A14 levels. Reducing SLC6A14 increased cell proliferation and suppressed apoptosis. Reducing SLC6A14 decreased pyroptosis-associated proteins (ASC, IL-1β, IL-18, NLRP3). NLRP3 overexpression counteracted the effects of sh-SLC6A14 on LPS-induced FHC and NCM460 cell pyroptosis. SLC6A14 improved the mucosa in mice with dextran sulfate sodium-induced colitis.

CONCLUSION

SLC6A14 promotes UC pyroptosis by regulating NLRP3, suggesting the therapeutic potential of modulating the SLC6A14/NLRP3 axis.

Single-Cell RNA-Sequencing Analysis of Colonic Lamina Propria Immune Cells Reveals the Key Immune Cell-Related Genes of Ulcerative Colitis

Background

Ulcerative colitis (UC) is a severe threat to humans worldwide. Single-cell RNA sequencing (scRNA-seq) can be used to screen gene expression patterns of each cell in the intestine, provide new insights into the potential mechanism of UC, and analyze the development of immune cell changes. These findings can provide new ideas for the diagnosis and treatment of intestinal diseases. In this study, bioinformatics analysis combined with experiments applied in dextran sulfate sodium (DSS)-induced colitis mice was used to explore new diagnostic genes for UC and their potential relationship with immune cells.

Methods

We downloaded microarray datasets (GSE75214, GSE87473, GSE92415) from the Gene Expression Omnibus and used these datasets to screen differentially expressed genes (DEGs) and conduct Weighted Gene Co-expression Network Analysis (WGCNA) after quality control. The hub genes were screened, and ROC curves were drawn to verify the reliability of the results in both training set (GSE75214, GSE87473, GSE92415) and validation cohort (GSE87466). Also, we explored the relation of diagnostic genes and immune cells by CIBERSORT algorithm and single-cell analysis. Finally, the expression of hub genes and their relation with immune cells were verified in DSS-induced colitis mice.

Results

Diagnostic genes (ANXA5, MMP7, NR1H4, CYP3A4, ABCG2) were identified. In addition, we found these five genes firmly related to immune infiltration. The DSS-induced colitis mice confirm that the expression of ANXA5 mainly increased in the intestinal macrophages and had a strong negative correlation with M2 macrophages, which indicated its possible influence on the polarization of macrophages in UC patients.

Conclusion

We identified ANXA5, MMP7, NR1H4, CYP3A4, and ABCG2 as diagnostic genes of UC that are closely related to immune infiltration and ANXA5 maintains a negative correlation with M2 macrophages which indicated its possible influence on the polarization of macrophage in UC patients.

Electroacupuncture alleviates ulcerative colitis by targeting CXCL1: evidence from the transcriptome and validation

Background

We aimed to use transcriptomics, bioinformatics analysis, and core gene validation to identify the core gene and potential mechanisms for electroacupuncture (EA) treatment of ulcerative colitis (UC).

Materials and methods

EA was performed in mice after induction of UC via dextran sodium sulfate. Body weight, disease activity index (DAI), colon length, and hematoxylin-eosin of the colon tissue were used to evaluate the effects of EA. Mice transcriptome samples were analyzed to identify the core genes, and further verified with human transcriptome database; the ImmuCellAI database was used to analyze the relationship between the core gene and immune infiltrating cells (IICs); and immunofluorescence was used to verify the results.

Results

EA could reduce DAI and histological colitis scores, increase bodyweight and colon length, and improve the expression of local and systemic proinflammatory factors in the serum and colon of UC mice. Eighteen co-differentially expressed genes were identified by joint bioinformatics analyses of mouse and human transcriptional data; Cxcl1 was the core gene. EA affected IICs by inhibiting Cxcl1 expression and regulated the polarization of macrophages by affecting the Th1 cytokine IFN-γ, inhibiting the expression of CXCL1.

Conclusions

CXCL1 is the target of EA, which is associated with the underlying immune mechanism related to Th1 cytokine IFN-γ.

Gegen Qinlian decoction (GQD) inhibits ulcerative colitis by modulating ferroptosis-dependent pathway in mice and organoids

BACKGROUND

Gegen Qinlian decoction (GQD) is a classic prescription for treating ulcerative colitis (UC) in traditional Chinese medicine. However, the therapeutic mechanism has not been fully clarified.

PURPOSE

In the present study, we aimed to evaluate the role of ferroptosis-mediated IEC death in UC treated mice with GQD by using DSS-induced a colitis mouse model and RSL3-induced ferroptosis in intestinal organoids.

METHODS

The effects of GQD on DSS-treated colitis were examined via daily body weight, DAI, colon length, HE staining, PAS staining, ZO-1 and Occludin immunohistochemical staining. Ferroptosis was determined by analysis of iron load, MDA, GSH, mitochondrial morphology, and expression of ferroptosis-associated proteins (GPX4, SLC7A11 and ACSL4).

RESULTS

In vivo, GQD administration reduced body weight loss and DAI scores, increased colon length, and improved intestinal histological characteristics and epithelial barrier dysfunction. GQD administration obviously improved the levels of ferroptosis markers (iron load, MDA, GSH, and mitochondrial morphology) and the expression of ferroptosis-associated proteins (GPX4, SLC7A11 and ACSL4). Consistent with in vivo results, GQD administration partially reversed the levels of mtROS, Fe2+ and MDA in intestinal organoids induced by RSL3, and notably improved morphological destruction, histological damage and epithelial barrier dysfunction in organoids.

CONCLUSIONS

In this study, we demonstrated that ferroptosis was triggered in DSS-induced experimental colitis and that GQD adiministration could protect against colonic damage and intestinal epithelial barrier dysfunction by inhibiting ferroptosis.

Serum amyloid protein A in inflammatory bowel disease: from bench to bedside

Inflammatory bowel diseases (IBD) is featured by gastrointestinal inflammation and a disease course with alternating recurrence and remission. The global burden caused by IBD has significantly boosted in recent years, necessitating treatment optimization. Serum amyloid A (SAA) is a class of 104 amino acid conservative acute-phase proteins, which is essential in immune-mediated inflammatory processes, like IBD. The SAA monomeric structure is composed of four α-helical regions and a C-terminal amorphous tail. Its disordered structure enables multiple bindings to different ligands and permits multiple functions. It has been proven that SAA has dual roles in the inflammatory process. SAA stimulates the pro-inflammatory cytokine expression and promotes the pathogenic differentiation of TH17 cells. In addition, SAA can remove toxic lipids produced during inflammatory responses and membrane debris from dead cells, redirect HDL, and recycle cholesterol for tissue repair. In IBD, SAA acts on gut epithelium barriers, induces T-cell differentiation, and promotes phagocytosis of Gram-negative bacteria. Owing to the tight connection between SAA and IBD, several clinical studies have taken SAA for a biomarker for diagnosis, assessing disease activity, and predicting prognosis in IBD. Furthermore, 5-MER peptide, a drug specifically targeting SAA, has shown anti-inflammatory effects in some SAA-dependent animal models, providing novel insights into the therapeutic targets of IBD.

Identifying biomarkers associated with the diagnosis of ulcerative colitis via bioinformatics and machine learning

BACKGROUND

Ulcerative colitis (UC) is an idiopathic inflammatory disease with an increasing incidence. This study aimed to identify potential UC biomarkers and associated immune infiltration characteristics.

METHODS

Two datasets (GSE87473 and GSE92415) were merged to obtain 193 UC samples and 42 normal samples. Using R, differentially expressed genes (DEGs) between UC and normal samples were filtered out, and their biological functions were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Promising biomarkers were identified using least absolute shrinkage selector operator regression and support vector machine recursive feature elimination, and their diagnostic efficacy was evaluated through receiver operating characteristic (ROC) curves. Finally, CIBERSORT was used to investigate the immune infiltration characteristics in UC, and the relationship between the identified biomarkers and various immune cells was examined.

RESULTS

We found 102 DEGs, of which 64 were significantly upregulated, and 38 were significantly downregulated. The DEGs were enriched in pathways associated with interleukin-17, cytokine-cytokine receptor interaction and viral protein interactions with cytokines and cytokine receptors, among others. Using machine learning methods and ROC tests, we confirmed DUOX2, DMBT1, CYP2B7P, PITX2 and DEFB1 to be essential diagnostic genes for UC. Immune cell infiltration analysis revealed that all five diagnostic genes were correlated with regulatory T cells, CD8 T cells, activated and resting memory CD4 T cells, activated natural killer cells, neutrophils, activated and resting mast cells, activated and resting dendritic cells and M0, M1 and M2 macrophages.

CONCLUSIONS

DUOX2, DMBT1, CYP2B7P, PITX2 and DEFB1 were identified as prospective biomarkers for UC. A new perspective on understanding the progression of UC may be provided by these biomarkers and their relationship with immune cell infiltration.

Identification of diagnostic biomarks and immune cell infiltration in ulcerative colitis

We aimed to explore diagnostic biomarks and immune cell infiltration characteristics in ulcerative colitis (UC). We used the dataset GSE38713 as the training set and dataset GSE94648 as the test set. A total of 402 differentially expressed genes (DEGs) were obtained from GSE38713. Annotating, visualizing, and integrating discovery of these differential genes was performed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia Pathway (KEGG), and Gene Set Enrichment Analysis (GSEA). Protein-protein interaction networks were constructed from the STRING database, and protein functional modules were identified using the CytoHubba plugin of Cytoscape. Random forest and LASSO regression were used to screen for UC-related diagnostic markers, and ROC curves were generated to validate their diagnostic value. The composition of 22 immune cells was analyzed, and the immune cell infiltration in UC was analyzed using CIBERSORT. Results: Seven diagnostic markers associated with UC were identified: TLCD3A, KLF9, EFNA1, NAAA,WDR4, CKAP4, and CHRNA1. Immune cell infiltration assessment revealed that macrophages M1, activated dendritic cells, and neutrophil cells infiltrated relatively more compared to normal control samples. Our results suggest a new functional feature of UC and suggest potential biomarkers for UC through comprehensive analysis of integrated gene expression data.

Identification of hub genes and immune infiltration in ulcerative colitis using bioinformatics

Ulcerative colitis (UC) is a chronic inflammatory disease of the intestine, whose pathogenesis is not fully understood. Given that immune infiltration plays a key role in UC progression, our study aimed to assess the level of immune cells in UC intestinal mucosal tissues and identify potential immune-related genes. The GSE65114 UC dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between healthy and UC tissues were identified using the "limma" package in R, while their Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were determined with the clusterProfiler package. Protein-protein interaction network analysis and visualization were performed with STRING and Cytoscape. Immune cell infiltration was calculated with CIBERSORT. The relationship between hub genes and immune-infiltrated cells in UC was determined by Pearson correlation. A total of 206 DEGs were identified, of which 174 were upregulated and 32 downregulated. GO and KEGG functional classification indicated DEG enrichment in immune response pathways, including Toll-like receptor signaling, IL-17 signaling, and immune system process and chemokine signaling. 13 hub genes were identified. Infiltration matrix analysis of immune cells showed abundant plasma cells, memory B cells, resting CD4 memory T cells, γδ T cells, M0 and M1 macrophages, and neutrophils in UC intestinal tissues. Correlation analysis revealed 13 hub genes associated with immune-infiltrated cells in UC. 13 hub genes associated with immune-infiltrated cells in UC were identified; they included CXCL13, CXCL10, CXCL9, CXCL8, CCL19, CTLA4, CCR1, CD69, CD163, IL7R, PECAM1, TLR8 and TLR2. These genes could potentially serve as markers for the diagnosis and treatment of UC.

Identification of ferroptosis-related genes in ulcerative colitis: a diagnostic model with machine learning

Background

Ulcerative colitis (UC) is an idiopathic, chronic disorder characterized by inflammation, injury, and disruption of the colonic mucosa. However, there are still many difficulties in the diagnosis and differential diagnosis of UC. An increasing amount of research has shown a connection between ferroptosis and the etiology of UC. Therefore, our study aimed to identify the key genes related to ferroptosis in UC to provide new ideas for diagnosis UC.

Methods

Gene expression profiles of normal and UC samples were extracted from the Gene Expression Omnibus (GEO) database. By combining differentially expressed genes (DEGs), Weighted correlation network analysis (WGCNA) genes, and ferroptosis-related genes, hub genes were identified and then screened using Lasso regression. Based on the key genes, gene ontology (GO) and gene set enrichment analysis (GSEA) analyses were performed. We used NaiveBeyas, Logistic, IBk, and RandomForest algorithms to build a disease diagnosis model using the hub genes. The model was validated using GSE87473 as the validation set.

Results

Gene expression matrices of GSE87466 and GSE75214 were downloaded from the GEO database, including 184 UC patients and 43 control samples. A total of 699 DEGs were obtained. From FerrDb, 565 genes related to ferroptosis were identified. The 1,513 genes with the highest absolute correlation coefficient value in the MEblue module were obtained from WGCNA analysis. Five hub genes (LCN2, MUC1, PARP8, PLIN2, and TIMP1) were identified using the Lasso regression algorithm based on the overlapped DEGs, WGCNA-identified genes, and ferroptosis-related genes. GO and GSEA analyses revealed that 5 hub genes were identified as being involved in the negative regulation of transcription by competitive promoter binding, cellular response to citrate cycle_tca_cycle, cytosolic_dna_sensing pathway, UV-A, and beta-alanine metabolism. The logistic algorithm's values of the area under the curve (AUC)were 1.000 and 0.995 for training and validation cohorts, and sensitivity is 0.962, specificity is 1.000, respectively, as determined by comparing various methods.

Conclusions

The previously described hub genes were identified as being intimately related to ferroptosis in UC and capable of distinguishing UC patients from controls. By detecting the expression of several genes, this model may aid in diagnosing UC and understanding the etiology and treatment of the disease.

Identification of Potential Biomarkers and Immune Infiltration Characteristics in Ulcerative Colitis by Combining Results from Two Machine Learning Algorithms

Objective

This study was designed to identify potential biomarkers for ulcerative colitis (UC) and analyze the immune infiltration characteristics in UC.

Methods

Datasets containing human UC and normal control tissues (GSE87466, GSE107597, and GSE13367) were downloaded from the GEO database. Then, the GSE87466 and GSE107597 datasets were merged, and the differentially expressed genes (DEGs) between UC and normal control tissues were screened out by the “limma R” package. The LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) were performed to screen out the best biomarkers. The GSE13367 dataset was used as a validation cohort, and the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance. Finally, the immune infiltration characteristics in UC were explored by CIBERSORT, and we further analyzed the correlation between potential biomarkers and different immune cells.

Results

A total of 76 DEGs were screened out, among which 56 genes were upregulated and 20 genes were downregulated. Functional enrichment analysis revealed that these DEGs were mainly involved in immune response, chemokine signaling, IL−17 signaling, cytokine receptor interactions, inflammatory bowel disease, etc. ABCG2, HSPB3, SLC6A14, and VNN1 were identified as potential biomarkers for UC and validated in the GSE13367 dataset (AUC = 0.889, 95% CI: 0.797~0.961). Immune infiltration analysis by CIBERSORT revealed that there were significant differences in immune infiltration characteristics between UC and normal control tissues. A high level of memory B cells, γδ T cells, activated mast cells, M1 macrophages, neutrophils, etc. were found in the UC group, while a high level of M2 type macrophages, resting mast cells, eosinophils, CD8+ T cells, etc. were found in the normal control group.

Conclusion

ABCG2, HSPB3, SLC6A14, and VNN 1 were identified as potential biomarkers for UC. There was an obvious difference in immune infiltration between UC and normal control tissues, which may provide help to guide individualized treatment and develop new research directions.

The Importance of CXCL1 in the Physiological State and in Noncancer Diseases of the Oral Cavity and Abdominal Organs

CXCL1 is a CXC chemokine, CXCR2 ligand and chemotactic factor for neutrophils. In this paper, we present a review of the role of the chemokine CXCL1 in physiology and in selected major non-cancer diseases of the oral cavity and abdominal organs (gingiva, salivary glands, stomach, liver, pancreas, intestines, and kidneys). We focus on the importance of CXCL1 on implantation and placentation as well as on human pluripotent stem cells. We also show the significance of CXCL1 in selected diseases of the abdominal organs, including the gastrointestinal tract and oral cavity (periodontal diseases, periodontitis, Sjögren syndrome, Helicobacter pylori infection, diabetes, liver cirrhosis, alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), HBV and HCV infection, liver ischemia and reperfusion injury, inflammatory bowel disease (Crohn’s disease and ulcerative colitis), obesity and overweight, kidney transplantation and ischemic-reperfusion injury, endometriosis and adenomyosis).

Artemisinin Alleviates Intestinal Inflammation and Metabolic Disturbance in Ulcerative Colitis Rats Induced by DSS

Objective

This study is aimed to reveal the possible mechanisms of artemisinin in the treatment of ulcerative colitis (UC) through bioinformatics analysis and experimental verification in UC model rats.

Methods

Firstly, we searched two microarray data of the Gene Expression Omnibus (GEO) database to explore the differentially expressed genes (DEGs) between UC samples and normal samples. Then, we selected DEGs for gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The acute UC model of rats was established by using 3.5% dextran sulfate sodium (DSS) for 10 days to verify the core pathway. Finally, we evaluated the therapeutic effect of artemisinin at the molecular level and used metabonomics to study the endogenous metabolites in the rat serum.

Results

We screened in the GEO database and selected two eligible microarray datasets, GSE36807 and GSE9452. We performed GO function and KEGG pathway enrichment analyses of DEGs and found that these DEGs were mainly enriched in the inflammatory response, immune response, and IL-17 and NF-κB signaling pathways. Finally, we verified the IL-17 signaling pathway and key cytokines, and ELISA and immunohistochemical results showed that artemisinin could downregulate the expression of proinflammatory cytokines such as IL-1β and IL-17 in the IL-17 signaling pathway and upregulate the expression of the anti-inflammatory cytokine PPAR-γ. Metabolomics analysis showed that 33 differential metabolites were identified in the artemisinin group (AG) compared to the model group (MG). Differential metabolites were mainly involved in alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies.

Conclusion

In this study, we found that artemisinin can significantly inhibit the inflammatory response in UC rats and regulate metabolites and related metabolic pathways. This study provides a foundation for further research on the mechanism of artemisinin in the treatment of UC.

Increased SERPINA3 Level Is Associated with Ulcerative Colitis

Ulcerative colitis (UC) is a recurrent, chronic intestinal disease that is currently incurable. Its pathogenesis remains to be further understood. Therefore, seeking new biomarkers and potential drug targets is urgent for the effective treatment of UC. In this study, the gene expression profile GSE38713 was obtained from the GEO (Gene Expression Omnibus) database. Data normalisation and screening of the differentially expressed genes (DEGs) were conducted using R software, and gene ontology (GO) enrichment was performed using Metascape online tools. The PubMed database was used to screen new genes that have not been reported, and SERPINA3 was selected. The correlation between SERPINA3 and other inflammatory factors was analysed by Spearman correlation analysis. Finally, colitis model mice and an in-vitro model were established to validate the function of the SERPINA3 gene. SERPINA3 gene expression was markedly increased in UC patient samples, colitis models and in-vitro models and showed an association with other inflammatory factors. ROC analysis indicated that SERPINA3 could represent a potential biomarker of active UC. Additionally, silencing SERPINA3 in an in-vitro intestinal epithelial inflammatory model significantly decreased the mRNA level of inflammatory factors. This study provides supportive evidence that SERPINA3 may act as a key biomarker and potential drug target in UC treatment.

Identification of diagnostic genes and vital microRNAs involved in rheumatoid arthritis: based on data mining and experimental verification

Background

The pathogenesis of rheumatoid arthritis (RA) is complex. This study aimed to identify diagnostic biomarkers and transcriptional regulators that underlie RA based on bioinformatics analysis and experimental verification.

Material and Methods

We applied weighted gene co-expression network analysis (WGCNA) to analyze dataset GSE55457 and obtained the key module most relevant to the RA phenotype. We then conducted gene function annotation, gene set enrichment analysis (GSEA) and immunocytes quantitative analysis (CIBERSORT). Moreover, the intersection of differentially expressed genes (DEGs) and genes within the key module were entered into the STRING database to construct an interaction network and to mine hub genes. We predicted microRNA (miRNA) using a web-based tool (miRDB). Finally, hub genes and vital miRNAs were validated with independent GEO datasets, RT-qPCR and Western blot.

Results

A total of 367 DEGs were characterized by differential expression analysis. The WGCNA method divided genes into 14 modules, and we focused on the turquoise module containing 845 genes. Gene function annotation and GSEA suggested that immune response and inflammatory signaling pathways are the molecular mechanisms behind RA. Nine hub genes were screened from the network and seven vital regulators were obtained using miRNA prediction. CIBERSORT analysis identified five cell types enriched in RA samples, which were closely related to the expression of hub genes. Through ROC curve and RT-qPCR validation, we confirmed five genes that were specific for RA, including CCL25, CXCL9, CXCL10, CXCL11, and CXCL13. Moreover, we selected a representative gene (CXCL10) for Western blot validation. Vital miRNAs verification showed that only the differences in has-miR-573 and has-miR-34a were statistically significant.

Conclusion

Our study reveals diagnostic genes and vital microRNAs highly related to RA, which could help improve our understanding of the molecular mechanisms underlying the disorder and provide theoretical support for the future exploration of innovative therapeutic approaches.

MicroRNA-532-5p protects against cerebral ischemia-reperfusion injury by directly targeting CXCL1

We investigated the function of microRNA (miR)-532-5p in cerebral ischemia-reperfusion injury (CI/RI) and the underlying mechanisms using oxygen-glucose deprivation and reperfusion (OGD/R)-treated SH-SY5Y cells and middle cerebral artery occlusion (MCAO) model rats. MiR-532-5p levels were significantly downregulated in OGD/R-treated SH-SY5Y cells and the brain tissues of MCAO model rats. MiR-532-5p overexpression significantly reduced apoptosis, reactive oxygen species (ROS), and inflammation in the OGD/R-induced SH-SY5Y cells. Bioinformatics analysis using the targetscan and miRDB databases as well as dual luciferase reporter assays confirmed that miR-532-5p directly binds to the 3’UTR of C-X-C Motif Ligand 1 (CXCL1). Methylation-specific PCR (MSP) analysis showed that miR-532-5p expression was reduced in OGD/R-treated SH-SY5Y cells because of miR-532-5p promoter hypermethylation. Moreover, 5-azacytidine, a methylation inhibitor, restored miR-532-5p expression in OGD/R-treated SH-SY5Y cells. Brain tissues of MCAO model rats showed significantly increased cerebral infarction areas, cerebral water, neuronal apoptosis, and activated CXCL1/CXCR2/NF-κB signaling, but these effects were alleviated by intraventricular injection of miR-532-5p agomir. These findings demonstrate that miR-532-5p overexpression significantly reduces in vitro and in vivo CI/RI by targeting CXCL1. Thus, miR-532-5p is a potential therapeutic target for patients with CI/RI.

Potential Biomarkers Associated with Differential Manifestations of Ulcerative Colitis (UC) in Uyghur and Han Population in China

BACKGROUND

Ulcerative colitis (UC) is one of the main subtypes of inflammatory bowel disease (IBD). The incidence of UC in the Xinjiang region is relatively high in China and the manifestations of UC in Uyghur and Han patients are usually differential. This study aimed to identify potential biomarkers of UC.

METHODS

All miRNA and mRNA were extracted from the tissue samples obtained from participants in Xinjiang. Differential expression analysis was performed on all mRNAs and miRNAs. The target genes of miRNAs were predicted via three databases. The clusterProfiler package was used for GO and KEGG pathway enrichment analysis.

RESULTS

Preliminarily, four miRNAs and 15 genes were associated with the differential manifestations of UC in Uyghur and Han patients. Through the co-expression network construction and further screening in more samples, two miRNAs (hsa-miR-141-5p and hsa-miR-378a-5p) and three genes (ARNTL2, CLDN1 and SLC6A14) were found to be more crucial. These 15 genes were enriched in tight junction, NF-κB, and several other pathways.

CONCLUSION

Two miRNAs (hsa-miR-141-5p and hsa-miR-378a-5p) and three genes (ARNTL2, CLDN1, and SLC6A14) associated with the differential manifestations of UC in Uyghur and Han population were identified, which were potential biomarkers.

Based on Network Pharmacology to Explore the Molecular Targets and Mechanisms of Gegen Qinlian Decoction for the Treatment of Ulcerative Colitis

Background

Gegen Qinlian (GGQL) decoction is a common Chinese herbal compound for the treatment of ulcerative colitis (UC). In this study, we aimed to identify its molecular target and the mechanism involved in UC treatment by network pharmacology and molecular docking. Material and Methods. The active ingredients of Puerariae, Scutellariae, Coptis, and Glycyrrhiza were screened using the TCMSP platform with drug‐like properties (DL) ≥ 0.18 and oral availability (OB) ≥ 30%. To find the intersection genes and construct the TCM compound-disease regulatory network, the molecular targets were determined in the UniProt database and then compared with the UC disease differential genes with P value < 0.005 and ∣log2 (fold change) | >1 obtained in the GEO database. The intersection genes were subjected to protein-protein interaction (PPI) construction and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. After screening the key active ingredients and target genes, the AutoDock software was used for molecular docking, and the best binding target was selected for molecular docking to verify the binding activity.

Results

A total of 146 active compounds were screened, and quercetin, kaempferol, wogonin, and stigmasterol were identified as the active ingredients with the highest associated targets, and NOS2, PPARG, and MMP1 were the targets associated with the maximum number of active ingredients. Through topological analysis, 32 strongly associated proteins were found, of which EGFR, PPARG, ESR1, HSP90AA1, MYC, HSPA5, AR, AKT1, and RELA were predicted targets of the traditional Chinese medicine, and PPARG was also an intersection gene. It was speculated that these targets were the key to the use of GGQL in UC treatment. GO enrichment results showed significant enrichment of biological processes, such as oxygen levels, leukocyte migration, collagen metabolic processes, and nutritional coping. KEGG enrichment showed that genes were particularly enriched in the IL-17 signaling pathway, AGE-RAGE signaling pathway, toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, transcriptional deregulation in cancer, and other pathways. Molecular docking results showed that key components in GGQL had good potential to bind to the target genes MMP3, IL1B, NOS2, HMOX1, PPARG, and PLAU.

Conclusion

GGQL may play a role in the treatment of ulcerative colitis by anti-inflammation, antioxidation, and inhibition of cancer gene transcription.

Interactions between tumor mutation burden and immune infiltration in ovarian cancer

The aim of the study was to evaluate the relationship between tumor mutational burden (TMB) and immune infiltration in ovarian cancer. We extracted somatic mutational data and gene expression profiles of ovarian cancer from The Cancer Genome Atlas (TCGA). The samples were separated into low and high TMB groups. Correlations between TMB and cancer prognosis were analyzed and immune cell infiltration in the high and low TMB subgroups was calculated using the CIBERSORT package software. High TMB was significantly related to an improved survival rate. We identified 4 TMB-related core genes that were significantly associated with prognosis. Furthermore, mutations in the 4 genes were associated with immune cell infiltration. We also found a high proportion of naive B cells and activated NK cells in the high TMB group, while increased proportions of memory B cells and plasma cells were found in the low TMB group. Overall, our study indicated that patients with a higher TMB level experienced a favorable survival outcome and this may influence immune infiltration in ovarian cancer. Furthermore, the 4 TMB-related core genes were highly correlated with prognosis and the level of immune cell infiltration.