Identification of Immune-Related Gene Signature and Prediction of CeRNA Network in Active Ulcerative Colitis

Investigating Overlapping Immune-related Genetic Markers in Cholangiocarcinoma and Inflammatory Bowel Disease for Predictive Prognosis

This study aims to explore the common immune-related gene characteristics of cholangiocarcinoma (CHOL) and inflammatory bowel disease (IBD) to predict disease prognosis. By analyzing the gene expression data from the TCGA, GEO, and NGDC databases, differentially expressed immune-related genes (DE-IRGs) were screened, and a prognostic model was constructed. The results showed that CCR7, OSM, S100P, ACVR1C, OSMR, SPP1, and PIK3R3 were key immune-related genes, and their expressions were closely related to the occurrence and development of CHOL and IBD. Patients in the low immune risk score (IRS) group had more abundant antitumor immune cell infiltration, while those in the high IRS group had more macrophage infiltration. In addition, the model based on these genes had good predictive ability for the diagnosis and prognosis of CHOL and IBD, with an area under the ROC curve (AUC) value exceeding 0.7. This study also predicted potential small molecule drugs that might be effective for the treatment of CHOL, such as Umbralisib and Tamoxifen. In conclusion, this study provides new biomarkers and potential targets for diagnosis, prognosis assessment, and treatment of CHOL and IBD.

Identification and experimental verification of biomarkers related to butyrate metabolism in osteoarthritis

Butyrate plays a crucial role in osteoarthritis (OA) development. However, the relationship between butyrate metabolism-related genes (BMRGs) and OA remains unclear. This study investigates the potential correlation between BMRGs and OA using OA-related datasets (GSE55235, GSE12021 and GSE143514). Differential expression analysis identified 38 differentially expressed butyrate metabolism-related genes (DE-BMRGs) from the overlap of 782 OA-related differentially expressed genes (DEGs) and 385 BMRGs in GSE55235. Enrichment analysis indicated that these DE-BMRGs were tightly associated with cell proliferation, differentiation, and apoptosis, which are key processes in OA pathogenesis. Six candidate biomarkers (IL1B, IGF1, CXCL8, PTGS2, SERPINE1, MMP9) were identified through two machine-learning algorithms. IL1B, CXCL8, and PTGS2 were upregulated in controls, exhibiting consistent patterns across validation datasets. Gene set enrichment analysis (GSEA) revealed that dysregulated expression of these biomarkers lead to abnormal cell proliferation and differentiation, contributing to OA progression. Furthermore, significant differences in immune cell infiltration-particularly activated and resting mast cells-along with correlations to immune regulatory factors (CD86, CXCL12, TNFSF9, IL6), highlighted potential therapeutic targets. Quantitative RT-PCR further confirmed elevated expression of IL1B, CXCL8 and PTGS2 in control group. This study identifies IL1B, CXCL8 and PTGS2 as OA-related biomarkers linked to butyrate metabolism, offering a theoretical foundation and potential therapeutic strategies.

Prognostic Value of Ferroptosis-Immunity-Related Signature Genes in Cervical Cancer Radiotherapy Resistance and Risk Modeling

Introduction

The aim of this study was to clarify the genome of ferroptosis in the genes involved in radiotherapy resistance and regulation of tumor immune microenvironment by multigene analysis of cervical cancer (CC) patients.

Methods

Different radiation sensitivity samples from CC patients were collected for RNA sequencing. Differentially expressed genes (DEGs) between the RNA dataset and the GSE9750 dataset were considered as radiotherapy-DEGs. The intersection genes of radiotherapy-DEGs with ferroptosis-related genes (FRGs) and the intersection genes of radiotherapy-DEGs with immune-related genes (IRGs) were labeled as FRGs-IRGs-DEGs (FIGs). A risk model was established by prognostic genes selected from FIGs by univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis. The results were further validated using samples from CC tissue samples.

Results

The 329 DEGs related to CC radiotherapy were identified. LSAAO analysis was utilized to identify five prognostic genes (CALCRL, UCHL1, GNRH1, ACVRL1, and MUC1) from six candidate prognosis genes and construct a risk model. The risk model demonstrated favorable effectiveness in predicting outcomes at 1, 3, and 5 years, as evidenced by ROC curves. Univariate and multivariate Cox regression analysis demonstrated that CALCRL, GNRH1, and MUC1 were independent prognostic factors. The results of functional similarity analysis showed that CALCRL, UCHL1, ACVRL1 and MUC1 had high average functional similarity. The results of PCR and IHC showed the same trend with the results above.

Discussion

A novel prognostic model related to ferroptosis and immune microenvironment in CC radiotherapy was developed and validated, providing valuable guidance for personalized anti-cancer therapy.

Hsa_circ_0004662 Accelerates the Progression of Ulcerative Colitis via the microRNA-532/HMGB3 Signalling Axis

Increasing research has indicated that circular RNAs (circRNAs) are crucial for the development of ulcerative colitis (UC). Thus, we attempted to identify the role of hsa_circ_0004662 in UC progression. Hsa_circ_0004662 expression was determined via qRT-PCR. Lipopolysaccharide (LPS)-induced inflammation in normal colonic epithelial cells (ECs). The hsa_circ_0004662 content was then assessed in a mucosal inflammatory bowel disease (IBD) model. Cell proliferation was examined via CCK-8 and EdU uptake assays. Apoptotic rates were analysed via flow cytometry. The protein content was quantified via Western blotting. Enzyme-linked immunosorbent assay kits were used to detect IL-1β, TNF-α and IL-6, and dual-luciferase reporter (DLR) assays were used to identify interactions between miR-532 and circ_0004662 or HMGB3. An animal model of UC was also developed for confirmation. In this study, we identified the function of hsa_circ_0004662 in promoting UC progression. Hsa_circ_0004662 was upregulated in clinical UC tissues and LPS-induced colonic ECs, and its knockdown inhibited apoptosis, reduced inflammatory cytokine release and promoted cell proliferation in vitro. Mechanistically, hsa_circ_0004662 acted as a molecular sponge for miR-532, which targets HMGB3. The hsa_circ_0004662/miR-532/HMGB3 axis was further validated in a DSS-induced colitis mouse model, where hsa_circ_0004662 knockdown attenuated inflammation and tissue damage. These findings suggested that hsa_circ_0004662 contributes to UC progression through the miR-532/HMGB3 signalling pathway, offering potential targets for UC therapy.

Molecular insights into ulcerative colitis and orbital inflammation

Ulcerative colitis (UC) is an increasingly prevalent inflammatory condition affecting the intestinal mucosa, while nonspecific orbital inflammation (NSOI) is a common non-neoplastic orbital disorder. Exploring the molecular interplay between UC and NSOI may help physicians make earlier diagnoses and enhance treatment approaches. We analyzed gene expression datasets (GSE58331, GSE105149, GSE206285, and GSE179285) for UC and NSOI from the GEO database. Using WGCNA and differential expression analysis, we identified genes commonly altered in both diseases. GO enrichment, PPI networks, and transcription factor prediction were performed using Cytoscape plugins (cytoHubba and iRegulon). Machine learning techniques were employed to assess transcription factor activity and evaluate potential therapeutic targets among the hub genes. We conducted an association analysis using the TwoSampleMR package in R to explore potential causal relationships between NSOI and UC. A total of 85 intersecting genes between NSOI and UC were identified, and enrichment analyses revealed their roles in immune and inflammatory processes. Key biomarkers, including CXCL10, CXCR4, CXCL9, CD27, SELL, MMP9, CD79A, CD3E, GZMK, and CCL19, were highlighted, linking them to processes such as leukocyte migration, viral response, and monocyte differentiation. STAT1 was identified as a shared transcription factor influencing both diseases. Machine learning algorithms identified eight potential genes for diagnostic and therapeutic use, with CXCL10 emerging as a key player in the pathogenesis of NSOI and UC. CXCL10 likely regulates CXCR4, LCK, CCR7, and other genes involved in pathways such as cytokine-cytokine receptor interactions, HIV-1 infection, and Epstein-Barr virus infection. This study offers insights into the co-pathogenic mechanisms of UC and NSOI, providing a foundation for further mechanistic research and therapeutic development.

Omics Investigations of Prostate Cancer Cells Exposed to Simulated Microgravity Conditions

Prostate cancer (PC) is the most diagnosed cancer in males across the globe. Following the formation of metastasis, PC is linked to a notable decline in both prognosis and survival rates. Three-dimensional multicellular spheroids (MCSs) of a prostate adenocarcinoma cell line were generated in a three-day simulated microgravity environment (s-µg) to serve as a model for metastasis and to derive transcriptional and epigenetic PC candidates from molecular biological changes. With an FDR of 10-3, we detected the most differentially expressed genes in the two comparisons' adherent cells (AD) to MCSs (N = 751 genes) and 1g control cells to MCSs (N = 662 genes). In these two comparisons, genes related to cell cycle, angiogenesis, cell adhesion, and extracellular space were consistently found to be significantly enriched in GO annotations. Furthermore, at a 5% FDR significance level, we were able to identify 11,090 genome-wide differentially methylated positions (DMPs) and one differentially methylated region in the SRMS gene in the 1g vs. AD comparison, as well as an additional 10,797 DMPs in the 1g vs. MCSs comparison. Finally, we identified five s-µg-related positive enrichments of transcription factor binding sites for AR, IRF1, IRF2, STAT1, STAT2, and FOXJ3 close to the DMPs.

Identification and validation of TSPAN13 as a novel temozolomide resistance-related gene prognostic biomarker in glioblastoma

Glioblastoma (GBM) is the most lethal primary tumor of the central nervous system, with its resistance to treatment posing significant challenges. This study aims to develop a comprehensive prognostic model to identify biomarkers associated with temozolomide (TMZ) resistance. We employed a multifaceted approach, combining differential expression and univariate Cox regression analyses to screen for TMZ resistance-related differentially expressed genes (TMZR-RDEGs) in GBM. Using LASSO Cox analysis, we selected 12 TMZR-RDEGs to construct a risk score model, which was evaluated for performance through survival analysis, time-dependent ROC, and stratified analyses. Functional enrichment and mutation analyses were conducted to explore the underlying mechanisms of the risk score and its relationship with immune cell infiltration levels in GBM. The prognostic risk score model, based on the 12 TMZR-RDEGs, demonstrated high efficacy in predicting GBM patient outcomes and emerged as an independent predictive factor. Additionally, we focused on the molecule TSPAN13, whose role in GBM is not well understood. We assessed cell proliferation, migration, and invasion capabilities through in vitro assays (including CCK-8, Edu, wound healing, and transwell assays) and quantitatively analyzed TSPAN13 expression levels in clinical glioma samples using tissue microarray immunohistochemistry. The impact of TSPAN13 on TMZ resistance in GBM cells was validated through in vitro experiments and a mouse orthotopic xenograft model. Notably, TSPAN13 was upregulated in GBM and correlated with poorer patient prognosis. Knockdown of TSPAN13 inhibited GBM cell proliferation, migration, and invasion, and enhanced sensitivity to TMZ treatment. This study provides a valuable prognostic tool for GBM and identifies TSPAN13 as a critical target for therapeutic intervention.

Transcriptomic Insights into the Molecular Mechanisms of Indole Analogues from the Periplaneta americana Extract and Their Therapeutic Effects on Ulcerative Colitis

Ulcerative colitis (UC) is an inflammatory disease of the intestinal mucosa, and its incidence is steadily increasing worldwide. As a traditional Chinese medicinal insect, Periplaneta americana has been broadly utilized in clinical practice to treat wound healing. The tryptophan (Trp), tryptamine (Try), and 1,2,3,4-tetrahydrogen-β-carboline-3-carboxylic acid (Thcc) identified from P. americana concentrated ethanol-extract liquid (PACEL) exhibit significant cell proliferation-promoting and anti-inflammatory effects in the treatment of UC, but the mechanism involved remains obscure. Here, a dextran sulfate sodium (DSS)-induced UC mouse model was used to investigate the efficacy of high/low doses of PACEL, Trp, Try, and Thcc. Transcriptome sequencing was employed to detect the gene expression in the mouse intestine. The results showed that high doses of PACEL, Trp, Try, and Thcc could significantly improve weight loss and diarrhea, notably in the PACEL and Trp groups. Transcriptome analysis indicated that statistically changed genes in four treatment groups were specifically enriched in the immune system. Of these, the integrated analysis identified six hub genes (IL1β, CCL4, CXCL5, CXCR2, LCN2, and MMP9) regulated by NF-κB, which were significantly downregulated. This study investigates the molecular mechanisms underlying the UC treatment properties of indole analogues from PACEL, potentially through the inhibition of the NF-κB signaling pathway.

Insights into lncRNA-mediated regulatory networks in Hevea brasiliensis under anthracnose stress

In recent years, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have emerged as critical regulators in plant biology, governing complex gene regulatory networks. In the context of disease resistance in Hevea brasiliensis, the rubber tree, significant progress has been made in understanding its response to anthracnose disease, a serious threat posed by fungal pathogens impacting global rubber tree cultivation and latex quality. While advances have been achieved in unraveling the genetic and molecular foundations underlying anthracnose resistance, gaps persist in comprehending the regulatory roles of lncRNAs and miRNAs under such stress conditions. The specific contributions of these non-coding RNAs in orchestrating molecular responses against anthracnose in H. brasiliensis remain unclear, necessitating further exploration to uncover strategies that increase disease resistance. Here, we integrate lncRNA sequencing, miRNA sequencing, and degradome sequencing to decipher the regulatory landscape of lncRNAs and miRNAs in H. brasiliensis under anthracnose stress. We investigated the genomic and regulatory profiles of differentially expressed lncRNAs (DE-lncRNAs) and constructed a competitive endogenous RNA (ceRNA) regulatory network in response to pathogenic infection. Additionally, we elucidated the functional roles of HblncRNA29219 and its antisense hbr-miR482a, as well as the miR390-TAS3-ARF pathway, in enhancing anthracnose resistance. These findings provide valuable insights into plant-microbe interactions and hold promising implications for advancing agricultural crop protection strategies. This comprehensive analysis sheds light on non-coding RNA-mediated regulatory mechanisms in H. brasiliensis under pathogen stress, establishing a foundation for innovative approaches aimed at enhancing crop resilience and sustainability in agriculture.

Utilizing an integrated bioinformatics and machine learning approach to uncover biomarkers linking ulcerative colitis to purine metabolism-related genes

Background

Ulcerative colitis (UC) is an increasing incidence of inflammatory disorder in the colon mucosa. One of the current research focuses is the alteration of metabolic networks in UC. One of the important aspects of this metabolic shift is the expression of purine metabolism genes (PMGs) vital for nucleic acid synthesis. Nevertheless, the precise function of PMGs in the pathophysiology of UC is not yet fully known.

Methods

To this end, this study used state-of-the-art bioinformatics tools and approaches to discover and confirm the PMGs involved in UC. All the 114 candidate PMGs were compared for their expression levels. GSEA and GSVA were applied to define the functional and pathway implications of these PMGs. Lasso regression and SVM-RFE approaches were used for the identification of hub genes and to assess the diagnostic potential of eight PMGs in UC classification. The relationship between these critical PMGs and clinical features was also systematically evaluated as well. The expression levels of these eight PMGs were validated using datasets GSE206285 and GSE179285.

Results

Using bioinformatics and machine learning, this work seeks to establish the involvement of PMGs in UC. From the LASSO and SVM models, 114 DE PMGs were selected and investigated to build a stable predictive model. Based on these studies, the following genes: IMPDH1, GUK1, POLE3, ADCY3, ADCY4, PDE6B, PNPT1 and PDE4D were suggested as potential biomarkers of UC. Gene ontology enrichment analysis revealed that these genes are implicated in the biological processes of particular relevance to immune and inflammatory responses. The study also provided a lot of information on the interaction between immune cells and PMGs indicating that these genes may control some immune-related pathways in UC. Moreover, drug-gene interaction analysis presents potential therapeutic opportunities for potential drug targets which were further confirmed through molecular docking. Mendelian randomization analysis revealed that ADCY4 and PDAZN are involved in PMG-related processes, thus opening new possibilities for treatment.

Conclusions

This work reveals eight PMGs closely related to UC and provides new perspectives on possible markers of this inflammatory disease. These findings not only increase the understanding of the pathogenesis of UC but also offer potential for improving the surveillance of disease and its progression.

EXPLORING THE PROGNOSTIC NECROPTOSIS-RELATED GENES AND UNDERLYING MECHANISM IN SEPSIS USING BIOINFORMATICS

ABSTRACT

Sepsis is a life-threatening disease due to a dysregulated host response to infection, with an unknown regulatory mechanism for prognostic necroptosis-related genes (NRGs). Using GEO datasets GSE65682 and GSE134347, we identified six NRG biomarkers ( ATRX , TSC1 , CD40 , BACH2 , BCL2 , and LEF1 ) with survival and diagnostic significance through Kaplan-Meier (KM) and receiver operating characteristic (ROC) analyses. Afterward, the ingenuity pathway analysis (IPA) highlighted enrichment in hepatic fibrosis pathways and BEX2 protein. Moreover, we examined their regulatory targets and functional links with necroptotic signaling molecules via miRDB, TargetScan, Network analyst, and GeneMANIA. The molecular regulatory network displayed that hsa-miR-5195-3p and hsa-miR-145-5p regulated ATRX, BACH2, and CD40, while YY1 showed strong connectivity, concurrently controlling LEF1, ATRX, BCL2, BACH2, and CD40. CD40 exhibited similar expression patterns to RIPK3 and MLKL, and LEF1 was functionally associated with MLKL. Additionally, DrugBank analysis identified paclitaxel, docetaxel, and rasagiline as potential BCL2-targeting sepsis treatments. Finally, real-time quantitative PCR confirmed ATRX, TSC1, and LEF1 downregulation in sepsis samples, contrasting CD40's increased expression in CTL samples. In conclusion, ATRX , TSC1 , CD40 , BACH2 , BCL2 , and LEF1 may be critical regulatory targets of necroptosis in sepsis, providing a basis for further necroptosis-related studies in sepsis.

Employing a synergistic bioinformatics and machine learning framework to elucidate biomarkers associating asthma with pyrimidine metabolism genes

BACKGROUND

Asthma, a prevalent chronic inflammatory disorder, is shaped by a multifaceted interplay between genetic susceptibilities and environmental exposures. Despite strides in deciphering its pathophysiological landscape, the intricate molecular underpinnings of asthma remain elusive. The focus has increasingly shifted toward the metabolic aberrations accompanying asthma, particularly within the domain of pyrimidine metabolism (PyM)-a critical pathway in nucleotide synthesis and degradation. While the therapeutic relevance of PyM has been recognized across various diseases, its specific contributions to asthma pathology are yet underexplored. This study employs sophisticated bioinformatics approaches to delineate and confirm the involvement of PyM genes (PyMGs) in asthma, aiming to bridge this significant gap in knowledge.

METHODS

Employing cutting-edge bioinformatics techniques, this research aimed to elucidate the role of PyMGs in asthma. We conducted a detailed examination of 31 PyMGs to assess their differential expression. Through Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), we explored the biological functions and pathways linked to these genes. We utilized Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) to pinpoint critical hub genes and to ascertain the diagnostic accuracy of eight PyMGs in distinguishing asthma, complemented by an extensive correlation study with the clinical features of the disease. Validation of the gene expressions was performed using datasets GSE76262 and GSE147878.

RESULTS

Our analyses revealed that eleven PyMGs-DHODH, UMPS, NME7, NME1, POLR2B, POLR3B, POLR1C, POLE, ENPP3, RRM2B, TK2-are significantly associated with asthma. These genes play crucial roles in essential biological processes such as RNA splicing, anatomical structure maintenance, and metabolic processes involving purine compounds.

CONCLUSIONS

This investigation identifies eleven PyMGs at the core of asthma's pathogenesis, establishing them as potential biomarkers for this disease. Our findings enhance the understanding of asthma's molecular mechanisms and open new avenues for improving diagnostics, monitoring, and progression evaluation. By providing new insights into non-cancerous pathologies, our work introduces a novel perspective and sets the stage for further studies in this field.

Genomic insights into pediatric intestinal inflammatory and eosinophilic disorders using single-cell RNA-sequencing

Introduction

Chronic inflammation of the gastrointestinal tissues underlies gastrointestinal inflammatory disorders, leading to tissue damage and a constellation of painful and debilitating symptoms. These disorders include inflammatory bowel diseases (Crohn's disease and ulcerative colitis), and eosinophilic disorders (eosinophilic esophagitis and eosinophilic duodenitis). Gastrointestinal inflammatory disorders can often present with overlapping symptoms necessitating the use of invasive procedures to give an accurate diagnosis.

Methods

This study used peripheral blood mononuclear cells from individuals with Crohn's disease, ulcerative colitis, eosinophilic esophagitis, and eosinophilic duodenitis to better understand the alterations to the transcriptome of individuals with these diseases and identify potential markers of active inflammation within the peripheral blood of patients that may be useful in diagnosis. Single-cell RNA-sequencing was performed on peripheral blood mononuclear cells isolated from the blood samples of pediatric patients diagnosed with gastrointestinal disorders, including Crohn's disease, ulcerative colitis, eosinophilic esophagitis, eosinophilic duodenitis, and controls with histologically healthy gastrointestinal tracts.

Results

We identified 730 (FDR < 0.05) differentially expressed genes between individuals with gastrointestinal disorders and controls across eight immune cell types.

Discussion

There were common patterns among GI disorders, such as the widespread upregulation of MTRNR2L8 across cell types, and many differentially expressed genes showed distinct patterns of dysregulation among the different gastrointestinal diseases compared to controls, including upregulation of XIST across cell types among individuals with ulcerative colitis and upregulation of Th2-associated genes in eosinophilic disorders. These findings indicate both overlapping and distinct alterations to the transcriptome of individuals with gastrointestinal disorders compared to controls, which provide insight as to which genes may be useful as markers for disease in the peripheral blood of patients.

MiRNAs: a new target for Chinese medicine to repair the intestinal barrier in the treatment of ulcerative colitis

Ulcerative colitis (UC) is a chronic nonspecific inflammatory bowel disease whose pathogenesis remains unclear. Dysfunction of the intestinal mucosal barrier is closely related to the pathogenesis of UC, which is characterised by damage to the colon epithelial barrier, disruption of immune homeostasis, and persistent inflammatory cell infiltration. MicroRNAs (miRNAs) exhibit specific or differential expression in both UC animal models and patients, implicating their involvement in the pathogenesis of UC. In recent years there has been progress in using Traditional Chinese medicine (TCM) to regulate miRNA expression for repairing the intestinal mucosal barrier in UC, as demonstrated in animal and cell experiments. However, it has not been applied in a clinical setting and its underlying molecular mechanisms require further investigation. Therefore, this study systematically described the role of miRNAs in UC-induced intestinal barrier damage and the application of TCM to repair this intestinal barrier by regulating miRNA expression, offering new therapeutic targets for UC treatment.

Evaluating the significance of ECSCR in the diagnosis of ulcerative colitis and drug efficacy assessment

Background

The main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms.

Methods

In this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples.

Results

RRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting with key UC genes in WGCNA, yielding 212 key DEGs. Subsequently, five UC signature biomarkers were identified by machine learning based on the key DEGs-THY1, SLC6A14, ECSCR, FAP, and GPR109B. A logistic regression model incorporating these five genes was constructed. The AUC values for the model set and internal validation data were 0.995 and 0.959, respectively. Mechanistically, activation of the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers. Additionally, the expression of the signature biomarkers was strongly correlated with various UC types and drug efficacy in different datasets. Notably, ECSCR was found to be upregulated in UC serum and exhibited a positive correlation with neutrophil levels in UC patients.

Conclusions

THY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC.

Exploring the Molecular Mechanism of Schisandrin C for the Treatment of Atherosclerosis via the PI3K/AKT/mTOR Autophagy Pathway

Atherosclerosis (AS) is a common cardiovascular disease that poses a major threat to health. Schisandra chinensis is a medicinal and edible plant that is commonly used to treat cardiovascular diseases. In this paper, HPLC was used to detect and analyze 5 different components in Schisandra chinensis. Network pharmacological predictions highlight the PI3K/AKT/mTOR pathway as an important pharmacological pathway. The effective ingredient Schisandrin C was screened by the molecular docking technique. ox-LDL-induced HUVECs were used to construct the atherosclerosis model for further experimental verification. The results showed that Schisandrin C interfered with the PI3K/AKT/mTOR autophagy pathway. This study lays a foundation for the further application of Schisandrin C in the prevention and treatment of atherosclerosis in the future.

Kuicolong-yu enema decoction retains traditional Chinese medicine enema attenuates inflammatory response ulcerative colitis through TLR4/NF-κB signaling pathway

BACKGROUND

Ulcer colitis (UC) is a chronic, nonspecific, and noninfectious inflammatory bowel disease. Recently, Toll-like receptors (TLRs) have been found to be closely associated with clinical inflammatory diseases. Achieving complete remission in patients with intermittent periods of activity followed by dormancy is challenging. Moreover, no study has explored the mechanism by which Kuicolong-yu enema decoction retains traditional Chinese medicine enemas to attenuate the inflammatory response in UC.

AIM

To explore the mechanism by which Kuicolong-yu enema decoction retains traditional Chinese medicine enemas to attenuate the inflammatory response in UC.

METHODS

This prospective clinical study included patients who met the exclusion criteria in 2020 and 2021. The patients with UC were divided into two groups (control and experimental). The peripheral blood of the experimental and control groups were collected under aseptic conditions. The expression of TLR4 protein, NF-κB, IL-6, and IL-17 was detected in the peripheral blood of patients in the experimental group and control group before and 1 month after taking the drug. Linear correlation analysis was used to analyze the relationship between the expression level of TLR4 protein and the expression levels of downstream signal NF-κB and inflammatory factors IL-6 and IL-17, and P < 0.05 was considered statistically significant.

RESULTS

There were no significant differences in the patient characteristics between the control and experimental groups. The results showed that the expression levels of TLR4 and NF-κB in the experimental group were significantly lower than those in the control group (P < 0.05). The levels of IL-6 and IL-17 in the experimental group were significantly lower than those in the control group (P < 0.05). The TLR4 protein expression in the experimental group was positively correlated with the expression level of downstream signal NF-κB and was positively correlated with the levels of downstream inflammatory cytokines IL-6 and IL-17 (r = 0.823, P < 0.05).

CONCLUSION

Kuicolong-yu enema decoction retains traditional Chinese medicine enema attenuates the inflammatory response of UC through the TLR4/NF-κB signaling pathway.

Expression profiles and gene set enrichment analysis of the transcriptomes from the cancer tissue, white adipose tissue and paracancer tissue with colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common cancers worldwide and is related to diet and obesity. Currently, crosstalk between lipid metabolism and CRC has been reported; however, the specific mechanism is not yet understood. In this study, we screened differentially expressed long non-coding RNAs (lncRNAs) and mRNAs from primary cancer, paracancer, and white adipose tissue of CRC patients. We screened and analyzed the genes differentially expressed between primary and paracancer tissue and between paracancer and white adipose tissue but not between primary and white adipose tissue. According to the results of the biological analysis, we speculated a lncRNA (MIR503HG) that may be involved in the crosstalk between CRC and lipid metabolism through exosome delivery.

Methods

We screened differentially expressed long non-coding RNAs (lncRNAs) and mRNAs from primary cancer, paracancer, and white adipose tissue of CRC patients. We screened and analyzed the genes differentially expressed between primary and paracancer tissue and between paracancer and white adipose tissue but not between primary and white adipose tissue.

Results

We speculated a lncRNA (MIR503HG) that may be involved in the crosstalk between CRC and lipid metabolism through exosome delivery.

Conclusions

In this study, the findings raise the possibility of crosstalk between lipid metabolism and CRC through the exosomal delivery of lncRNAs.

Construction of the underlying circRNA-miRNA-mRNA regulatory network and a new diagnostic model in ulcerative colitis by bioinformatics analysis

BACKGROUND

Circular RNAs (circRNAs) are involved in the pathogenesis of many diseases through competing endogenous RNA (ceRNA) regulatory mechanisms.

AIM

To investigate a circRNA-related ceRNA regulatory network and a new predictive model by circRNA to understand the diagnostic mechanism of circRNAs in ulcerative colitis (UC).

METHODS

We obtained gene expression profiles of circRNAs, miRNAs, and mRNAs in UC from the Gene Expression Omnibus dataset. The circRNA-miRNA-mRNA network was constructed based on circRNA-miRNA and miRNA-mRNA interactions. Functional enrichment analysis was performed to identify the biological mechanisms involved in circRNAs. We identified the most relevant differential circRNAs for diagnosing UC and constructed a new predictive nomogram, whose efficacy was tested with the C-index, receiver operating characteristic curve (ROC), and decision curve analysis (DCA).

RESULTS

A circRNA-miRNA-mRNA regulatory network was obtained, containing 12 circRNAs, three miRNAs, and 38 mRNAs. Two optimal prognostic-related differentially expressed circRNAs, hsa_circ_0085323 and hsa_circ_0036906, were included to construct a predictive nomogram. The model showed good discrimination, with a C-index of 1(> 0.9, high accuracy). ROC and DCA suggested that the nomogram had a beneficial diagnostic ability.

CONCLUSION

This novel predictive nomogram incorporating hsa_circ_0085323 and hsa_circ_0036906 can be conveniently used to predict the risk of UC. The circRNa-miRNA-mRNA network in UC could be more clinically significant.

Elucidating the role of TWIST1 in ulcerative colitis: a comprehensive bioinformatics and machine learning approach

Background: Ulcerative colitis (UC) is a common and progressive inflammatory bowel disease primarily affecting the colon and rectum. Prolonged inflammation can lead to colitis-associated colorectal cancer (CAC). While the exact cause of UC remains unknown, this study aims to investigate the role of the TWIST1 gene in UC. Methods: Second-generation sequencing data from adult UC patients were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and characteristic genes were selected using machine learning and Lasso regression. The Receiver Operating Characteristic (ROC) curve assessed TWIST1's potential as a diagnostic factor (AUC score). Enriched pathways were analyzed, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). Functional mechanisms of marker genes were predicted, considering immune cell infiltration and the competing endogenous RNA (ceRNA) network. Results: We found 530 DEGs, with 341 upregulated and 189 downregulated genes. TWIST1 emerged as one of four potential UC biomarkers via machine learning. TWIST1 expression significantly differed in two datasets, GSE193677 and GSE83687, suggesting its diagnostic potential (AUC = 0.717 in GSE193677, AUC = 0.897 in GSE83687). Enrichment analysis indicated DEGs associated with TWIST1 were involved in processes like leukocyte migration, humoral immune response, and cell chemotaxis. Immune cell infiltration analysis revealed higher rates of M0 macrophages and resting NK cells in the high TWIST1 expression group, while TWIST1 expression correlated positively with M2 macrophages and resting NK cell infiltration. We constructed a ceRNA regulatory network involving 1 mRNA, 7 miRNAs, and 32 long non-coding RNAs (lncRNAs) to explore TWIST1's regulatory mechanism. Conclusion: TWIST1 plays a significant role in UC and has potential as a diagnostic marker. This study sheds light on UC's molecular mechanisms and underscores TWIST1's importance in its progression. Further research is needed to validate these findings in diverse populations and investigate TWIST1 as a therapeutic target in UC.

RNA sequencing reveals differential long noncoding RNA expression profiles in bacterial and viral meningitis in children

BACKGROUND

We aimed to investigate the involvement of long non-coding RNA (lncRNA) in bacterial and viral meningitis in children.

METHODS

The peripheral blood of five bacterial meningitis patients, five viral meningitis samples, and five healthy individuals were collected for RNA sequencing. Then, the differentially expressed lncRNA and mRNA were detected in bacterial meningitis vs. controls, viral meningitis vs. healthy samples, and bacterial vs. viral meningitis patients. Besides, co-expression and the competing endogenous RNA (ceRNA) networks were constructed. Receiver operating characteristic curve (ROC) analysis was performed.

RESULTS

Compared with the control group, 2 lncRNAs and 32 mRNAs were identified in bacterial meningitis patients, and 115 lncRNAs and 54 mRNAs were detected in viral meningitis. Compared with bacterial meningitis, 165 lncRNAs and 765 mRNAs were identified in viral meningitis. 2 lncRNAs and 31 mRNAs were specific to bacterial meningitis, and 115 lncRNAs and 53 mRNAs were specific to viral meningitis. The function enrichment results indicated that these mRNAs were involved in innate immune response, inflammatory response, and immune system process. A total of 8 and 1401 co-expression relationships were respectively found in bacterial and viral meningitis groups. The ceRNA networks contained 1 lncRNA-mRNA pair and 4 miRNA-mRNA pairs in viral meningitis group. GPR68 and KIF5C, identified in bacterial meningitis co-expression analysis, had an area under the curve (AUC) of 1.00, while the AUC of OR52K2 and CCR5 is 0.883 and 0.698, respectively.

CONCLUSIONS

Our research is the first to profile the lncRNAs in bacterial and viral meningitis in children and may provide new insight into understanding meningitis regulatory mechanisms.

Comprehensive Analysis of PANoptosis-Related Gene Signature of Ulcerative Colitis

Accumulating evidence shows that the abnormal increase in the mortality of intestinal epithelial cells (IECs) caused by apoptosis, pyroptosis, and necroptosis is closely related to the function of mucous membrane immunity and barrier function in patients with ulcerative colitis (UC). As a procedural death path that integrates the above-mentioned many deaths, the role of PANoptosis in UC has not been clarified. This study aims to explore the characterization of PANoptosis patterns and determine the potential biomarkers and therapeutic targets. We constructed a PANoptosis gene set and revealed significant activation of PANoptosis in UC patients based on multiple transcriptome profiles of intestinal mucosal biopsies from the GEO database. Comprehensive bioinformatics analysis revealed five key genes (ZBP1, AIM2, CASP1/8, IRF1) of PANoptosome with good diagnostic value and were highly correlated with an increase in pro-inflammatory immune cells and factors. In addition, we established a reliable ceRNA regulatory network of PANoptosis and predicted three potential small-molecule drugs sharing calcium channel blockers that were identified, among which flunarizine exhibited the highest correlation with a high binding affinity to the targets. Finally, we used the DSS-induced colitis model to validate our findings. This study identifies key genes of PANoptosis associated with UC development and hypothesizes that IRF1 as a TF promotes PANoptosome multicomponent expression, activates PANoptosis, and then induces IECs excessive death.

Epigenetic regulation and therapeutic strategies in ulcerative colitis

Ulcerative colitis (UC) is an inflammatory bowel disease, and is characterized by the diffuse inflammation and ulceration in the colon and rectum mucosa, even extending to the caecum. Epigenetic modifications, including DNA methylations, histone modifications and non-coding RNAs, are implicated in the differentiation, maturation, and functional modulation of multiple immune and non-immune cell types, and are influenced and altered in various chronic inflammatory diseases, including UC. Here we review the relevant studies revealing the differential epigenetic features in UC, and summarize the current knowledge about the immunopathogenesis of UC through epigenetic regulation and inflammatory signaling networks, regarding DNA methylation, histone modification, miRNAs and lncRNAs. We also discuss the epigenetic-associated therapeutic strategies for the alleviation and treatment of UC, which will provide insights to intervene in the immunopathological process of UC in view of epigenetic regulation.

Identification of Immune-Related Genes as Biomarkers for Uremia

Purpose

Uremia, which is characterized by immunodeficiency, is associated with the deterioration of kidney function. Immune-related genes (IRGs) are crucial for uremia progression.

Methods

The co-expression network was constructed to identify key modular genes associated with uremia. IRGs were intersected with differentially expressed genes (DEGs) between uremia and control groups and key modular genes to obtain differentially expressed IRGs (DEIRGs). DEIRGs were subjected to functional enrichment analysis. The protein-protein interaction (PPI) network was constructed. The candidate genes were identified using the cytoHubba tool. The biomarkers were identified using various machine learning algorithms. The diagnostic value of the biomarkers was evaluated using receiver operating characteristic (ROC) analysis. The immune infiltration analysis was implemented. The biological pathways of biomarkers were identified using gene set enrichment analysis and ingenuity pathway analysis. The mRNA expression of biomarkers was validated using blood samples of patients with uremia and healthy subjects with quantitative real-time polymerase chain reaction (qRT-PCR).

Results

In total, four biomarkers (PDCD1, NGF, PDGFRB, and ZAP70) were identified by machine learning methods. ROC analysis demonstrated that the area under the curve values of individual biomarkers were > 0.9, indicating good diagnostic power. The nomogram model of biomarkers exhibited good predictive power. The proportions of six immune cells significantly varied between the uremia and control groups. ZAP70 expression was positively correlated with the proportions of resting natural killer (NK) cells, naïve B cells, and regulatory T cells. Functional enrichment analysis revealed that the biomarkers were mainly associated with translational function and neuroactive ligand-receptor interaction. ZAP70 regulated NK cell signaling. The PDCD1 and NGF expression levels determined using qRT-PCR were consistent with those determined using bioinformatics analysis.

Conclusion

PDCD1, NGF, PDGFRB, and ZAP70 were identified as biomarkers for uremia, providing a theoretical foundation for uremia diagnosis.

Inhibition of UFM1 expression suppresses cancer progression and is linked to the dismal prognosis and immune infiltration in oral squamous cell carcinoma

BACKGROUND

Ubiquitin fold modifier 1 (UFM1) overexpression is associated with cancer cell proliferation, migration and invasion. However, the roles and pathways of UFM1 in oral squamous cell carcinoma (OSCC) has remained undefined.

METHODS

The expression of UFM1 and the relationship between UFM1 expression and prognosis were investigated using data of OSCC patients from The Cancer Genome Atlas (TCGA) database. The UFM1 co-expressed genes, and the association between the UFM1 expression and immune cells and ubiquitination were explored. The effects of UFM1 expression on the growth and migration of OSCC cells were investigated by siRNA interference, Cell Counting Kit-8 (CCK-8), Transwell, Western blotting, and wound healing experiments.

RESULTS

UFM1 was highly expressed in OSCC. UFM1 overexpression was associated with short overall survival, disease-specific survival, and progression-free interval, and was an adverse factor for prognosis in OSCC. UFM1-related nomograms were significantly associated with poor prognosis in OSCC patients. Decreased UFM1 expression could inhibit the proliferation, migration, and invasion of OSCC cells. UFM1 was associated with the immune cells (such as the Th17 cells, T helper cells, and cytotoxic cells) and ubiquitination.

CONCLUSION

Elevated UFM1 expression was associated with poor prognosis, ubiquitination and immune infiltration in OSCC, and inhibition of UFM1 expression delayed OSCC progression, showing that UFM1 could be a biomarker for prognosis and treating OSCC patients.

SKIL/SnoN attenuates TGF-β1/SMAD signaling-dependent collagen synthesis in hepatic fibrosis

The ski-related novel gene (SnoN), encoded by the SKIL gene, has been shown to negatively regulated transforming growth factor-β1 (TGF-β1) signaling pathway. However, the roles of SnoN in hepatic stellate cell (HSC) activation and hepatic fibrosis (HF) are still unclear. To evaluate the role of SnoN in HF, we combined bulk RNA sequencing analysis and single-cell RNA sequencing analysis to analyse patients with HF. The role of SKIL/SnoN was verified using liver samples from rat model transfected HSC-T6 and LX-2 cell lines. Immunohistochemistry, immunofluorescence, PCR, and western blotting techniques were used to demonstrate the expression of SnoN and its regulatory effects on TGF-β1 signaling in fibrotic liver tissues and cells. Furthermore, we constructed competitive endogenous RNA regulatory network and potential drug network associated with the SnoN gene. We identified SKIL gene as a differentially expressed gene in hepatic fibrosis. SnoN protein was found to be widely expressed in the cytoplasm of normal hepatic tissues, whereas it was almost absent in HF tissues. In the rat group subjected to bile duct ligation (BDL), SnoN protein expression decreased, while TGF-β1, collagen III, tissue inhibitor of metalloproteinase 1 (TIMP-1), and fibronectin levels increased. We observed the interaction of SnoN with p-SMAD2 and p-SMAD3 in the cytoplasm. Following SnoN overexpression, apoptosis of HSCs was promoted, and the expression of HF-associated proteins, including collagen I, collagen III, and TIMP-1, was reduced. Conversely, downregulation of SnoN inhibited HSC apoptosis, increased collagen III and TIMP-1 levels, and decreased matrix metalloproteinase 13 (MMP-13) expression. In conclusion, SnoN expression is downregulated in fibrotic livers, and could attenuate TGF-β1/SMADs signaling-dependent de-repression of collagen synthesis.

Identifying Macrophage-Related Genes in Ulcerative Colitis Using Weighted Coexpression Network Analysis and Machine Learning

Ulcerative colitis (UC) is an inflammatory bowel disease of unknown cause that typically affects the colon and rectum. Innate intestinal immunity, including macrophages, plays a significant role in the pathological development of UC. Using the CIBERSORT algorithm, we observed elevated levels of 22 types of immune cell infiltrates, as well as increased M1 and decreased M2 macrophages in UC compared to normal colonic mucosa. Weighted gene coexpression network analysis (WGCNA) was used to identify modules associated with macrophages and UC, resulting in the identification of 52 macrophage-related genes (MRGs) that were enriched in macrophages at single-cell resolution. Consensus clustering based on these 52 MRGs divided the integrated UC cohorts into three subtypes. Machine learning algorithms were used to identify ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), sodium- and chloride-dependent neutral and basic amino acid transporter B(0+) (SLC6A14), and 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) in the training set, and their diagnostic value was validated in independent validation sets. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) revealed the main biological effects, and that interleukin-17 was one of several signaling pathways enriched by the three genes. We also constructed a competitive endogenous RNA (CeRNA) network reflecting a potential posttranscriptional regulatory mechanism. Expression of diagnostic markers was validated in vivo and in biospecimens, and our immunohistochemistry (IHC) results confirmed that HMGCS2 gradually decreased during the transformation of UC to colorectal cancer. In conclusion, ENPP1, SLC6A14, and HMGCS2 are associated with macrophages and the progression of UC pathogenesis and have good diagnostic value for patients with UC.

Biomarkers of ulcerative colitis disease activity CXCL1, CYP2R1, LPCAT1, and NEU4 and their relationship to immune infiltrates

The diagnosis and assessment of ulcerative colitis (UC) poses significant challenges, which may result in inadequate treatment and a poor prognosis for patients. This study aims to identify potential activity biomarkers for UC and investigate the role of infiltrating immune cells in the disease. To perform gene set enrichment analysis, we utilized the cluster profiler and ggplot2 packages. Kyoto encyclopedia of genes and genomes was used to analyze degenerate enrichment genes. Significant gene set enrichment was determined using the cluster profiler and ggplot2 packages. Additionally, quantitative PCR (qRT-PCR) was employed to validate the expression of each marker in the ulcerative colitis model. We identified 651 differentially expressed genes (DEGs) and further investigated potential UC activity biomarkers. Our analysis revealed that CXCL1 (AUC = 0.710), CYP2R1 (AUC = 0.863), LPCAT1 (AUC = 0.783), and NEU4 (AUC = 0.833) were promising activity markers for the diagnosis of UC. Using rat DSS model, we validated these markers through qRT-PCR, which showed statistically significant differences between UC and normal colon mucosa. Infiltrating immune cell analysis indicated that M1 macrophages, M2 macrophages, activated dendritic cells (DCs), and neutrophils played crucial roles in the occurrence and progression of UC. Moreover, the activity markers exhibited varying degrees of correlation with activated memory CD4 T cells, M0 macrophages, T follicular helper cells, memory B cells, and activated DCs. The potential diagnostic genes for UC activity, such as CXCL1, CYP2R1, LPCAT1, and NEU4, as well as the infiltration of immune cells, may contribute to the pathogenesis and progression of UC.

Prediction and Verification of Potential Therapeutic Targets for Non-Responders to Infliximab in Ulcerative Colitis

Background

Infliximab (IFX) has been widely used in ulcerative colitis (UC) patients. However, the subsequent effective treatment of IFX non-response in UC patients remains a challenge. This study aims to predict potential therapeutic targets for non-responders by performing a bioinformatic analysis of the data in the Gene Expression Omnibus (GEO) database and validation by biopsies.

Methods

Colonic mucosal biopsies expression profiles of IFX-treated UC patients (GSE73661, GSE16879) were utilized to predict potential therapeutic targets. Bioinformatics analyses were used to explore potential biological mechanisms. CytoHubba was performed to screen hub genes. We used a validation dataset and colonic mucosal biopsies of UC patients to validate hub genes.

Results

A total of 147 DEGs were identified (119 upregulated genes and 28 downregulated genes). GSEA showed that DEGs in GSE73661 were enriched in the pathways of the cytokine-cytokine receptor, the chemokine, and the adhesion molecules system. Based on the PPI network analysis, we identified four hub genes (and the transcription factor NF-κB). Then, we validate the expression of hub genes by reverse transcription-polymerase chain reaction (RT-PCR). We found higher expression of IL-6, IL1B, CXCL8, and CCL2 in non-responders compared to responders.

Conclusion

In summary, four potential targets (IL-6, IL1B, CXCL8, and CCL2) were finally identified by performing a bioinformatics analysis of the datasets in the GEO database. Their expression was confirmed in colonic mucosal biopsies of patients with UC. These results can help to further explore the mechanism of non-responders to IFX in UC and to provide potential targets for their subsequent treatment.

Integrative Analysis and Experimental Validation of Competing Endogenous RNAs in Obstructive Sleep Apnea

Background: Obstructive sleep apnea (OSA) is highly prevalent yet underdiagnosed. This study aimed to develop a predictive signature, as well as investigate competing endogenous RNAs (ceRNAs) and their potential functions in OSA. Methods: The GSE135917, GSE38792, and GSE75097 datasets were collected from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Weighted gene correlation network analysis (WGCNA) and differential expression analysis were used to identify OSA-specific mRNAs. Machine learning methods were applied to establish a prediction signature for OSA. Furthermore, several online tools were used to establish the lncRNA-mediated ceRNAs in OSA. The hub ceRNAs were screened using the cytoHubba and validated by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Correlations between ceRNAs and the immune microenvironment of OSA were also investigated. Results: Two gene co-expression modules closely related to OSA and 30 OSA-specific mRNAs were obtained. They were significantly enriched in the antigen presentation and lipoprotein metabolic process categories. A signature that consisted of five mRNAs was established, which showed a good diagnostic performance in both independent datasets. A total of twelve lncRNA-mediated ceRNA regulatory pathways in OSA were proposed and validated, including three mRNAs, five miRNAs, and three lncRNAs. Of note, we found that upregulation of lncRNAs in ceRNAs could lead to activation of the nuclear factor kappa B (NF-κB) pathway. In addition, mRNAs in the ceRNAs were closely correlated to the increased infiltration level of effector memory of CD4 T cells and CD56bright natural killer cells in OSA. Conclusions: In conclusion, our research opens new possibilities for diagnosis of OSA. The newly discovered lncRNA-mediated ceRNA networks and their links to inflammation and immunity may provide potential research spots for future studies.

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 Novel Core Genes Involved in Malignant Transformation of Inflamed Colon Tissue Using a Computational Biology Approach and Verification in Murine Models

Inflammatory bowel disease (IBD) is a complex and multifactorial systemic disorder of the gastrointestinal tract and is strongly associated with the development of colorectal cancer. Despite extensive studies of IBD pathogenesis, the molecular mechanism of colitis-driven tumorigenesis is not yet fully understood. In the current animal-based study, we report a comprehensive bioinformatics analysis of multiple transcriptomics datasets from the colon tissue of mice with acute colitis and colitis-associated cancer (CAC). We performed intersection of differentially expressed genes (DEGs), their functional annotation, reconstruction, and topology analysis of gene association networks, which, when combined with the text mining approach, revealed that a set of key overexpressed genes involved in the regulation of colitis (C3, Tyrobp, Mmp3, Mmp9, Timp1) and CAC (Timp1, Adam8, Mmp7, Mmp13) occupied hub positions within explored colitis- and CAC-related regulomes. Further validation of obtained data in murine models of dextran sulfate sodium (DSS)-induced colitis and azoxymethane/DSS-stimulated CAC fully confirmed the association of revealed hub genes with inflammatory and malignant lesions of colon tissue and demonstrated that genes encoding matrix metalloproteinases (acute colitis: Mmp3, Mmp9; CAC: Mmp7, Mmp13) can be used as a novel prognostic signature for colorectal neoplasia in IBD. Finally, using publicly available transcriptomics data, translational bridge interconnecting of listed colitis/CAC-associated core genes with the pathogenesis of ulcerative colitis, Crohn's disease, and colorectal cancer in humans was identified. Taken together, a set of key genes playing a core function in colon inflammation and CAC was revealed, which can serve both as promising molecular markers and therapeutic targets to control IBD and IBD-associated colorectal neoplasia.

Identification of gene signatures associated with ulcerative colitis and the association with immune infiltrates in colon cancer

BACKGROUND

Inflammatory bowel diseases, including ulcerative colitis (UC) and Crohn's disease, are some of the most common inflammatory disorders of the gastrointestinal tract. The dysfunction of the immune system in the intestines is suggested to be the underlying cause of the pathogenesis of UC. However, the mechanisms regulating these dysfunctional immune cells and inflammatory phenotypes are still unclear.

METHODS

The differential expression analysis on microarray datasets were performed including GSE24287, GSE87466, GSE102133, and GSE107499, including 376 samples. "Gene Ontology" and "Kyoto Encyclopedia of Genes and Genomes" pathway enrichment analyses were conducted to identify the common differentially expressed genes (DEGs) in these datasets and explore their underlying biological mechanisms. Further algorithms like "Cell-type Identification by Estimating Relative Subsets of RNA Transcripts" were used to determine the infiltration status of immune cells in patients with UC. "Cytoscape" and "Gene Set Enrichment Analysis" were used to screen for hub genes and to investigate their biological mechanisms. The Tumor Immune Estimation Resource database was used to study the correlation between hub genes and infiltrating immune cells in patients with UC. A total of three hub genes, CCL3, MMP3, and TIMP1, were identified using Cytoscape.

RESULTS

A positive correlation was observed between these hub genes and patients with active UC. These genes served as a biomarker for active UC. Moreover, a decrease in CCL3, MMP3, and TIMP1 expression was observed in the mucosa of the intestine of patients with active UC who responded to Golimumab therapy. In addition, results show a significant positive correlation between CCL3, MMP3, and TIMP1 expression and different immune cell types including dendritic cells, macrophages, CD8+ T cells, and neutrophils in patients with colon cancer. Moreover, CCL3, MMP3, and TIMP1 expression were strongly correlated with different immune cell markers.

CONCLUSION

Study results show the involvement of hub genes like CCL3, MMP3, and TIMP1 in the pathogenesis of UC. These genes could serve as a novel pharmacological regulator of UC. These could be used as a therapeutic target for treating patients with UC and may serve as biomarkers for immune cell infiltration in colon cancer.

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).