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Identification and analysis of key genes associated with ulcerative colitis based on DNA microarray data.

ABSTRACT: This study aimed to identify genes that may play a role in development of ulcerative colitis (UC) and gain insight into its pathogenesis.Gene expression profiling data, including samples collected from 13 early-stage UC (EUC), 8 advanced-stage UC (AUC), and 5 control subjects, were downloaded from the Gene Expression Omnibus database under the accession number of GSE9452. Differentially expressed genes (DEGs) were identified in EUC and AUC compared with controls. DEGs for EUC and AUC, as well as AUC-specific DEGs were subjected to pathway enrichment analysis. Random Walk with Restart (RWR) was used to identify DEGs that are critical in UC based on a protein-to-protein interaction (PPI) network and the inflammatory bowel disease (IBD) pathway downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. IL17 and transforming growth factor beta TGF-?) expression levels in colonic tissue from patients with UC and normal colonic mucosa from healthy adults were analyzed by immunohistochemistry (IHC).A total of 3511 and 911 DEGs were identified in AUC and EUC, respectively. The overlapping DEGs and the AUC-specific DEGs were both enriched in pathways related to immunity, such as antigen processing and presentation. AUC-specific DEGs were related to cell migration, such as ECM-receptor interaction. Following DEG prioritization, TLR4 and STAT1 were linked with EUC, AUC, and CD. The upregulated gene TGFB increased the number of Th17 cells, as verified by IHC. Furthermore, PIK3R1, CREBBP, and STAT1 were part of high-degree nodes in the PPI sub-network.The upregulated gene TGFB may regulate IL17 expression in UC. PIK3R1 may participate in immunity and CREBBP may interact with STAT1 in the development and progression of UC.

SUBMITTER: Song R

PROVIDER: S-EPMC6392526 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Identification and analysis of key genes associated with ulcerative colitis based on DNA microarray data.

Song Ruifeng R Li Ya Y Hao Weiwei W Wang Bingxue B Yang Lei L Xu Feng F

Medicine 20180501 21

This study aimed to identify genes that may play a role in development of ulcerative colitis (UC) and gain insight into its pathogenesis.Gene expression profiling data, including samples collected from 13 early-stage UC (EUC), 8 advanced-stage UC (AUC), and 5 control subjects, were downloaded from the Gene Expression Omnibus database under the accession number of GSE9452. Differentially expressed genes (DEGs) were identified in EUC and AUC compared with controls. DEGs for EUC and AUC, as well as ...[more]

PMID: 29794741

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Project description:BackgroundUlcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC.MethodsMicroarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the "limma" R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the "clusterProfiler" R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene.ResultsSix functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3.ConclusionsUsing WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.

Project description:Six pairs of transcription profiles between glycopeptide-intermediate S. aureus (GISA [or vancomycin-intermediate S. aureus; VISA]) and glycopeptide-susceptible S. aureus (vancomycin-susceptible S. aureus [VSSA], including glycopeptide-susceptible isogenic mutants from VISA) strains were compared using a microarray. Ninety-two open reading frames which were or tended to be increased in transcription in VISA in at least five out of six array combination pairs were evaluated for their effects on glycopeptide susceptibility by introducing these genes one by one into VSSA strain N315 to construct an overexpression library. By screening the library, 17 genes including 8 novel genes were identified as associated with glycopeptide resistance since their experimental overexpression reduced vancomycin and/or teicoplanin susceptibility of N315. The raised MICs of vancomycin and teicoplanin were 1.25 to 3.0 and 1.5 to 6.0 mg/liter, respectively, as compared to 1.0 mg/liter of N315. Three of these genes, namely graF, msrA2, and mgrA, also raised the oxacillin MIC from 8.0 mg/liter for N315 to 64 to approximately 128 mg/liter when they were overexpressed in N315. Their contribution to vancomycin and beta-lactam resistance was further supported by gene knockout and trans-complementation assay. By using a plasmid-based promoter-green fluorescent protein gene (gfp) transcriptional fusion system, graF promoter-activated cells were purified, and subsequent susceptibility tests and Northern blot analysis demonstrated that the cells with up-regulated activity of graF promoter showed reduced susceptibility to vancomycin, teicoplanin, and oxacillin. In addition, cell morphology studies showed that graF and msrA2 overexpression increased cell wall thickness of N315 by factors of 23.91 and 22.27%, respectively, accompanied by glycopeptide MIC increments of 3- to 6-fold, when they were overexpressed in N315. Moreover, extended experiments and analyses indicate that many of the genes identified above are related to the cell wall biosynthetic pathway, including active nutrient transport systems. We propose that the genes which raise glycopeptide resistance in S. aureus function toward altering the cell wall metabolic pathway.

Project description:BackgroundUlcerative colitis (UC) is a chronic and debilitating inflammatory bowel disease that impairs quality of life. Cuproptosis, a recently discovered form of cell death, has been linked to many inflammatory diseases, including UC. This study aimed to examine the biological and clinical significance of cuproptosis-related genes in UC.MethodsThree gene expression profiles of UC were obtained from the Gene Expression Omnibus (GEO) database to form the combined dataset. Differential analysis was performed based on the combined dataset to identify differentially expressed genes, which were intersected with cuproptosis-related genes to obtain differentially expressed cuproptosis-related genes (DECRGs). Machine learning was conducted based on DECRGs to identify signature genes. The prediction model of UC was established using signature genes, and the molecular subtypes related to cuproptosis of UC were identified. Functional enrichment analysis and immune infiltration analysis were used to evaluate the biological characteristics and immune infiltration landscape of signature genes and molecular subtypes.ResultsSeven signature genes (ABCB1, AQP1, BACE1, CA3, COX5A, DAPK2, and LDHD) were identified through the machine learning algorithms, and the nomogram built from these genes had excellent predictive performance. The 298 UC samples were divided into two subtypes through consensus cluster analysis. The results of the functional enrichment analysis and immune infiltration analysis revealed significant differences in gene expression patterns, biological functions, and enrichment pathways between the cuproptosis-related molecular subtypes of UC. The immune infiltration analysis also showed that the immune cell infiltration in cluster A was significantly higher than that of cluster B, and six of the characteristic genes (excluding BACE1) had higher expression levels in subtype B than in subtype A.ConclusionsThis study identified several promising signature genes and developed a nomogram with strong predictive capabilities. The identification of distinct subtypes of UC enhances our current understanding of UC's underlying pathogenesis and provides a foundation for personalized diagnosis and treatment in the future.

Dataset Information

Identification and analysis of key genes associated with ulcerative colitis based on DNA microarray data.

Publications

Identification and analysis of key genes associated with ulcerative colitis based on DNA microarray data.

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