Evidence for two distinct alpha(1,2)-fucosyltransferase genes differentially expressed throughout the rat colon.
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ABSTRACT:
SUBMITTER: Piau JP
PROVIDER: S-EPMC1138212 | biostudies-other | 1994 Jun
REPOSITORIES: biostudies-other
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Project description:Purpose:Colon adenocarcinoma (COAD) is the third most common malignancy globally and is further categorized as left colon adenocarcinoma (LCOAD) or right colon adenocarcinoma (RCOAD) depending on the location of the primary tumor. The therapeutic outcome and long-term prognosis for patients with COAD are less than satisfactory, and this may be associated with tumor location. Therefore, it is important to investigate the genetic differences in COAD at different sites. Patients and Methods. Public data associated with COAD were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using R software (version 3.5.3), and functional annotation of DEGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction network was constructed, hub genes were identified and analyzed, and data mining using Gene Expression Profiling Interactive Analysis (GEPIA) was conducted. Results:A total of 286 DEGs were identified between LCOAD and RCOAD. Additionally, 10 hub genes associated with COAD at different locations were screened, namely, CDKN2A, IGF1R, MDM2, SMAD3, SLC2A1, GRM5, PLCB4, FGFR1, UBE2V2, and TNFRSF10B. The expression of cyclin-dependent kinase inhibitor 2A (CDKN2A) and solute carrier family 2 member 1 (SLC2A1) was significantly associated with pathological stage (P < 0.05). COAD patients with high expression levels of CDKN2A exhibited poorer overall survival (OS) times than those with low expression levels (P < 0.05). Conclusion:CDKN2A expression was significantly different between LCOAD and RCOAD and was closely related to the prognosis of COAD. It is of great value for further understanding of the pathogenesis of LCOAD and RCOAD.
| S-EPMC7201700 | biostudies-literature
Project description:BackgroundSessile serrated adenomas/polyps (SSA/Ps) may account for 20-30% of colon cancers. Although large SSA/Ps are generally recognized phenotypically, small (<1 cm) or dysplastic SSA/Ps are difficult to differentiate from hyperplastic or small adenomatous polyps by endoscopy and histopathology. Our aim was to define the comprehensive gene expression phenotype of SSA/Ps to better define this cancer precursor.ResultsRNA sequencing was performed on 5' capped RNA from seven SSA/Ps collected from patients with the serrated polyposis syndrome (SPS) versus eight controls. Highly expressed genes were analyzed by qPCR in additional SSA/Ps, adenomas and controls. The cellular localization and level of gene products were examined by immunohistochemistry in syndromic and sporadic SSA/Ps, adenomatous and hyperplastic polyps and controls. We identified 1,294 differentially expressed annotated genes, with 106 increased ≥10-fold, in SSA/Ps compared to controls. Comparing these genes with an array dataset for adenomatous polyps identified 30 protein coding genes uniquely expressed ≥10-fold in SSA/Ps. Biological pathways altered in SSA/Ps included mucosal integrity, cell adhesion, and cell development. Marked increased expression of MUC17, the cell junction protein genes VSIG1 and GJB5, and the antiapoptotic gene REG4 were found in SSA/Ps, relative to controls and adenomas, were verified by qPCR analysis of additional SSA/Ps (n = 21) and adenomas (n = 10). Immunohistochemical staining of syndromic (n≥11) and sporadic SSA/Ps (n≥17), adenomatous (n≥13) and hyperplastic (n≥10) polyps plus controls (n≥16) identified unique expression patterns for VSIG1 and MUC17 in SSA/Ps.ConclusionA subset of genes and pathways are uniquely increased in SSA/Ps, compared to adenomatous polyps, thus supporting the concept that cancer develops by different pathways in these phenotypically distinct polyps with markedly different gene expression profiles. Immunostaining for a subset of these genes differentiates both syndromic and sporadic SSA/Ps from adenomatous and hyperplastic polyps.
| S-EPMC3922809 | biostudies-literature
Project description:Glycolipids in epithelial tissues of the gastrointestinal tract act as receptors for enteric bacteria and are implicated in the activation of the intestinal immune system. To clarify the genes involved in the fucosylation of the major glycolipids, substrate glycolipids and fucosylated products were measured in tissues of wild-type and mutant mice lacking alpha(1,2)fucosyltransferase genes FUT1 or FUT2. Quantitative determination was performed by TLC-immunostaining for GA1 (Gg4Cer), FGA1 (fucosyl GA1), GM1 (II3NeuAc-Gg4Cer), FGM1 (fucosyl GM1), and Forssman glycolipids. Both FGM1 and FGA1 completely disappeared from the antrum, cecum, and colon of FUT2-null mice, but not those of FUT1-null and wild-type mice. Precursor glycolipids, GM1 and GA1, accumulated in tissues of FUT2-null mice, indicating that the FUT2-encoded enzyme preferentially participates in the fucosylation of GA1 and GM1 in these tissues. Female reproductive organs were similarly found to utilize FUT2 for the fucosylation of glycolipids FGA1 (uterus and cervix), and FGM1 (ovary), due to their absence in FUT2-null mice. In FUT1-null mice FGA1 was lost from the pancreas, but was present in wild-type and FUT2-null mice, indicating that FUT1 is essential for fucosylation of GA1 in the pancreas. Ulex europaeus agglutinin-I lectin histochemistry for alpha(1,2)fucose residues confirmed the absence of alpha(1,2)fucose residues from the apical surface of pancreatic acinar glands of FUT1-null mice. Ileum, epididymis, and testis retained specific fucosylated glycolipids, irrespective of targeted deletion of either gene, indicating either compensation for or redundancy of the alpha(1,2)fucosyltransferase genes in these tissues.
| S-EPMC1224153 | biostudies-other
Project description:BackgroundDNA methylation, acknowledged as a key modification in the field of epigenetics, regulates gene expression at the transcriptional level. Aberrant methylation in DNA regulatory regions could upregulate oncogenes and downregulate tumor suppressor genes without changing the sequences. However, studies of methylation in the control of gene expression are still inadequate. In the present research, we performed bioinformatics analysis to clarify the function of methylation and supply candidate methylation-related biomarkers and drivers for colon cancer.AimTo identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in colon cancer by bioinformatics analysis.MethodsWe downloaded RNA expression profiles, Illumina Human Methylation 450K BeadChip data, and clinical data of colon cancer from The Cancer Genome Atlas project. MeDEGs were identified by analyzing the gene expression and methylation levels using the edgeR and limma package in R software. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed in the DAVID database and KEGG Orthology-Based Annotation System 3.0, respectively. We then conducted Kaplan-Meier survival analysis to explore the relationship between methylation and expression and prognosis. Gene set enrichment analysis (GSEA) and investigation of protein-protein interactions (PPI) were performed to clarify the function of prognosis-related genes.ResultsA total of 5 up-regulated and 81 down-regulated genes were identified as MeDEGs. GO and KEGG pathway analyses indicated that MeDEGs were enriched in multiple cancer-related terms. Furthermore, Kaplan-Meier survival analysis showed that the prognosis was negatively associated with the methylation status of glial cell-derived neurotrophic factor (GDNF) and reelin (RELN). In PPI networks, GDNF and RELN interact with neural cell adhesion molecule 1. Besides, GDNF can interact with GDNF family receptor alpha (GFRA1), GFRA2, GFRA3, and RET. RELN can interact with RAFAH1B1, disabled homolog 1, very low-density lipoprotein receptor, lipoprotein receptor-related protein 8, and NMDA 2B. Based on GSEA, hypermethylation of GDNF and RELN were both significantly associated with pathways including "RNA degradation," "ribosome," "mismatch repair," "cell cycle" and "base excision repair."ConclusionAberrant DNA methylation plays an important role in colon cancer progression. MeDEGs that are associated with the overall survival of patients may be potential targets in tumor diagnosis and treatment.
| S-EPMC6639549 | biostudies-literature
Project description:Left-sided colon carcinoma (LSCC) and right-sided colon carcinoma (RSCC) differ in their genetic susceptibilities to neoplastic transformation. The present study identified 11 genes that were differentially expressed in LSCC and RSCC by expression profiling with microarray analysis. Compared with RSCC, the human genes for L-lactate dehydrogenase B chain (LDHB), cyclin-dependent kinase 4 inhibitor D (CDKN2D), phosphatidylinositol-4-phosphate-3-kinase C2 domain-containing subunit α (PI3KC2α), protocadherin fat 1 (FAT; a human protein that closely resembles the Drosophila tumor suppressor, fat) and dual specificity protein phosphatase 2 (DUSP2) were upregulated in LSCC. By contrast, genes for ubiquitin D (UBD), casein kinase-1 binding protein (CK1BP), synaptotagmin-13 (SYT1), zinc finger protein 560 (ZNF560), pleckstrin homology domain-containing family B member 2 (PLEKHB2) and IgGFc-binding protein (FCGBP) were downregulated in LSCC compared with RSCC. A quantitative polymerase chain reaction (qPCR) analysis revealed that the mRNA levels of UBD and CK1BP in LSCC were significantly lower compared with those in RSCC (P=0.033 and P= 0.005, respectively), whereas the mRNA levels of LDHB and CDKN2D in LSCC were significantly higher compared with those in RSCC (P=0.008 and P=0.017, respectively). Western blot and immunohistochemical analyses demonstrated that the expression of CDKN2D in LSCC was significantly higher compared with that in RSCC, while the expression of UBD in LSCC was significantly lower compared with that in RSCC. The present study provides important insights into the understanding of the molecular genetic basis for the different biological behaviors observed between LSCC and RSCC. These insights may therefore serve as a basis for the identification of novel colon cancer markers and therapeutic targets.
| S-EPMC3789115 | biostudies-literature
Project description:A summary of the work associated to these microarrays is the following: The need for an integrated view of all data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize phenomena in terms of how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed Biological Association Networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). Seven cell lines representative of different types of cancer including colon cancer (HT29 and Caco2), breast cancer (MCF7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by microarrays covering the whole human genome and analyzed with the GeneSpring GX software package, v.7.3.1. Genes deregulated in common in the two colon cancer cell lines studied, were subject of Biological Association Networks construction. Dikkopf homolog-1 (DKK1) was a clear node of this network, and functional validations of this target using a siRNA showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of differentially expressed genes in the two breast cancer cell lines studied. siRNA treatment against UGT1A showed also an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was a gene overexpressed in common among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. Biological Association Networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using iRNA technology against these three genes show chemosensitization toward MTX. Two cell lines are compared, which are Caco2 colon cancer cells sensitive to methotrexate and Caco2 cells resistant to 10e-5M MTX. Six samples are provided, which correspond to triplicates of each cell line. The samples provided were analyzed using the specific software GeneSpring GX.
| S-ECPF-GEOD-16066 | biostudies-other
Project description:The alpha-2-fucosyltransferases (alpha2FTs) are enzymes involved in the biosynthesis of alpha2fucosylated glycan structures. In mammalian genomes, there are three alpha2FT genes located in tandem-FUT1, FUT2, and Sec1-each contained within a single exon. It has been suggested that these genes originated from two successive duplications, with FUT1 being generated first and FUT2 and Sec1 second. Despite gene conversion being considered the main mechanism of concerted evolution in gene families, previous studies of primates alpha2FTs failed to detect it, although the occurrence of gene conversion between FUT2 and Sec1 was recently reported in a human allele. The primary aim of our work was to initiate a broader study on the molecular evolution of mammalian alpha2FTs. Sequence comparison leads us to confirm that the three genes appeared by two rounds of duplication. In addition, we were able to detect multiple gene-conversion events at the base of primates and within several nonprimate species involving FUT2 and Sec1. Gene conversion involving FUT1 and either FUT2 or Sec1 was also detected in rabbit. The extent of gene conversion between the alpha2FTs genes appears to be species-specific, possibly related to functional differentiation of these genes. With the exception of rabbits, gene conversion was not observed in the region coding the C-terminal part of the catalytic domain. In this region, the number of amino acids that are identical between FUT1 and FUT2, but different in Sec1, is higher than in other parts of the protein. The biologic meaning of this observation may be related to functional constraints.
| S-EPMC2706377 | biostudies-literature
Project description:BACKGROUND: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariate in nature. Yet, current statistical methods for detecting differential expression merely consider the univariate difference in expression level of each gene in isolation, thus potentially neglecting many genes of biological importance. RESULTS: We have developed a novel algorithm for detecting multivariate expression patterns, named Recursive Independence Test (RIT). This algorithm generalizes differential expression testing to more complex expression patterns, while still including genes found by the univariate approach. We prove that RIT is consistent and controls error rates for small sample sizes. Simulation studies confirm that RIT offers more power than univariate differential expression analysis when multivariate effects are present. We apply RIT to gene expression data sets from diabetes and cancer studies, revealing several putative disease genes that were not detected by univariate differential expression analysis. CONCLUSION: The proposed RIT algorithm increases the power of gene expression analysis by considering multivariate effects while retaining error rate control, and may be useful when conventional differential expression tests yield few findings.
| S-EPMC1885271 | biostudies-literature
Project description:BackgroundColon adenocarcinoma (COAD) can be divided into left-sided and right-sided COAD (LCCs and RCCs, respectively). They have unique characteristics in various biological aspects, particularly immune invasion and prognosis. The purpose of our study was to develop a prognostic risk scoring model (PRSM) based on differentially expressed immune-related genes (IRGs) between LCCs and RCCs, therefore the prognostic key IRGs could be identified.MethodsThe gene sets and clinical information of COAD patients were derived from TCGA and GEO databases. The comparison of differentially expressed genes (DEGs) of LCCs and RCCs were conducted with appliance of "Limma" analysis. The establishment about co-expression modules of DEGs related with immune score was conducted by weighted gene co-expression network analysis (WGCNA). Furthermore, we screened the module genes and completed construction of gene pairs. The analysis of the prognosis and the establishment of PRSM were performed with univariate- and lasso-Cox regression. We employed the PRSM in the model group and verification group for the purpose of risk group assignment and PRSM accuracy verification. Finally, the identification of the prognostic key IRGs was guaranteed by the adoption of functional enrichment, "DisNor" and protein-protein interaction (PPI).ResultsA total of 215 genes were screened out by differential expression analysis and WGCNA. A PRSM with 16 immune-related gene pairs (IRGPs) was established upon the genes pairing. Furthermore, we confirmed that the risk score was an independent factor for survival by univariate- and multivariate-Cox regression. The prognosis of high-risk group in model group (P < 0.001) and validation group (P = 0.014) was significantly worse than that in low-risk group. Treg cells (P < 0.001) and macrophage M0 (P = 0.015) were highly expressed in the high-risk group. The functional analysis indicated that there was significant up-regulation with regard of lymphocyte and cytokine related terms in low-risk group. Finally, we identified five prognostic key IRGs associated with better prognosis through PPI and prognostic analysis, including IL2RB, TRIM22, CIITA, CXCL13, and CXCR6.ConclusionThrough the analysis and screening of the DEGs between LCCs and RCCs, we constructed a PRSM which could predicate prognosis of LCCs and RCCs, and five prognostic key IRGs were identified as well. Therefore, the basis for identifying the benefits of immunotherapy and immunomodulatory was built.
| S-EPMC7982460 | biostudies-literature
Project description:BackgroundThe ubiquitination process can be reversed by deubiquitinating enzymes (DUBs). These proteases are involved in ubiquitin processing, in the recovery of modified ubiquitin trapped in inactive forms, and in the recycling of ubiquitin monomers from polyubiquitinated chains. The diversity of DUB functions is illustrated by their number and variety of their catalytic domains with specific 3D architectures. DUBs can be divided into five subclasses: ubiquitin C-terminal hydrolases (UCHs), ubiquitin-specific proteases (USPs or UBPs), ovarian tumour proteases (OTUs), Machado-Joseph disease proteases (MJDs) and JAB1/MPN/Mov34 metalloenzymes (JAMMs).MethodsConsidering the role that the ubiquitin-proteasome system has been shown to play during the development of Schistosoma mansoni, our main goal was to identify and characterize SmUSPs. Here, we showed the identification of putative ubiquitin-specific proteases using bioinformatic approaches. We also evaluated the gene expression profile of representative USP family members using qRT-PCR.ResultsWe reported 17 USP family members in S. mansoni that present a conservation of UCH domains. Furthermore, the putative SmUSP transcripts analysed were detected in all investigated stages, showing distinct expression during S. mansoni development. The SmUSPs exhibiting high expression profiles were SmUSP7, SmUSP8, SmUSP9x and SmUSP24.ConclusionS. mansoni USPs showed changes in expression levels for different life cycle stages indicating their involvement in cellular processes required for S. mansoni development. These data will serve as a basis for future functional studies of USPs in this parasite.
| S-EPMC4485857 | biostudies-literature