scholarly journals 14 Claudin-6 affects the cell cycle and p53 signaling in Gastric cancer

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A14-A15
Author(s):  
Sanyog Dwivedi

BackgroundClaudin-6 (CLDN6) differentially overexpressed in Gastric Cancer (GC) is associated with poor prognosis and survival of patients. Uncovering affected pathways and genes associated with CLDN6 in GC can help in the identification of novel prognostic targets.MethodsCBioPortal1 2 was used to extract and analyze The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma Pan-Cancer Atlas Data (STAD). FunRich tool3 and Gene Ontology molecular signature database of Gene Set Enrichment Analysis (GSEA) were used for functional enrichment. CBioPortal was used to identify differentially expressed genes between groups. Graph pad Prism 8 was used to generate the graphics.ResultsTCGA STAD PanCancer Atlas data was analyzed in terms of alterations in CLDN6. 34% of the GC samples (141 samples) were assigned to the CLDN6 alteration group while the rest of the samples (299) were assigned to the non-CLDN6 alteration group (figure 1). Major alterations of CLDN6 in GC included shallow deletion, diploid, gain, and differentially expressed mRNA (figure 2). Differentially overexpressed genes in the CLDN6 group with log-ratio cutoff≥1 were used for functional enrichment in different biological pathway categories (figure 3); 18.1% of genes were associated with the transport of small molecules through the membrane, 14.6% mediated transmembrane transport and 12.5% were associated with lipid metabolism (figure 4). The Gene ontology molecular signature database of GSEA also confirmed that these genes were involved in lipid metabolism, transport activity, and epithelium development processes (table 1). Moreover, GC samples with CLDN6 alterations have higher mutations in p53 signaling (29% in TP53, 7% in CDKN2A) gene signature (figure 5) over samples in the non-CLDN6 alteration group (figure 6). Similarly, genes related with cell cycle control like CCNE1, MYC, SRC, and STAT3 showed higher mutations in the CLDN6 alteration group while JAK1 and E2F8 showed lower mutations than non-CLDN6 GC samples (figure 7). These observations indicate that CLDN6 in GC affects the transport of small molecules and lipid metabolism and that it is associated to tumors with higher mutations in p53 and cell cycle-related genes.Abstract 14 Table 1Functional enrichment of differentially expressed genes (log-ratio ≥1) in CLDN6 group GC samples in Gene ontology molecular signature database of GSEAAbstract 14 Figure 1Distribution of GC samples and patients of TCGA STAD data between CLDN6 and non CLDN6 alteration groupsAbstract 14 Figure 2Major alterations in CLDN6 in GC (TCGA STAD data)Abstract 14 Figure 3Volcano plot of differentially expressed genes in CLDN6 and non CLDN6 groups. Log10 p-Value cutoff ≥2Abstract 14 Figure 4Functional enrichment of differentially expressed genes (log-ratio ≥1) in biological process categoryAbstract 14 Figure 5Overall mutations in several important gene signatures involved in cancer between CLDN6 and non-CLDN6 GC samplesAbstract 14 Figure 6Total mutations in p53 signaling genesAbstract 14 Figure 7Total mutations in genes involved in cell cycle control between CLDN6 and non-CLDN6 GC samplesConclusionsCLDN6 alterations in GC affect the cell cycle and p53 signaling pathways with higher mutations in TP53, CDKN2A, CCNE1, MYC, SRC, and STAT3 genes.AcknowledgementsThis research was supported by CONACYT CVU grant 871712.ReferencesCerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2012;2:401–4.Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 2013;6:l1.Pathan M, Keerthikumar S, Ang C-S, Gangoda L, Quek CYJ, Williamson NA, et al. FunRich: An open access standalone functional enrichment and interaction network analysis tool. PROTEOMICS 2015;15:2597–601.

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rowan AlEjielat ◽  
Anas Khaleel ◽  
Amneh H. Tarkhan

Abstract Background Ankylosing spondylitis (AS) is a rare inflammatory disorder affecting the spinal joints. Although we know some of the genetic factors that are associated with the disease, the molecular basis of this illness has not yet been fully elucidated, and the genes involved in AS pathogenesis have not been entirely identified. The current study aimed at constructing a gene network that may serve as an AS gene signature and biomarker, both of which will help in disease diagnosis and the identification of therapeutic targets. Previously published gene expression profiles of 16 AS patients and 16 gender- and age-matched controls that were profiled on the Illumina HumanHT-12 V3.0 Expression BeadChip platform were mined. Patients were Portuguese, 21 to 64 years old, were diagnosed based on the modified New York criteria, and had Bath Ankylosing Spondylitis Disease Activity Index scores > 4 and Bath Ankylosing Spondylitis Functional Index scores > 4. All patients were receiving only NSAIDs and/or sulphasalazine. Functional enrichment and pathway analysis were performed to create an interaction network of differentially expressed genes. Results ITM2A, ICOS, VSIG10L, CD59, TRAC, and CTLA-4 were among the significantly differentially expressed genes in AS, but the most significantly downregulated genes were the HLA-DRB6, HLA-DRB5, HLA-DRB4, HLA-DRB3, HLA-DRB1, HLA-DQB1, ITM2A, and CTLA-4 genes. The genes in this study were mostly associated with the regulation of the immune system processes, parts of cell membrane, and signaling related to T cell receptor and antigen receptor, in addition to some overlaps related to the IL2 STAT signaling, as well as the androgen response. The most significantly over-represented pathways in the data set were associated with the “RUNX1 and FOXP3 which control the development of regulatory T lymphocytes (Tregs)” and the “GABA receptor activation” pathways. Conclusions Comprehensive gene analysis of differentially expressed genes in AS reveals a significant gene network that is involved in a multitude of important immune and inflammatory pathways. These pathways and networks might serve as biomarkers for AS and can potentially help in diagnosing the disease and identifying future targets for treatment.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hui Li ◽  
Jing-An Chen ◽  
Qian-Zhi Ding ◽  
Guan-Yi Lu ◽  
Ning Wu ◽  
...  

Abstract Background Methamphetamine (METH) is one of the most widely abused illicit substances worldwide; unfortunately, its addiction mechanism remains unclear. Based on accumulating evidence, changes in gene expression and chromatin modifications might be related to the persistent effects of METH on the brain. In the present study, we took advantage of METH-induced behavioral sensitization as an animal model that reflects some aspects of drug addiction and examined the changes in gene expression and histone acetylation in the prefrontal cortex (PFC) of adult rats. Methods We conducted mRNA microarray and chromatin immunoprecipitation (ChIP) coupled to DNA microarray (ChIP-chip) analyses to screen and identify changes in transcript levels and histone acetylation patterns. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were performed to analyze the differentially expressed genes. We then further identified alterations in ANP32A (acidic leucine-rich nuclear phosphoprotein-32A) and POU3F2 (POU domain, class 3, transcription factor 2) using qPCR and ChIP-PCR assays. Results In the rat model of METH-induced behavioral sensitization, METH challenge caused 275 differentially expressed genes and a number of hyperacetylated genes (821 genes with H3 acetylation and 10 genes with H4 acetylation). Based on mRNA microarray and GO and KEGG enrichment analyses, 24 genes may be involved in METH-induced behavioral sensitization, and 7 genes were confirmed using qPCR. We further examined the alterations in the levels of the ANP32A and POU3F2 transcripts and histone acetylation at different periods of METH-induced behavioral sensitization. H4 hyperacetylation contributed to the increased levels of ANP32A mRNA and H3/H4 hyperacetylation contributed to the increased levels of POU3F2 mRNA induced by METH challenge-induced behavioral sensitization, but not by acute METH exposure. Conclusions The present results revealed alterations in transcription and histone acetylation in the rat PFC by METH exposure and provided evidence that modifications of histone acetylation contributed to the alterations in gene expression caused by METH-induced behavioral sensitization.


2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8831 ◽  
Author(s):  
Xiaojiao Guan ◽  
Yao Yao ◽  
Guangyao Bao ◽  
Yue Wang ◽  
Aimeng Zhang ◽  
...  

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.


2021 ◽  
Author(s):  
Haiyun Luo ◽  
Wenjing Liu ◽  
Yanli Zhang ◽  
Xiao Jiang ◽  
Shiqing Wu ◽  
...  

Abstract Background: Dental pulp stem cells (DPSCs) exhibited self-renewal, pluripotency capacity and served as promising cells source in endodontic regeneration and tissue engineering. Meanwhile, the regenerative capacity of DPSCs is limited and reduced in long lifespan. N6-methyladenosine (m6A) is the most prevalent, reversible internal modification in RNAs. The methyltransferases complex and demethylases mediated m6A methylation and cooperated to impact various biological processes associated with stem cell fate determination. However, the biological effect of m6A methylation in DPSCs remained unclear. Methods: Cell surface markers and differentiation potential of primary DPSCs were identified and m6A immunoprecipitation with deep sequencing (m6A RIP-seq) was used to uncover characteristics of m6A modifications in DPSCs transcriptome. Expression level of m6A-related genes were evaluated in immature/mature pulp tissues and cells. Lentiviral vectors were constructed to knockdown or overexpress methyltransferase like 3 (METTL3). Cell morphology, viability, senescence and apoptosis were further analyzed by β-galactosidase, TUNEL staining and flow cytometry. Bioinformatic analysis combing m6A RIP and shMETTL3 RNA-seq was used to functionally enrich overlapped genes and screen target of METTL3. Cell cycle distributions were assayed by flow cytometry and m6A RIP-qPCR was used to confirm METTL3 mediated m6A methylation in DPSCs. Results: Here, m6A peaks distribution, binding area and motif in DPSCs were first revealed by m6A RIP-seq. We also found a relative high expression level of METTL3 in immature DPSCs with superior regenerative potential and METTL3 knockdown induced cell apoptosis and senescence. Furthermore, Conjoint analysis of m6A RIP and RNA-sequencing showed differentially expressed genes affected by METTL3 depletion was mainly enriched in cell cycle, mitosis and alteration of METTL3 expression resulted in cell cycle arrest which indicated METTL3 make essential effect in cell cycle control. To further investigate underlying mechanisms, we explored proteins interaction network of differentially expressed genes and Polo-like Kinase 1 (PLK1), a critical cycle modulator was identified as target of METTL3-mediated m6A methylation in DPSCs. Conclusions: These results revealed m6A methylated hallmarks in DPSCs and a regulatory role of METTL3 in cell cycle control. Our study shed light on therapeutic approaches in vital pulp therapy and serve new insight in stem cells based tissue engineering.


2019 ◽  
Vol 48 (5) ◽  
pp. 030006051988726
Author(s):  
Yuting Zhang ◽  
Bo Shen ◽  
Liya Zhuge ◽  
Yong Xie

Objective We aimed to identify differentially expressed genes (DEG) in patients with inflammatory bowel disease (IBD). Methods RNA-seq data were obtained from the Array Express database. DEG were identified using the edgeR package. A co-expression network was constructed and key modules with the highest correlation with IBD inflammatory sites were identified for analysis. The Cytoscape MCODE plugin was used to identify key sub-modules of the protein–protein interaction (PPI) network. The genes in the sub-modules were considered hub genes, and functional enrichment analysis was performed. Furthermore, we constructed a drug–gene interaction network. Finally, we visualized the hub gene expression pattern between the colon and ileum of IBD using the ggpubr package and analyzed it using the Wilcoxon test. Results DEG were identified between the colon and ileum of IBD patients. Based on the co-expression network, the green module had the highest correlation with IBD inflammatory sites. In total, 379 DEG in the green module were identified for the PPI network. Nineteen hub genes were differentially expressed between the colon and ileum. The drug–gene network identified these hub genes as potential drug targets. Conclusion Nineteen DEG were identified between the colon and ileum of IBD patients.


Rheumatology ◽  
2020 ◽  
Author(s):  
Jun Inamo

Abstract Objectives The aims of this study were to investigate the relationship between the type of autoantibody and gene expression profile in skin lesions from patients with SSc, and to identify specific dysregulated pathways in SSc patients compared with healthy controls. Methods Sixty-one patients with SSc from the Genetics vs Environment in Scleroderma Outcome Study cohort and 36 healthy controls were included in this study. Differentially expressed genes were extracted and functional enrichment and pathway analysis were conducted. Results Compared with healthy controls, lists containing 2, 71, 10, 144 and 78 differentially expressed genes were created for patients without specific autoantibody, ACA, anti-U1 RNP antibody (RNP), anti-RNA polymerase III antibody (RNAP) and anti-topoisomerase I antibody (ATA), respectively. While part of the enriched pathways overlapped, distinct pathways were identified except in those patients lacking specific autoantibody. The distinct enriched pathways included ‘keratinocyte differentiation’ for ACA, ‘nuclear factor κB signalling’ and ‘cellular response to TGF-β stimulus’ for RNAP, ‘interferon α/β signalling’ for RNP, and ‘cellular response to stress’ for ATA. Cell type signature score analysis revealed that macrophages/monocytes, endothelial cells and fibroblasts were associated with ACA, RNAP, ATA and the severity of the SSc skin lesions. Conclusion Pathogenic pathways were identified according to the type of autoantibody by leveraging gene expression data of patients and controls from a multicentre cohort. The current study may promote the search for new therapeutic targets for SSc.


Rheumatology ◽  
2020 ◽  
Author(s):  
Seung Min Jung ◽  
Kyung-Su Park ◽  
Ki-Jo Kim

Abstract Objective RA encompasses a complex, heterogeneous and dynamic group of diseases arising from molecular and cellular perturbations of synovial tissues. The aim of this study was to decipher this complexity using an integrative systems approach and provide novel insights for designing stratified treatments. Methods An RNA sequencing dataset of synovial tissues from 152 RA patients and 28 normal controls was imported and subjected to filtration of differentially expressed genes, functional enrichment and network analysis, non-negative matrix factorization, and key driver analysis. A naïve Bayes classifier was applied to the independent datasets to investigate the factors associated with treatment outcome. Results A matrix of 1241 upregulated differentially expressed genes from RA samples was classified into three subtypes (C1–C3) with distinct molecular and cellular signatures. C3 with prominent immune cells and proinflammatory signatures had a stronger association with the presence of ACPA and showed a better therapeutic response than C1 and C2, which were enriched with neutrophil and fibroblast signatures, respectively. C2 was more occupied by synovial fibroblasts of destructive phenotype and carried highly expressed key effector molecules of invasion and osteoclastogenesis. CXCR2, JAK3, FYN and LYN were identified as key driver genes in C1 and C3. HDAC, JUN, NFKB1, TNF and TP53 were key regulators modulating fibroblast aggressiveness in C2. Conclusions Deep phenotyping of synovial heterogeneity captured comprehensive and discrete pathophysiological attributes of RA regarding clinical features and treatment response. This result could serve as a template for future studies to design stratified approaches for RA patients.


2020 ◽  
Vol 21 (2) ◽  
pp. 147032032091963
Author(s):  
Xiaoxue Chen ◽  
Mindan Sun

Purpose: This study aims to identify immunoglobulin-A-nephropathy-related genes based on microarray data and to investigate novel potential gene targets for immunoglobulin-A-nephropathy treatment. Methods: Immunoglobulin-A-nephropathy chip data was obtained from the Gene Expression Omnibus database, which included 10 immunoglobulin-A-nephropathy and 22 normal samples. We used the limma package of R software to screen differentially expressed genes in immunoglobulin-A-nephropathy and normal glomerular compartment tissues. Functional enrichment (including cellular components, molecular functions, biological processes) and signal pathways were performed for the differentially expressed genes. The online analysis database (STRING) was used to construct the protein-protein interaction networks of differentially expressed genes, and Cytoscape software was used to identify the hub genes of the signal pathway. In addition, we used the Connectivity Map database to predict possible drugs for the treatment of immunoglobulin-A-nephropathy. Results: A total of 348 differentially expressed genes were screened including 107 up-regulated and 241 down-regulated genes. Functional analysis showed that up-regulated differentially expressed genes were mainly concentrated on leukocyte migration, and the down-regulated differentially expressed genes were significantly enriched in alpha-amino acid metabolic process. A total of six hub genes were obtained: JUN, C3AR1, FN1, AGT, FOS, and SUCNR1. The small-molecule drugs thapsigargin, ciclopirox and ikarugamycin were predicted therapeutic targets against immunoglobulin-A-nephropathy. Conclusion: Differentially expressed genes and hub genes can contribute to understanding the molecular mechanism of immunoglobulin-A-nephropathy and providing potential therapeutic targets and drugs for the diagnosis and treatment of immunoglobulin-A-nephropathy.


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