scholarly journals A curated collection of transcriptome datasets to investigate the molecular mechanisms of immunoglobulin E-mediated atopic diseases

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Susie S Y Huang ◽  
Fatima Al Ali ◽  
Sabri Boughorbel ◽  
Mohammed Toufiq ◽  
Damien Chaussabel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Web Application ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Immunoglobulin E ◽  
Developed Countries ◽  
Gene Expression Omnibus ◽  
School Age Children ◽  
Atopic Diseases ◽  
Sample Number

Abstract Prevalence of allergies has reached ~20% of population in developed countries and sensitization rate to one or more allergens among school age children are approaching 50%. However, the combination of the complexity of atopic allergy susceptibility/development and environmental factors has made identification of gene biomarkers challenging. The amount of publicly accessible transcriptomic data presents an unprecedented opportunity for mechanistic discoveries and validation of complex disease signatures across studies. However, this necessitates structured methodologies and visual tools for the interpretation of results. Here, we present a curated collection of transcriptomic datasets relevant to immunoglobin E-mediated atopic diseases (ranging from allergies to primary immunodeficiencies). Thirty-three datasets from the Gene Expression Omnibus, encompassing 1860 transcriptome profiles, were made available on the Gene Expression Browser (GXB), an online and open-source web application that allows for the query, visualization and annotation of metadata. The thematic compositions, disease categories, sample number and platforms of the collection are described. Ranked gene lists and sample grouping are used to facilitate data visualization/interpretation and are available online via GXB (http://ige.gxbsidra.org/dm3/geneBrowser/list). Dataset validation using associated publications showed good concordance in GXB gene expression trend and fold-change.

scholarly journals A curated collection of transcriptome datasets to investigate the molecular mechanisms of immunoglobulin E-mediated atopic diseases

2019 ◽  
Author(s):  
Susie S. Y. Huang ◽  
Fatima Al Ali ◽  
Sabri Boughorbel ◽  
Mohammed Toufiq ◽  
Damien Chaussabel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Web Application ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Immunoglobulin E ◽  
Gene Expression Omnibus ◽  
Atopic Diseases ◽  
Sample Number ◽  
Link Type ◽  
Good Concordance

ABSTRACTPrevalence of allergies has reached ~50% of industrialized populations and with children under ten being the most susceptible. However, the combination of the complexity of atopic allergy susceptibility/development and environmental factors has made identification of gene biomarkers challenging. The amount of publicly accessible transcriptomic data presents an unprecedented opportunity for mechanistic discoveries and validation of complex disease signatures across studies. However, this necessitates structured methodologies and visual tools for the interpretation of results. Here, we present a curated collection of transcriptomic datasets relevant to immunoglobin E (IgE)-mediated atopic diseases (ranging from allergies to primary immunodeficiencies). 30 datasets from the Gene Expression Omnibus (GEO), encompassing 1761 transcriptome profiles, were made available on the Gene Expression Browser (GXB), an online and open-source web application that allows for the query, visualization, and annotation of metadata. The thematic compositions, disease categories, sample number, and platforms of the collection are described. Ranked gene lists and sample grouping are used to facilitate data visualization/interpretation and are available online via GXB (http://ige.gxbsidra.org/dm3/geneBrowser/list). Dataset validation using associated publications showed good concordance in GXB gene expression trend and fold-change.Database URL: http://ige.gxbsidra.org/dm3/geneBrowser/list

scholarly journals Functions and clinical significance of KLRG1 in the development of lung adenocarcinoma and immunotherapy

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaodong Yang ◽  
Yuexin Zheng ◽  
Zhihai Han ◽  
Xiliang Zhang
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Killer Cell ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Normal Lung ◽  
Using Data ◽  
Low Expression

Abstract Background As a marker of differentiation, Killer cell lectin like receptor G1 (KLRG1) plays an inhibitory role in human NK cells and T cells. However, its clinical role remains inexplicit. This work intended to investigate the predictive ability of KLRG1 on the efficacy of immune-checkpoint inhibitor in the treatment of lung adenocarcinoma (LUAD), as well as contribute to the possible molecular mechanisms of KLRG1 on LUAD development. Methods Using data from the Gene Expression Omnibus, the Cancer Genome Atlas and the Genotype-Tissue Expression, we compared the expression of KLRG1 and its related genes Bruton tyrosine kinase (BTK), C-C motif chemokine receptor 2 (CCR2), Scm polycomb group protein like 4 (SCML4) in LUAD and normal lung tissues. We also established stable LUAD cell lines with KLRG1 gene knockdown and investigated the effect of KLRG1 knockdown on tumor cell proliferation. We further studied the prognostic value of the four factors in terms of overall survival (OS) in LUAD. Using data from the Gene Expression Omnibus, we further investigated the expression of KLRG1 in the patients with different responses after immunotherapy. Results The expression of KLRG1, BTK, CCR2 and SCML4 was significantly downregulated in LUAD tissues compared to normal controls. Knockdown of KLRG1 promoted the proliferation of A549 and H1299 tumor cells. And low expression of these four factors was associated with unfavorable overall survival in patients with LUAD. Furthermore, low expression of KLRG1 also correlated with poor responses to immunotherapy in LUAD patients. Conclusion Based on these findings, we inferred that KLRG1 had significant correlation with immunotherapy response. Meanwhile, KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD.

scholarly journals Investigation of the Mechanism of Complement System in Diabetic Nephropathy via Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Bojun Xu ◽  
Lei Wang ◽  
Huakui Zhan ◽  
Liangbin Zhao ◽  
Yuehan Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diabetic Nephropathy ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Topological Analysis ◽  
Gene Expression Omnibus ◽  
Complement Cascade ◽  
Hub Genes ◽  
Novel Biomarkers

Objectives. Diabetic nephropathy (DN) is a major cause of end-stage renal disease (ESRD) throughout the world, and the identification of novel biomarkers via bioinformatics analysis could provide research foundation for future experimental verification and large-group cohort in DN models and patients. Methods. GSE30528, GSE47183, and GSE104948 were downloaded from Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs). The difference of gene expression between normal renal tissues and DN renal tissues was firstly screened by GEO2R. Then, the protein-protein interactions (PPIs) of DEGs were performed by STRING database, the result was integrated and visualized via applying Cytoscape software, and the hub genes in this PPI network were selected by MCODE and topological analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to determine the molecular mechanisms of DEGs involved in the progression of DN. Finally, the Nephroseq v5 online platform was used to explore the correlation between hub genes and clinical features of DN. Results. There were 64 DEGs, and 32 hub genes were identified, enriched pathways of hub genes involved in several functions and expression pathways, such as complement binding, extracellular matrix structural constituent, complement cascade related pathways, and ECM proteoglycans. The correlation analysis and subgroup analysis of 7 complement cascade-related hub genes and the clinical characteristics of DN showed that C1QA, C1QB, C3, CFB, ITGB2, VSIG4, and CLU may participate in the development of DN. Conclusions. We confirmed that the complement cascade-related hub genes may be the novel biomarkers for DN early diagnosis and targeted treatment.

scholarly journals SMC4, CCNB1 and CKS1B as potential targets and new critical biomarkers for the prognosis of human bladder cancer

2021 ◽  
Author(s):  
Hongpeng Fang ◽  
Zhansen Huang ◽  
Xianzi Zeng ◽  
Jiaming Wan ◽  
Jieying Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Transcriptional Level ◽  
Hub Genes ◽  
Kaplan Meier ◽  
High Form

Abstract Background As a common malignant cancer of the urinary system, the precise molecular mechanisms of bladder cancer remain to be illuminated. The purpose of this study was to identify core genes with prognostic value as potential oncogenes for the diagnosis, prognosis or novel therapeutic targets of bladder cancer. Methods The gene expression profiles GSE3167 and GSE7476 were available from the Gene Expression Omnibus (GEO) database. Next, PPI network was built to filter the hub gene through the STRING database and Cytoscape software and GEPIA and Kaplan-Meier plotter were implemented. Frequency and type of hub genes and sub groups analysis were performed in cBioportal and ULCAN database. Finally,We used RT-qPCR to confirm our results. Results Totally, 251 DEGs were excavated from two datasets in our study. We only founded high expression of SMC4, TYMS, CCNB1, CKS1B, NUSAP1 and KPNA2 was associated with worse outcomes in bladder cancer patients and no matter from the type of mutation or at the transcriptional level of hub genes, the tumor showed a high form of expression. However, only the expression of SMC4,CCNB1and CKS1B remained changed between the cancer and the normal samples in our results of RT-qPCR. Conclusion In conclusion,These findings indicate that the SMC4,CCNB1 and CKS1B may serve as critical biomarkers in the development and poor prognosis.

scholarly journals Integrative In Silico and In Vitro Transcriptomics Analysis Revealed Gene Expression Changes and Oncogenic Features of Normal Cholangiocytes after Chronic Alcohol Exposure

2019 ◽  
Vol 20 (23) ◽  
pp. 5987
Author(s):  
Suthipong Chujan ◽  
Tawit Suriyo ◽  
Jutamaad Satayavivad
Keyword(s):  
Gene Expression ◽  
Rna Polymerase Ii ◽  
Molecular Mechanisms ◽  
Function Analysis ◽  
Alcohol Exposure ◽  
Gene Expression Omnibus ◽  
Regulation Of Transcription ◽  
Chronic Alcohol ◽  
Chronic Alcohol Exposure

Cholangiocarcinoma (CCA) is a malignant tumor originating from cholangiocyte. Prolonged alcohol consumption has been suggested as a possible risk factor for CCA, but there is no information about alcohol’s mechanisms in cholangiocyte. This study was designed to investigate global transcriptional alterations through RNA-sequencing by using chronic alcohol exposure (20 mM for 2 months) in normal human cholangiocyte MMNK-1 cells. To observe the association of alcohol induced CCA pathogenesis, we combined differentially expressed genes (DEGs) with computational bioinformatics of CCA by using publicly gene expression omnibus (GEO) datasets. For biological function analysis, Gene ontology (GO) analysis showed biological process and molecular function related to regulation of transcription from RNA polymerase II promoter, while cellular component linked to the nucleoplasm. KEGG pathway presented pathways in cancer that were significantly enriched. From KEGG result, we further examined the oncogenic features resulting in chronic alcohol exposure, enhanced proliferation, and migration through CCND-1 and MMP-2 up-regulation, respectively. Finally, combined DEGs were validated in clinical data including TCGA and immunohistochemistry from HPA database, demonstrating that FOS up-regulation was related to CCA pathogenesis. This study is the first providing more information and molecular mechanisms about global transcriptome alterations and oncogenic enhancement of chronic alcohol exposure in normal cholangiocytes.

OSkirc: a web tool for identifying prognostic biomarkers in kidney renal clear cell carcinoma

2019 ◽  
Vol 15 (27) ◽  
pp. 3103-3110 ◽  
Author(s):  
Longxiang Xie ◽  
Qiang Wang ◽  
Yifang Dang ◽  
Linna Ge ◽  
Xiaoxiao Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Carcinoma ◽  
Web Application ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
P Value ◽  
Survival Plot

Aim: To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). Patients & methods: A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. Results: One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan–Meier survival plot with hazard ratio and log-rank p-value. Conclusion: OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp

scholarly journals Identification of Novel Cancer Stem Cell Markers in Glioblastoma by Comparing Tumor Cells with Stem-cell-like Cell Lines

2021 ◽  
Vol 11 (2) ◽  
pp. 1567-1583
Author(s):  
Divya G.
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Tumor Cells ◽  
Cell Lines ◽  
Molecular Mechanisms ◽  
Cell Attachment ◽  
Microarray Dataset ◽  
Gene Expression Omnibus ◽  
Stem Cell Markers ◽  
Cancer Stem Cell Markers

Aim. The aim of this study is to identify differential gene expression for glioblastoma tumor cells, normoxic and hypoxic glioblastoma stem-like cell lines. Finding the upregulated and downregulated gene and pathway interactions. Analysis to find the differential expression genes and pathway interactions. Materials and methods. The gene expression profiling data from the microarray dataset GSE45117 from the Gene Expression Omnibus (GEO) database, as well as differentially expressed genes (DEGs) between the 2 categories, are used in this analysis. 4 Samples of Glioblastoma tumors were considered as group 1 and 4 samples of normoxic and Hypoxic glioblastoma stem-like cell lines were considered as group 2 in the GEO2R web tool that has been used to screen them. Results. The gene-gene interactions among the DEGs and the GGI network with 37 nodes and 13 edges. The stem-cell-like cell lines showed lower expression of endothelin-related genes such as EDN3 and EDNRA along with dysregulation of enzymes such as PDK1, PGK1 which points to dysregulation of cellular respiratory pathways. This effect in consensus with under expression of cell attachment genes such as COL2A1, COL5A2, COL15A1 denotes a strong shift toward metastasis. Conclusion. Thus, a computational pipeline for identifying the significant genes and pathways involved in the glioblastoma tumors and glioblastoma stem-like cell lines. This study provides a path towards discovering potential leads for the treatment of glioblastoma and aids in comprehending the underlying novel molecular mechanisms.

scholarly journals Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Md. Rakibul Islam ◽  
Lway Faisal Abdulrazak ◽  
Mohammad Khursheed Alam ◽  
Bikash Kumar Paul ◽  
Kawsar Ahmed ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
New Treatments

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log   fold   change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

scholarly journals Regulatory T Cell-Related Gene Biomarkers in the Deterioration of Atherosclerosis

2021 ◽  
Vol 8 ◽  
Author(s):  
Meng Xia ◽  
Qingmeng Wu ◽  
Pengfei Chen ◽  
Cheng Qian
Keyword(s):  
Gene Expression ◽  
Cardiovascular Events ◽  
Molecular Mechanisms ◽  
Inflammatory Responses ◽  
Expression Patterns ◽  
Interaction Network ◽  
Gene Signature ◽  
Smooth Muscle Contraction ◽  
Gene Expression Omnibus ◽  
Scoring Method

Background: Regulatory T cells (Tregs) have shown to be protective against the development of atherosclerosis, a major pathological cause for cardiovascular events. Here, we aim to explore the roles of Tregs-related genes in atherosclerosis deterioration.Methods and Results: We downloaded the gene expression profile of 29 atherosclerotic samples from the Gene Expression Omnibus database with an accession number of GSE28829. The abundance of Tregs estimated by the CIBERSORT algorithm was negatively correlated with the atherosclerotic stage. Using the limma test and correlation analysis, a total of 159 differentially expressed Tregs-related genes (DETregRGs) between early and advanced atherosclerotic plaques were documented. Functional annotation analysis using the DAVID tool indicated that the DETregRGs were mainly enriched in inflammatory responses, immune-related mechanisms, and pathways such as complement and coagulation cascades, platelet activation, leukocyte trans-endothelial migration, vascular smooth muscle contraction, and so on. A protein-protein interaction network of the DETregRGs was then constructed, and five hub genes (PTPRC, C3AR1, CD53, TLR2, and CCR1) were derived from the network with node degrees ≥20. The expression patterns of these hub DETregRGs were further validated in several independent datasets. Finally, a single sample scoring method was used to build a gene signature for the five DETregRGs, which could distinguish patients with myocardial infarction from those with stable coronary disease.Conclusion: The results of this study will improve our understanding about the Tregs-associated molecular mechanisms in the progression of atherosclerosis and facilitate the discovery of novel biomarkers for acute cardiovascular events.

scholarly journals Mapping eQTLs With RNA-Seq Reveals Novel SLE Susceptibility Genes, Non-Coding RNAs, and Alternative-Splicing Events That Are Concealed Using Microarrays

2016 ◽  
Author(s):  
Christopher A. Odhams ◽  
Andrea Cortini ◽  
Lingyan Chen ◽  
Amy L. Roberts ◽  
Ana Vinuela ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lupus Erythematosus ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Splice Junction ◽  
Susceptibility Genes ◽  
Eqtl Analysis ◽  
Rna Seq ◽  
Control Of Gene Expression ◽  
Non Coding Rnas

AbstractStudies attempting to functionally interpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed microarrays to quantify gene-expression. RNA-Seq has the potential to discover a more comprehensive set of eQTLs and illuminate the underlying molecular consequence. We examine the functional outcome of 39 variants associated with Systemic Lupus Erythematosus (SLE) through integration of GWAS and eQTL data from the TwinsUK microarray and RNA-Seq cohort in lymphoblastoid cell lines. We use conditional analysis and a Bayesian colocalisation method to provide evidence of a shared causal-variant, then compare the ability of each quantification type to detect disease relevant eQTLs and eGenes. We discovered a greater frequency of candidate-causal eQTLs using RNA-Seq, and identified novel SLE susceptibility genes that were concealed using microarrays (e.g. NADSYN1, SKP1, and TCF7). Many of these eQTLs were found to influence the expression of several genes, suggesting risk haplotypes may harbour multiple functional effects. We pinpointed eQTLs modulating expression of four non-coding RNAs; three of which were replicated in whole-blood. Novel SLE associated splicing events were identified in the T-reg restricted transcription factor, IKZF2, the autophagy-related gene WDFY4, and the redox coenzyme NADSYN1, through asQTL mapping using the Geuvadis cohort. We have significantly increased our understanding of the genetic control of gene-expression in SLE by maximising the leverage of RNA-Seq and performing integrative GWAS-eQTL analysis against gene, exon, and splice-junction quantifications. In doing so, we have identified novel SLE candidate genes and specific molecular mechanisms that will serve as the basis for targeted follow-up studies.

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