scholarly journals Comparative pathway enrichment analysis in gastrointestinal cell lines Caco-2, HT-29, HEPG2, and colon fibroblasts using a custom expression panel for tight-junction and cytoskeletal regulatory genes

2019 ◽  
Author(s):  
JM Robinson
Keyword(s):  
Gene Expression ◽  
Comparative Analysis ◽  
Tight Junction ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Intestinal Epithelial ◽  
Expression Data ◽  
Pathway Enrichment ◽  
Ht 29

AbstractThis brief report details results from a comparative analysis of Nanostring expression data between cell lines HEPG2, Caco-2, HT-29, and colon fibroblasts. Raw and normalized data are available publicly in the NCBI GEO/Bioproject databases. Results identify cell-line specific variations in gene expression relevant to intestinal epithelial function.

scholarly journals BNrich: A Bayesian network approach to the pathway enrichment analysis

2020 ◽  
Author(s):  
Samaneh Maleknia ◽  
Ali Sharifi-Zarchi ◽  
Vahid Rezaei Tabar ◽  
Mohsen Namazi ◽  
Kaveh Kavousi
Keyword(s):  
Gene Expression ◽  
Bayesian Network ◽  
Signaling Pathway ◽  
Gene Expression Data ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Data ◽  
Pathway Enrichment ◽  
Topological Features ◽  
Biological Studies

AbstractMotivationOne of the most popular techniques in biological studies for analyzing high throughput data is pathway enrichment analysis (PEA). Many researchers apply the existing methods without considering the topology of pathways or at least they have overlooked a significant part of the structure, which may reduce the accuracy and generalizability of the results. Developing a new approach while considering gene expression data and topological features like causal relations regarding edge directions will help the investigators to achieve more accurate results.ResultsWe proposed a new pathway enrichment analysis based on Bayesian network (BNrich) as an approach in PEA. To this end, the cycles were eliminated in 187 KEGG human signaling pathways concerning intuitive biological rules and the Bayesian network structures were constructed. The constructed networks were simplified by the Least Absolute Shrinkage Selector Operator (LASSO), and their parameters were estimated using the gene expression data. We finally prioritize the impacted pathways by Fisher’s Exact Test on significant parameters. Our method integrates both edge and node related parameters to enrich modules in the affected signaling pathway network. In order to evaluate the proposed method, consistency, discrimination, false positive rate and empirical P-value criteria were calculated, and the results are compared to well-known enrichment methods such as signaling pathway impact analysis (SPIA), bi-level meta-analysis (BLMA) and topology-based pathway enrichment analysis (TPEA).AvailabilityThe R package is available on carn.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

Identification of differential gene expression related to epirubicin-induced cardiomyopathy in breast cancer patients

2019 ◽  
Vol 39 (4) ◽  
pp. 393-401 ◽  
Author(s):  
J Peng ◽  
Z Wang ◽  
Y Li ◽  
D Lv ◽  
X Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Enrichment Analysis ◽  
Global Gene Expression ◽  
Pathway Enrichment Analysis ◽  
Breast Cancer Patients ◽  
Chlorophyll Metabolism ◽  
Pathway Enrichment ◽  
Before And After

Background: Epirubicin is a potent chemotherapeutic agent for the treatment of breast cancer. However, it may lead to cardiotoxicity and cardiomyopathy, and no reliable biomarker was available for the early prediction of epirubicin-induced cardiomyopathy. Methods: Global gene expression changes of peripheral blood cells were studied using high-throughput RNA sequencing in three pair-matched breast cancer patients (patients who developed symptomatic cardiomyopathy paired with patients who did not) before and after the full session of epirubicin-based chemotherapy. Functional analysis was conducted using gene ontology and pathway enrichment analysis. Results: We identified 13 significantly differentially expressed genes between patients who developed symptomatic epirubicin-induced cardiomyopathy and their paired control who did not. Among them, the upregulated Bcl-associated X protein was related to “apoptosis,” while the downregulated 5′-aminolevulinate synthase 2 (ALAS2) was related to both “glycine, serine, and threonine metabolism” and “porphyrin and chlorophyll metabolism” in pathway enrichment analysis. Conclusions: ALAS2 and the metabolic pathways which were involved may play an important role in the development of epirubicin-induced cardiomyopathy. ALAS2 may be useful as an early biomarker for epirubicin-induced cardiotoxicity detection.

MFN2 might be a risk factor for lung adenocarcinoma.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13007-e13007
Author(s):  
Yuqing Lou ◽  
Yanwei Zhang ◽  
Jianlin Xu ◽  
Ping Gu ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Lung Adenocarcinoma ◽  
A549 Cells ◽  
Enrichment Analysis ◽  
Tumor Formation ◽  
Normal Lung ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Functional Pathway

e13007 Background: Genetic mutations in Mitofusin-2(MFN2) interrupt mitochondrial fusion and cause the untreatable neurodegenerative condition Charcot-Marie-Tooth disease type 2A( Nature, December 2016). MFN2 was initially identified as a hypertension-associated gene and implicated in the pathogenesis of multiple cancer types. However, underlying mechanisms of MFN2 in lung adenocarcinoma was unclear. Methods: MFN2 expression at protein level was examined in 30 pair lung adenocarcinoma/adjacent normal lung samples with immunohistochemistry staining. Then MFN2 knocked down in human lung adenocarcinoma cells A549 with lentiviral-mediated shRNA strategy. The effects of MFN2 knockdown on cell proliferation, cell cycle process, cell migration and invasion was investigated in A549 cells. MFN2-knockdown induced gene expression changes was analyzed by microarray assay and then functional pathway enrichment analysis was performed to identify critical pathways involved in MFN2-mediated lung adenocarcinoma development. The expression changes of downstream factors were determined by western blot. Furthermore, tumor models in nude mice were generated. Tumor formation and progression in these mice were analyzed. Results: As compared to adjacent normal lung tissues, MFN2 expression was significantly higher in lung adenocarcinoma tissues with positive MFN2 signals in 90% (27/30) lung adenocarcinoma tissues and only in 26.7% (8/30) adjacent normal tissues. Furthermore, MFN2 knockdown inhibited cell proliferation, induced cell cycle arrest and blocked invasion behavior in A549 cells. MFN2-knockdown induced gene expression changes in A549 cells was analyzed by microarray assay. Functional pathway enrichment analysis revealed that 6 pathways were enriched in deregulated genes including Cell cycle, DNA replication, ECM-receptor interaction, Focal adhesion, MAPK signaling pathway and Chemokine signaling pathway. Downregulation of RAP1A and upregulation of RALB and ITGA2 identified in MFN2-knockdown cells by microarray analysis were confirmed by western blot. In vivo, tumor formation and progression in nude mice showed that MFN2 knockdown reduced tumorigenesis of A549 cells. Conclusions: MFN2 overexpression run a risk of lung adenocarcinoma.

scholarly journals SARS-CoV-2 Infections - Gene Expression Omnibus (GEO) Data Mining, Pathway Enrichment Analysis, and Prediction of Repurposable Drugs/Compounds

2020 ◽  
Author(s):  
Srilakshmi Chaparala ◽  
Carrie L Iwema ◽  
Ansuman Chattopadhyay
Keyword(s):  
Gene Expression ◽  
Oxidative Phosphorylation ◽  
Mitochondrial Dysfunction ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Host Cells ◽  
In Vivo Studies ◽  
Pathway Enrichment Analysis ◽  
Gene Expressions ◽  
Pathway Enrichment

The COVID-19 global pandemic has created dire consequences with an alarming rate of morbidity and mortality. There are not yet vaccine or efficacious treatment options to combat the causative SARS-CoV-2 infection. This paper describes the identification of potentially repurposable drugs for COVID-19 treatment by conducting pathway enrichment analysis on publicly available Gene Expression Omnibus datasets. We first determined SARS-CoV-2 infection-induced alterations of host gene expressions and pathways. We then identified drugs or compounds that target and counter virus-triggered cellular perturbations, suggesting their potential repurposing for COVID-19 treatment. The key findings are that SARS-CoV-2 infection in host cells induces mitochondrial dysfunction, inhibits oxidative phosphorylation, and activates several immune response and pro-inflammatory pathways. Triptolide, the major bioactive component of a traditional Chinese medicine herb, may rescue mitochondrial dysfunction by activating oxidative phosphorylation. Further in vitro and in vivo studies are necessary to verify these results prior to clinical application.

scholarly journals Novel Biomarker MicroRNAs for Subtyping of Acute Coronary Syndrome: A Bioinformatics Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yujie Zhu ◽  
Yuxin Lin ◽  
Wenying Yan ◽  
Zhandong Sun ◽  
Zhi Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Coronary Syndrome ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Biological Processes ◽  
Pathway Enrichment ◽  
Coronary Syndrome ◽  
Life Threatening

Acute coronary syndrome (ACS) is a life-threatening disease that affects more than half a million people in United States. We currently lack molecular biomarkers to distinguish the unstable angina (UA) and acute myocardial infarction (AMI), which are the two subtypes of ACS. MicroRNAs play significant roles in biological processes and serve as good candidates for biomarkers. In this work, we collected microRNA datasets from the Gene Expression Omnibus database and identified specific microRNAs in different subtypes and universal microRNAs in all subtypes based on our novel network-based bioinformatics approach. These microRNAs were studied for ACS association by pathway enrichment analysis of their target genes. AMI and UA were associated with 27 and 26 microRNAs, respectively, nine of them were detected for both AMI and UA, and five from each subtype had been reported previously. The remaining 22 and 21 microRNAs are novel microRNA biomarkers for AMI and UA, respectively. The findings are then supported by pathway enrichment analysis of the targets of these microRNAs. These novel microRNAs deserve further validation and will be helpful for personalized ACS diagnosis.

scholarly journals Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jia-qi Wu ◽  
Lin-bo Mao ◽  
Ling-feng Liu ◽  
Yong-mei Li ◽  
Jian Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Osteogenic Differentiation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Key Genes

Abstract Background The purpose of present study was to identify the differentially expressed genes (DEGs) associated with BMP-9-induced osteogenic differentiation of mesenchymal stem cells (MSCs) by using bioinformatics methods. Methods Gene expression profiles of BMP-9-induced MSCs were compared between with GFP-induced MSCs and BMP-9-induced MSCs. GSE48882 containing two groups of gene expression profiles, 3 GFP-induced MSC samples and 3 from BMP-9-induced MSCs, was downloaded from the Gene Expression Omnibus (GEO) database. Then, DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in cytoplasm, nucleus, and extracellular exosome signaling pathway. Results A total of 1967 DEGs (1029 upregulated and 938 downregulated) were identified from GSE48882 datasets. R/Bioconductor package limma was used to identify the DEGs. Further analysis revealed that there were 35 common DEGs observed between the samples. GO function and KEGG pathway enrichment analysis, among which endoplasmic reticulum, protein export, RNA transport, and apoptosis was the most significant dysregulated pathway. The result of protein-protein interaction (PPI) network modules demonstrated that the Hspa5, P4hb, Sec61a1, Smarca2, Pdia3, Dnajc3, Hyou1, Smad7, Derl1, and Surf4 were the high-degree hub nodes. Conclusion Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in BMP-9 induced MSCs, which could improve our understanding of the key genes and pathways for BMP-9-induced osteogenic of MSCs.

scholarly journals Nodes with high centrality in protein interaction networks are responsible for driving signaling pathways in diabetic nephropathy

PeerJ ◽  
2015 ◽  
Vol 3 ◽  
pp. e1284 ◽  
Author(s):  
Maryam Abedi ◽  
Yousof Gheisari
Keyword(s):  
Gene Expression ◽  
Diabetic Nephropathy ◽  
Signaling Pathways ◽  
Protein Interaction ◽  
Enrichment Analysis ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Pathway Enrichment Analysis ◽  
Complex Disorders ◽  
Pathway Enrichment

In spite of huge efforts, chronic diseases remain an unresolved problem in medicine. Systems biology could assist to develop more efficient therapies through providing quantitative holistic sights to these complex disorders. In this study, we have re-analyzed a microarray dataset to identify critical signaling pathways related to diabetic nephropathy. GSE1009 dataset was downloaded from Gene Expression Omnibus database and the gene expression profile of glomeruli from diabetic nephropathy patients and those from healthy individuals were compared. The protein-protein interaction network for differentially expressed genes was constructed and enriched. In addition, topology of the network was analyzed to identify the genes with high centrality parameters and then pathway enrichment analysis was performed. We found 49 genes to be variably expressed between the two groups. The network of these genes had few interactions so it was enriched and a network with 137 nodes was constructed. Based on different parameters, 34 nodes were considered to have high centrality in this network. Pathway enrichment analysis with these central genes identified 62 inter-connected signaling pathways related to diabetic nephropathy. Interestingly, the central nodes were more informative for pathway enrichment analysis compared to all network nodes and also 49 differentially expressed genes. In conclusion, we here show that central nodes in protein interaction networks tend to be present in pathways that co-occur in a biological state. Also, this study suggests a computational method for inferring underlying mechanisms of complex disorders from raw high-throughput data.

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