scholarly journals Identification of Differentially Expressed Gene after Femoral Fracture via Microarray Profiling

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Donggen Zhong
Keyword(s):  
Gene Expression ◽  
Calcium Signaling ◽  
Signaling Pathway ◽  
Femoral Fracture ◽  
Differentially Expressed Gene ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Calcium Signaling Pathway

We aimed to investigate differentially expressed genes (DEGs) in different stages after femoral fracture based on rat models, providing the basis for the treatment of sport-related fractures. Gene expression data GSE3298 was downloaded from Gene Expression Omnibus (GEO), including 16 chips. All femoral fracture samples were classified into earlier fracture stage and later fracture stage. Total 87 DEGs simultaneously occurred in two stages, of which 4 genes showed opposite expression tendency. Out of the 4 genes,RestandCst8were hub nodes in protein-protein interaction (PPI) network. The GO (Gene Ontology) function enrichment analysis verified that nutrition supply related genes were enriched in the earlier stage and neuron growth related genes were enriched in the later stage. Calcium signaling pathway was the most significant pathway in earlier stage; in later stage, DEGs were enriched into 2 neurodevelopment-related pathways. Analysis of Pearson's correlation coefficient showed that a total of 3,300 genes were significantly associated with fracture time, none of which was overlapped with identified DEGs. This study suggested thatRestandCst8might act as potential indicators for fracture healing. Calcium signaling pathway and neurodevelopment-related pathways might be deeply involved in bone healing after femoral fracture.

Prognostic Values and Prospective Pathway Signaling of miR-30a in Ovarian Cancer: A Study Based on Gene Expression Omnibus and Bioinformatics Analysis

2020 ◽  
Author(s):  
Weijia Lu ◽  
Yunyu Wu ◽  
CanXiong Lu ◽  
Ting Zhu ◽  
ZhongLu Ren ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Target Genes ◽  
Ovarian Tissue ◽  
Differentially Expressed Gene ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Public Data

Abstract Objective MicroRNAs (MiRNAs) is considered to play an important role in the occurrence and development of ovarian cancer(OC). Although miRNAs has been widely recognized in ovarian cancer, the role of hsa-miR-30a-5p (miR-30a) in OC has not been fully elucidated. Methods Through the analysis of public data sets in Gene Expression Omnibus (GEO) database and literature review, the significance of miR-30a expression in OC is evaluated. Three mRNA datasets of OC and normal ovarian tissue, GSE14407, GSE18520 and GSE36668, were downloaded from GEO to find the differentially expressed gene (DEG). Then the target genes of hsa-miR-30a-5p were predicted by miRWALK3.0 and TargetScan. Then, the gene overlap between DEG and the predicted target genes of miR-30a in OC was analyzed by Gene Ontology (GO) enrichment analysis. Protein-protein interaction (PPI) network was constructed by STRING and Cytoscape, and the effect of HUB gene on the prognosis of OC was analyzed. Results A common pattern of up-regulation of miR-30a in OC was found. A total of 225 DEG, were identified, both OC-related and miR-30a-related. Many DEG are enriched in the interactions of intracellular matrix tissue, ion binding and biological process regulation. Among the 10 major Hub genes analyzed by PPI, five Hub genes were significantly related to the overall poor survival of OC patients, in which the low expression of ESR1 ,MAPK10, Tp53 and the high expression of YKT ,NSF were related to poor prognosis of OC.

scholarly journals Microarray analysis of gene expression in mouse aorta reveals role of the calcium signaling pathway in control of atherosclerosis susceptibility

2009 ◽  
Vol 296 (5) ◽  
pp. H1336-H1343 ◽  
Author(s):  
Zuobiao Yuan ◽  
Toru Miyoshi ◽  
Yongde Bao ◽  
Jason P. Sheehan ◽  
Alan H. Matsumoto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Calcium Signaling ◽  
Signaling Pathway ◽  
Oxidized Ldl ◽  
Atherosclerotic Lesion ◽  
Differentially Expressed ◽  
Monocyte Chemoattractant Protein 1 ◽  
Monocyte Chemoattractant ◽  
Monocyte Chemoattractant Protein ◽  
Calcium Signaling Pathway

Inbred mouse strains C57BL/6J (B6) and C3H/HeJ (C3H) exhibit a marked difference in atherosclerotic lesion formation when deficient in apolipoprotein E (apoE−/−), and the arterial wall has been identified as a source of the difference in atherosclerosis susceptibility. In the present study, differences in gene expression in aortic walls of the two strains were analyzed by microarrays. Total RNA was extracted from the aorta of 6-wk-old female B6 and C3H apoE−/− mice fed a chow or Western diet. There were 1,514 genes in chow fed mice and 590 genes in Western fed mice that were found to be differentially expressed between the two strains. Pathway analysis of differentially expressed genes suggested a role for the calcium signaling pathway in regulating atherosclerosis susceptibility. Oxidized LDL (oxLDL) induced a dose-dependent rise in cytosolic calcium levels in B6 endothelial cells. oxLDL-induced monocyte chemoattractant protein-1 production was inhibited by pretreatment with calcium chelator EGTA or intracellular calcium trapping compound BAPTA, indicating that calcium ions mediate the effect of oxLDL on monocyte chemoattractant protein-1 induction. The present findings demonstrate involvement of the calcium signaling pathway in the inflammatory process of atherogenesis.

scholarly journals Differentially expressed genes SNRPC and PRPF38A are potential biomarkers candidates for osteosarcoma

2020 ◽  
Author(s):  
Sheng Chang ◽  
Yang Cao
Keyword(s):  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Osteogenic Sarcoma ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Potential Biomarkers

Abstract Background: Osteosarcoma (osteogenic sarcoma, OS) is a primary cause of morbidity and mortality and is associated with poor prognosis in the field of orthopedic. Globally, rates of OS are highest among 15 to 25-year-old adolescent. However, the mechanism of gene regulation and signaling pathway is unknown. Material and Methods: GSE9508, including 34 OS samples and 5 non-malignant bone samples, was gained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were picked out by GEO2R online R soft tool. Furthermore, the protein-protein interaction (PPI) network between the DEGs was molded utilizing STRING online software. Afterward, PPI network of DEGs was constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were carried out on DAVID online tool and visualized via cytoscape software. Subsequently, module analysis of PPI was performed by using MCODE app. What’s more, prognosis-related genes were screened by using online databases including GEPIA, UALCAN and cBioPortal databases. Results: Totally, 671 DEGs were picked out, including 501 up-regulated genes and 170 down-regulated genes. Moreover, 22 hub genes were identified to be significantly expressed in PPI network (16 up-regulated and 6 down-regulated). We found that spliceosome signaling pathway may provide a potential target in OS. Furthermore, on the basis of common crucial pathway, PRPF38A and SNRPC were closely associated with spliceosome. Conclusion: This study showed that SNRPC and PRPF38A are potential biomarkers candidates for osteosarcoma.

scholarly journals The Bioinformatics Analysis of Aldosterone-Producing Adenoma and Verification of Differentially Expressed Genes

2021 ◽  
Author(s):  
Yinjie Gao ◽  
Xiaosen Ma ◽  
Huiping Wang ◽  
Yunying Cui ◽  
Yushi Zhang ◽  
...  
Keyword(s):  
Calcium Signaling ◽  
Signaling Pathway ◽  
Quantitative Pcr ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Ion Homeostasis ◽  
Differentially Expressed Gene ◽  
Differentially Expressed ◽  
Mrna Levels ◽  
Calcium Signaling Pathway

Abstract BackgroundPrevious studies have investigated the transcriptional modulations of aldosterone overproduction of aldosterone-producing adenomas (APAs), and several potential genes were found with high expressions. PurposeWe aimed to systematically study the genes and pathways associated with molecular mechanism underlying APA by bioinformatics analysis and experimental validation for the expression profile. MethodsThis study was performed based on three gene expression profiles (GSE64957, GSE8514, and GSE60042). Differentially expressed gene (DEG) investigation, function and pathway enrichment, as well as protein-protein interaction (PPI) network, were performed by the bioinformatics analysis. For the validation with quantitative PCR, tissues from 11 patients with non-functioning adrenal adenoma (NFA) and 13 with APA were included in our cohort. ResultsIn this study, the bioinformatics analysis was performed and 182 upregulated and 88 downregulated DEGs were identified. As expected, the upregulated DEGs were primarily involved in calcium ion homeostasis (GO: 0055074, n = 3, p = 2.00X10-4). In the KEGG pathway analysis, calcium signaling pathway (hsa04020, n = 8, p= 4.38X10-6) and the aldosterone synthesis and secretion (hsa04925, n = 6, p = 8.73X10-6) were enriched. Moreover, quantitative PCR was performed to detect the expression of 7 upregulated genes (PCP4, ATP2A3, CYP11B2, CLCN5, HTR4, VDR and AQP2) among the intersection of DEGs. The mRNA levels of CYP11B2, HTR4 and AQP2 were significantly increased in APA samples compared to NFA (24.420 folds of NFA, p<0.001, 3.753 folds of NFA, p=0.002 and 11.487 folds of NFA, p=0.018).ConclusionIn summary, the present study showed several candidate genes with high expression from bioinformatics analysis and our cohort. And the DEGs were enriched in aldosterone synthesis and secretion and calcium signaling pathway as expected.

scholarly journals The Bioinformatics Analysis of Aldosterone-Producing Adenoma and Verification of Differentially Expressed Genes

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yinjie Gao ◽  
Xiaosen Ma ◽  
Huiping Wang ◽  
Yunying Cui ◽  
Yushi Zhang ◽  
...  
Keyword(s):  
Calcium Signaling ◽  
Signaling Pathway ◽  
Quantitative Pcr ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Differentially Expressed Gene ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Mrna Levels ◽  
Calcium Signaling Pathway

Purpose. Previous studies have investigated the transcriptional modulations of aldosterone overproduction of aldosterone-producing adenomas (APAs). We aimed to systematically study the genes and pathways associated with molecular mechanism underlying APA by bioinformatics analysis and experimental validation for the expression profile. Methods. This study was performed based on three gene expression profiles (GSE64957, GSE8514, and GSE60042). Differentially expressed gene (DEG) investigation, function and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed by the bioinformatics analysis. For the validation with quantitative PCR, tissues from 11 patients with nonfunctioning adrenal adenoma (NFA) and 13 with APA were included in our cohort. Results. In this study, the bioinformatics analysis was performed and 182 upregulated and 88 downregulated DEGs were identified. As expected, the upregulated DEGs were primarily involved in calcium ion homeostasis ( p  = 2.00X10−4). In the KEGG pathway analysis, calcium signaling pathway ( p  = 4.38X10−6) and the aldosterone synthesis and secretion ( p  = 8.73X10−6) were enriched. Moreover, quantitative PCR was performed to detect the expression of 7 upregulated genes (PCP4, ATP2A3, CYP11B2, CLCN5, HTR4, VDR, and AQP2) among the intersection of DEGs. The mRNA levels of CYP11B2, HTR4, and AQP2 were significantly increased in APA samples compared to NFA (24.420 folds of NFA, p  < 0.001; 3.753 folds of NFA, p  = 0.002; and 11.487 folds of NFA, p  = 0.018). Conclusion. In summary, the present study showed several candidate genes with high expression from bioinformatics analysis and our cohort. Also, the DEGs were enriched in aldosterone synthesis and secretion and calcium signaling pathway as expected.

Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways

2020 ◽  
Vol 26 (29) ◽  
pp. 3619-3630
Author(s):  
Saumya Choudhary ◽  
Dibyabhaba Pradhan ◽  
Noor S. Khan ◽  
Harpreet Singh ◽  
George Thomas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Gene ◽  
Therapeutic Targets ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Keratinocyte Differentiation ◽  
Hub Genes ◽  
Lesional Skin ◽  
Ncbi Gene Expression Omnibus

Background: Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive. Objective: To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis. Method: The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE. Results: A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene. Conclusion: The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis.

scholarly journals Identification of Key Genes and miRNAs in Osteosarcoma Patients with Chemoresistance by Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Binbin Xie ◽  
Yiran Li ◽  
Rongjie Zhao ◽  
Yuzi Xu ◽  
Yuhui Wu ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Search Tool ◽  
Poor Outcomes

Chemoresistance is a significant factor associated with poor outcomes of osteosarcoma patients. The present study aims to identify Chemoresistance-regulated gene signatures and microRNAs (miRNAs) in Gene Expression Omnibus (GEO) database. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) included positive regulation of transcription, DNA-templated, tryptophan metabolism, and the like. Then differentially expressed genes (DEGs) were uploaded to Search Tool for the Retrieval of Interacting Genes (STRING) to construct protein-protein interaction (PPI) networks, and 9 hub genes were screened, such as fucosyltransferase 3 (Lewis blood group) (FUT3) whose expression in chemoresistant samples was high, but with a better prognosis in osteosarcoma patients. Furthermore, the connection between DEGs and differentially expressed miRNAs (DEMs) was explored. GEO2R was utilized to screen out DEGs and DEMs. A total of 668 DEGs and 5 DEMs were extracted from GSE7437 and GSE30934 differentiating samples of poor and good chemotherapy reaction patients. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to perform GO and KEGG pathway enrichment analysis to identify potential pathways and functional annotations linked with osteosarcoma chemoresistance. The present study may provide a deeper understanding about regulatory genes of osteosarcoma chemoresistance and identify potential therapeutic targets for osteosarcoma.

scholarly journals Bioinformatics Analysis of the Molecular Mechanism and Potential Treatment Target of Ankylosing Spondylitis

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Fanyan Meng ◽  
Ningna Du ◽  
Daoming Xu ◽  
Li Kuai ◽  
Lanying Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ankylosing Spondylitis ◽  
Molecular Mechanism ◽  
Soft Tissues ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Expression Omnibus ◽  
Treatment Targets ◽  
Protein Protein Interaction

Ankylosing spondylitis (AS) is an autoimmune disease that mainly affects the spinal joints, sacroiliac joints, and adjacent soft tissues. We conducted bioinformatics analysis to explore the molecular mechanism related to AS pathogenesis and uncover novel potential molecular targets for the treatment of AS. The profiles of GSE25101, containing gene expression data extracted from the blood of 16 AS patients and 16 matched controls, were acquired from the Gene Expression Omnibus (GEO) database. The background correction and standardization were carried out utilizing the transcript per million (TPM) method. After analysis of AS patients and the normal groups, we identified 199 differentially expressed genes (DEGs) with upregulation and 121 DEGs with downregulation by the limma R package. The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis revealed that the DEGs with upregulation were mainly associated with spliceosome, ribosome, RNA-catabolic process, electron transport chain, etc. And the DEGs with downregulation primarily participated in T cell-associated pathways and processes. After analysis of the protein-protein interaction (PPI) network, our data revealed that the hub genes, comprising MRPL13, MRPL22, LSM3, COX7A2, COX7C, EP300, PTPRC, and CD4, could be the treatment targets in AS. Our data furnish new hints to uncover the features of AS and explore more promising treatment targets towards AS.

scholarly journals Identification of microRNAs and genes as biomarkers of atrial fibrillation using a bioinformatics approach

2019 ◽  
Vol 47 (8) ◽  
pp. 3580-3589 ◽  
Author(s):  
Yingyuan Li ◽  
Wulin Tan ◽  
Fang Ye ◽  
Faling Xue ◽  
Shaowei Gao ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Control Groups ◽  
Protein Protein Interaction ◽  
Differentially Expressed Mirnas ◽  
Software Modules ◽  
And Control

Objective We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3. Conclusion The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.

Uncovering potential lncRNAs and nearby mRNAs in systemic lupus erythematosus from the Gene Expression Omnibus dataset

Epigenomics ◽  
2019 ◽  
Vol 11 (16) ◽  
pp. 1795-1809 ◽  
Author(s):  
Haiyu Cao ◽  
Dong Li ◽  
Huixiu Lu ◽  
Jing Sun ◽  
Haibin Li
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Noncoding Rnas ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Systemic Lupus ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Aim: The aim of this study was to find potential differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in systemic lupus erythematosus. Materials & methods: Differentially expressed lncRNAs and mRNAs were obtained in the Gene Expression Omnibus dataset. Functional annotation of differentially expressed mRNAs was performed, followed by protein–protein interaction network analysis. Then, the interaction network of lncRNA-nearby targeted mRNA was built. Results: Several interaction pairs of lncRNA-nearby targeted mRNA including NRIR-RSAD2, RP11-153M7.5-TLR2, RP4-758J18.2-CCNL2, RP11-69E11.4-PABPC4 and RP11-496I9.1-IRF7/ HRAS/ PHRF1 were identified. Measles and MAPK were significantly enriched signaling pathways of differentially expressed mRNAs. Conclusion: Our study identified several differentially expressed lncRNAs and mRNAs. And their interactions may play a crucial role in the process of systemic lupus erythematosus.

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