scholarly journals A competing endogenous RNA mechanism in glioblastoma is investigated by bioinformatics analysis

2020 ◽  
Author(s):  
Jinsheng Wang ◽  
Yutao Wang ◽  
Lei Gao ◽  
Yuhua Zhao ◽  
Junhua Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Lupus Erythematosus ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Dendritic Cell Maturation ◽  
Vital Role ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
P53 Signaling

Abstract Background Glioblastoma (GBM) is the most aggressive and most lethal primary malignant brain tumor, the 5-year survival rate of which is less than 5%. Novel potential molecular and mechanism of GBM need to investigate.Materials and methods Microarray data of GSE15824 was downloaded from GEO. Differentially expressed genes and lncRNAs were screened by Limma package in R studio, and pathway enrichment analysis was performed by clusterprofiler package in R studio and IPA. The ceRNA mechanism was analyzed and predicted by several kinds of online public databases.ResultsThere were 567 differentially expressed genes and 121 differentially expressed lncRNAs in GBM. And differentially expressed genes were mainly enriched in Tuberculosis, Staphylococcus aureus infection, Systemic lupus erythematosus, Basal cell carcinoma, TGF-beta signaling pathway and p53 signaling pathway. Besides, Neuroinflammation signaling pathway, Role of NFAT in regulation of the immune response, and Dendritic cell maturation were significantly activated in GBM. According to the analysis of target miRNAs of SEM4D and OSER1-AS1, a possible ceRNA mechanism OSER1-AS1/hsa-miR-520h/SEMA4D axis was predicted in GBM.Conclusion Bioinformatics analysis was employed to analyze GSE15824 chip, and predict the potential mechanism. The results revealed that the ceRNA mechanism, OSER1-AS1/hsa-miR-520h/SEMA4D axis, might play a vital role in GBM.

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.

Identification of Differentially Expressed Genes and Signaling Pathways Related to Ovarian Endometriosis by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Kainan Lin ◽  
Zhenyan Pan ◽  
Renke He ◽  
Hanchu Wang ◽  
Kai Zhou ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Go Analysis ◽  
Pathway Enrichment

Abstract Purpose: Endometriosis was a common gynecological disease, however, the specific mechanism and the key molecules of endometriosis remained uncertain. This study aimed to single out key genes associated with poor prognosis, and further uncover underlying mechanisms.Methods: Data regarding mRNA expression profiles used in this study were retrieved from the Gene Expression Omnibus (GEO) database, a total of three mRNA expression profiles were included for subsequent analysis (GSE31515, GSE58178 and GSE120103). Then, we conducted Gene Ontology analysis (GO analysis), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) analysis by the software R.Results: A total of 304 differentially expressed genes (DEGs) between endometriosis tissues and normal endometrium tissues were identified in integrated analysis, including 185 up-regulated genes and 119 down-regulated genes. GO analysis reveals that the DEGs of endometriosis were closely associated with molecular origin of bacteria. KEGG pathway enrichment analysis indicates that the DEGs were mainly involved in AGE-RAGE signaling pathway in diabetic complications. In addition, PPI of these DEGs was visualized by Cytoscape platform with utilization of Search Tool for the Retrieval of Interacting Genes (STRING). PPI analysis identifies 10 potential DEGs-related protein targets, including CCND1, IL6, CCL2, COL1A2, PTGS2, VCAM1, COL3A1, ELN, SERPINE1, HSP90B1. Conclusion: In conclusion, the present study reveals that bacterial contamination, defect of female reproductive system development, retrograde menstruation and the AGE-RAGE signaling pathway may be involved in the development of endometriosis In addition, these identified DEGs may be of clinical significance for the diagnosis and treatment of the endometriosis.

scholarly journals Lipidomics profiling of goose granulosa cell model of stearoyl-CoA desaturase function identifies a pattern of lipid droplets associated with follicle development

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Yuan ◽  
Shenqiang Hu ◽  
Liang Li ◽  
Chunchun Han ◽  
Hehe Liu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Lipid Droplets ◽  
Cell Model ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Follicle Development ◽  
Microscopy Analysis ◽  
Stearoyl Coa Desaturase ◽  
Underlying Mechanisms

Abstract Background Despite their important functions and nearly ubiquitous presence in cells, an understanding of the biology of intracellular lipid droplets (LDs) in goose follicle development remains limited. An integrated study of lipidomic and transcriptomic analyses was performed in a cellular model of stearoyl-CoA desaturase (SCD) function, to determine the effects of intracellular LDs on follicle development in geese. Results Numerous internalized LDs, which were generally spherical in shape, were dispersed throughout the cytoplasm of granulosa cells (GCs), as determined using confocal microscopy analysis, with altered SCD expression affecting LD content. GC lipidomic profiling showed that the majority of the differentially abundant lipid classes were glycerophospholipids, including PA, PC, PE, PG, PI, and PS, and glycerolipids, including DG and TG, which enriched glycerophospholipid, sphingolipid, and glycerolipid metabolisms. Furthermore, transcriptomics identified differentially expressed genes (DEGs), some of which were assigned to lipid-related Gene Ontology slim terms. More DEGs were assigned in the SCD-knockdown group than in the SCD-overexpression group. Integration of the significant differentially expressed genes and lipids based on pathway enrichment analysis identified potentially targetable pathways related to glycerolipid/glycerophospholipid metabolism. Conclusions This study demonstrated the importance of lipids in understanding follicle development, thus providing a potential foundation to decipher the underlying mechanisms of lipid-mediated follicle development.

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals MicroRNA expression profiling involved in Borax-induced anti-tumor effect using gene-chip analysis

2020 ◽  
Author(s):  
Lun Wu ◽  
Ying Wei ◽  
Wen-Bo Zhou ◽  
Jiao Zhou ◽  
Li-Hua Yang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hepg2 Cells ◽  
Enrichment Analysis ◽  
Gene Chip ◽  
Differentially Expressed ◽  
Control Group ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Therapeutic Benefits ◽  
Differentially Expressed Mirnas

Abstract Background Borax, a boron compound, which is becoming widely recognized for its biological effects, including antioxidant activity, cytotoxicity, and potential therapeutic benefits. However, the specific molecular mechanisms underlying borax-induced anti-tumor effect still remain to be to further elucidated. MicroRNAs (miRNAs) may play key roles in cellular processes including tumor progression, cell apoptosis and cytotoxicity. Thus, this study aimed to investigate, whether miRNAs were involved in the borax-mediated anti-tumor effect using miRNA profiling of a human liver cancer cell line (HepG2) using gene-chip analysis.Methods Total RNA was extracted and purified from HepG2 cells that were treated with 4 mM borax for either 2 or 24 h. The samples underwent microarray analysis using an Agilent Human miRNA Array. Differentially expressed miRNAs were analysed by volcano plot and heatmap, and were validated using real-time fluorescent quantitative PCR (qPCR).ResultsAmong this, 2- or 24-h exposure to borax significantly altered the expression level of miRNAs in HepG2 cells, 4 or 14 were upregulated and 3 were downregulated compared with the control group, respectively (≥2-fold; P<0.05). GO enrichment analysis and KEGG pathway enrichment analysis revealed that target genes of differentially expressed miRNAs in HepG2 cells predominantly participated in MAPK signaling pathway, TGF-beta signaling pathway, NF-kappa B signaling pathway, etc; in 2-h borax treatment group, while Ras signaling pathway, FoxO signaling pathway, Cellular senescence, etc; involved in 24-h treatment group.Conclusions Result indicates that borax-induced anti-tumor effect may be associated with alterations in miRNAs.

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

scholarly journals Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Wenqing Nai ◽  
Diane Threapleton ◽  
Jingbo Lu ◽  
Kewei Zhang ◽  
Hongyuan Wu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Transforming Growth Factor ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transforming Growth Factor Β ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.

scholarly journals Integrative Analysis for Elucidating Transcriptomics Landscapes of Systemic Lupus Erythematosus

2021 ◽  
Vol 12 ◽  
Author(s):  
Haihong Zhang ◽  
Yanli Wang ◽  
Jinghui Feng ◽  
Shuya Wang ◽  
Yan Wang ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Differentially Expressed Genes ◽  
Lupus Erythematosus ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Potential Candidate ◽  
Systemic Lupus

Systemic lupus erythematosus (SLE) is a complex and heterogeneous autoimmune disease that the immune system attacks healthy cells and tissues. SLE is difficult to get a correct and timely diagnosis, which makes its morbidity and mortality rate very high. The pathogenesis of SLE remains to be elucidated. To clarify the potential pathogenic mechanism of SLE, we performed an integrated analysis of two RNA-seq datasets of SLE. Differential expression analysis revealed that there were 4,713 and 2,473 differentially expressed genes, respectively, most of which were up-regulated. After integrating differentially expressed genes, we identified 790 common differentially expressed genes (DEGs). Gene functional enrichment analysis was performed and found that common differentially expressed genes were significantly enriched in some important immune-related biological processes and pathways. Our analysis provides new insights into a better understanding of the pathogenic mechanisms and potential candidate markers for systemic lupus erythematosus.

scholarly journals Study on the Differentially Expressed Genes and Signaling Pathways in Systemic Lupus Erythematosus Using Integrated Bioinformatics Method

2020 ◽  
Author(s):  
Jing Liang ◽  
Xin Zhang ◽  
Wenjia Zhao
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Lupus Erythematosus ◽  
Scientific Research ◽  
Differentially Expressed ◽  
Statistical Hypothesis ◽  
Systemic Lupus ◽  
Ppi Networks ◽  
Geo Database

Abstract Background: Systemic lupus erythematosus (SLE) is a chronic immune connective tissue disease, which is common in women of childbearing age and easy to cause multiple organ inflammatory injury. The occurrence of prostate cancer is the result of multiple factors and genes, but we have little understanding of the mechanism involved. In this study, we deeply explored and analyzed the existing gene data in GEO database in order to find the key genes and new therapeutic targets of SLE.Results: The expression profile dataset of GDS4185, GDS4888, GDS4889 and GDS4890 containing 99 specimens, 42 cases of SLE patients and 57 cases of normal volunteers, were downloaded from the Gene Expression Omnibus (GEO) website. The differentially expressed genes (DEGs) in different tissues was analyzed by statistical hypothesis T test. The gene ontology (GO) enrichment analysis was carried out by the DAVID online tool. KEGG pathway annotation of DEGs was carried out by the KOBAS online computing database. The protein–protein interaction (PPI) networks of the DEGs were built from the STRING website and Cytoscape software. A total of 839 DEGs were calculated from the four GEO datasets. The GO and KEGG analysis indicated that the functions of DEGs mostly participated in the Osteoclast differentiation, HTLV-I infection, Measles, FoxO signaling pathway, Herpes simplex infection, Primary immunodeficiency, Jak-STAT signaling pathway. The following 14 closely related genes, HERC5, TP53, CDC20, GNB2, GNB4, PPP2R1A, GNAI2, PMCH, SOCS3, HERC6, STAT1, SOCS1, ISG15, IFIT3, were key nodes from the PPI network. These genes may have synergistic or indirect interactions with each other in the process of biological metabolism inducing the pathogenesis of SLE.Conclusion: Mining geo database has great scientific research value. In the future, scientific research must fully excavate a variety of database analysis methods. In this study, the screened candidate genes provide effective theoretical basis for the diagnosis, treatment, expected evaluation and related laboratory research of SLE, which are worthy of further experimental verification.

scholarly journals Bioinformatics Analysis Reveals the Potential Diagnostic Biomarkers for Abdominal Aortic Aneurysm

2021 ◽  
Vol 8 ◽  
Author(s):  
Xinsheng Xie ◽  
En ci Wang ◽  
Dandan Xu ◽  
Xiaolong Shu ◽  
Yu fei Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Aortic Aneurysms ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Abdominal Aortic

Objectives: Abdominal aortic aneurysms (AAAs) are associated with high mortality rates. The genes and pathways linked with AAA remain poorly understood. This study aimed to identify key differentially expressed genes (DEGs) linked to the progression of AAA using bioinformatics analysis.Methods: Gene expression profiles of the GSE47472 and GSE57691 datasets were acquired from the Gene Expression Omnibus (GEO) database. These datasets were merged and normalized using the “sva” R package, and DEGs were identified using the limma package in R. The functions of these DEGs were assessed using Cytoscape software. We analyzed the DEGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein–protein interaction networks were assembled using Cytoscape, and crucial genes were identified using the Cytoscape plugin, molecular complex detection. Data from GSE15729 and GSE24342 were also extracted to verify our findings.Results: We found that 120 genes were differentially expressed in AAA. Genes associated with inflammatory responses and nuclear-transcribed mRNA catabolic process were clustered in two gene modules in AAA. The hub genes of the two modules were IL6, RPL21, and RPL7A. The expression levels of IL6 correlated positively with RPL7A and negatively with RPL21. The expression of RPL21 and RPL7A was downregulated, whereas that of IL6 was upregulated in AAA.Conclusions: The expression of RPL21 or RPL7A combined with IL6 has a diagnostic value for AAA. The novel DEGs and pathways identified herein might provide new insights into the underlying molecular mechanisms of AAA.

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