Potential Molecular Mechanism of the NPPB Gene in Postischemic Heart Failure with and without T2DM

Background. This study is aimed at investigating natriuretic peptide B (NPPB) coexpression genes and their pathways involved in heart failure (HF) among patients both with and without type 2 diabetes mellitus (T2DM). Methods. The microarray dataset GSE26887, containing 19 postischemic HF patients’ peripheral blood samples (7 with T2DM and 12 without T2DM), was examined to detect the genes coexpressed with NPPB using the corr.test function in the R packet. Furthermore, using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of the coexpression genes. The modules and hub genes of the PPI network were then identified using the Cytoscape software. Results. In patients with T2DM, a total of 41 biological processes (BP), 20 cellular components (CC), 13 molecular functions (MF), and 41 pathways were identified. Furthermore, a total of 61 BPs, 16 CCs, 13 MFs, and 22 pathways in patients without T2DM were identified. In both groups of patients, 17 BPs, 10 CCs, 6 MFs, and 13 pathways were enriched. We also identified 173 intersectional coexpression genes (63 positively, 106 negatively, and 4 differently coexpressed in patients with and without T2DM, respectively) in both types of patients, which were enriched in 16 BPs, 8 CCs, 3 MFs, and 8 KEGG pathways. Moreover, the PPI network (containing 237 edges and 170 nodes) with the top module significantly enriched in 4 BPs (tricarboxylic acid metabolic process, citrate metabolic process, tricarboxylic acid cycle, and aerobic respiration) and 3 pathways (citrate cycle, malaria parasite metabolic pathway, and AGE-RAGE signaling pathway in diabetic complications) was constructed. DECR1, BGN, TIMP1, VCAN, and CTCF are the top hub genes. Conclusions. Our findings may elucidate the functions and roles of the NPPB gene in patients with postischemic HF and facilitate HF management.

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Potential molecular mechanism of the NPPB gene in post-ischemic heart failure with and without T2DM

10.21203/rs.2.21573/v1 ◽

2020 ◽

Author(s):

Yao-Zong Guan ◽

Rui-Xing Yin ◽

Guo-Xiong Deng ◽

Peng-Fei Zheng ◽

Chun-Xiao Liu ◽

...

Keyword(s):

Heart Failure ◽

Tricarboxylic Acid Cycle ◽

Enrichment Analysis ◽

Tricarboxylic Acid ◽

Metabolic Process ◽

Ischemic Heart ◽

Pathway Enrichment Analysis ◽

Ischemic Heart Failure ◽

Ppi Network ◽

Go Annotation

Abstract Background This study aimed to investigate natriuretic peptide B ( NPPB ) co-expression genes and the pathways involved in post-ischemic heart failure (HF) among patients both with and without type 2 diabetes mellitus (T2DM). Methods The microarray dataset of GSE26887 was examined to detect the genes that co-expressed with NPPB from 19 post-ischemic HF patients’ peripheral blood samples (7 with T2DM and 12 without T2DM). NPPB co-expression genes were then screened using the R packet. Further, using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of the co-expression genes. The modules and hub genes of the PPI network were then identified using the Cytoscape software. Results In patients with T2DM, a total of 41 biological processes (BP), 20 cellular components (CC), 13 molecular functions (MF), and 41 pathways were identified. Further, a total of 61 BPs, 16 CCs, 13 MFs, and 22 pathways in patients without T2DM were identified. In both groups of patients, 17 BPs, 10 CCs, 6 MFs, and 13 pathways were enriched. We also identified 173 intersectional co-expression genes (63 positive, 106 negative, and 4 differently co-expressed in patients with and without T2DM, respectively) in both types of patients, which enriched in 16 BPs, 8 CCs, 3 MFs, and 8 KEGG pathways. Moreover, the PPI network (contained 237 edges and 170 nodes) with the top module significantly enriched in 4 BPs (the tricarboxylic acid metabolic process, citrate metabolic process, tricarboxylic acid cycle, and aerobic respiration) and 3 pathways (the citrate cycle, malaria parasite metabolic pathway, and AGE-RAGE signaling pathway in diabetic complications) was constructed. Conclusions This study used genome-wide co-expression genes to identify the potential functions and mechanisms of the NPPB gene in post-ischemic HF with and without T2DM. Our findings may elucidate the functions and roles of NPPB in patients with post-ischemic HF and facilitate HF management.

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Potential Molecular Mechanism of the NPPB Gene in Post-Ischemic Heart Failure with and without T2DM

10.21203/rs.3.rs-21106/v1 ◽

2020 ◽

Author(s):

Yao-Zong Guan ◽

Rui-Xing Yin ◽

Guo-Xiong Deng ◽

Peng-Fei Zheng ◽

Chun-Xiao Liu ◽

...

Keyword(s):

Diabetes Mellitus ◽

Heart Failure ◽

Microarray Dataset ◽

Tricarboxylic Acid ◽

Metabolic Process ◽

Ischemic Heart ◽

Pathway Enrichment Analysis ◽

Ischemic Heart Failure ◽

Ppi Network ◽

Hub Genes

Abstract Background: This study aimed to investigate natriuretic peptide B (NPPB) co-expression genes and the pathways involved in post-ischemic heart failure (HF) among patients both with and without type 2 diabetes mellitus (T2DM). Methods: The microarray dataset of GSE26887 was examined to detect the genes that co-expressed with NPPB from 19 post-ischemic HF patients’ peripheral blood samples (7 with T2DM and 12 without T2DM). NPPB co-expression genes were then screened using the R packet. Further, using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of the co-expression genes. The modules and hub genes of the PPI network were then identified using the Cytoscape software. Results: In patients with T2DM, a total of 41 biological processes (BP), 20 cellular components (CC), 13 molecular functions (MF), and 41 pathways were identified. Further, a total of 61 BPs, 16 CCs, 13 MFs, and 22 pathways in patients without T2DM were identified. In both groups of patients, 17 BPs, 10 CCs, 6 MFs, and 13 pathways were enriched. We also identified 173 intersectional co-expression genes (63 positive, 106 negative, and 4 differently co-expressed in patients with and without T2DM, respectively) in both types of patients, which enriched in 16 BPs, 8 CCs, 3 MFs, and 8 KEGG pathways. Moreover, the PPI network (contained 237 edges and 170 nodes) with the top module significantly enriched in 4 BPs (the tricarboxylic acid metabolic process, citrate metabolic process, tricarboxylic acid cycle, and aerobic respiration) and 3 pathways (the citrate cycle, malaria parasite metabolic pathway, and AGE-RAGE signaling pathway in diabetic complications) was constructed. DECR1, BGN, TIMP1, VCAN and CTCF are the top hub genes. Conclusions: This study used genome-wide co-expression genes to identify the potential functions and mechanisms of the NPPB gene in post-ischemic HF with and without T2DM. Our findings may elucidate the functions and roles of NPPB in patients with post-ischemic HF and facilitate HF management. Key words: Co-expression genes, NPPB, Heart failure, Diabetes mellitus, Microarray dataset

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Prediction and Validation of Hub Genes Associated with Colorectal Cancer by Integrating PPI Network and Gene Expression Data

BioMed Research International ◽

10.1155/2017/2421459 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Yongfu Xiong ◽

Wenxian You ◽

Rong Wang ◽

Linglong Peng ◽

Zhongxue Fu

Keyword(s):

Colorectal Cancer ◽

Mrna Expression ◽

Interaction Network ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Advanced Tumor Stage ◽

Ppi Network ◽

Hub Genes ◽

Clinical Value ◽

Advanced Tumor

Although hundreds of colorectal cancer- (CRC-) related genes have been screened, the significant hub genes still need to be further identified. The aim of this study was to identify the hub genes based on protein-protein interaction network and uncover their clinical value. Firstly, 645 CRC patients’ data from the Tumor Cancer Genome Atlas were downloaded and analyzed to screen the differential expression genes (DEGs). And then, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed, and PPI network of the DEGs was constructed by Cytoscape software. Finally, four hub genes (CXCL3, ELF5, TIMP1, and PHLPP2) were obtained from four subnets and further validated in our clinical setting and TCGA dataset. The results showed that mRNA expression of CXCL3, ELF5, and TIMP1 was increased in CRC tissues, whereas PHLPP2 mRNA expression was decreased. More importantly, high expression of CXCL3, ELF5, and TIMP1 was significantly associated with lymphatic invasion, distance metastasis, and advanced tumor stage. In addition, a shorter overall survival was observed in patients with increased CXCL3, TIMP1, and ELF5 expression and decreased PHLPP2 expression. In conclusion, the four hub genes screened by our strategy could serve as novel biomarkers for prognosis prediction of CRC patients.

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Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses

10.1101/2020.12.21.20248688 ◽

2020 ◽

Author(s):

Basavaraj Vastrad ◽

Chanabasayya Vastrad ◽

Iranna Kotturshetti

Keyword(s):

Regulatory Network ◽

Molecular Mechanisms ◽

Target Genes ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Bioinformatics Analyses ◽

Go Enrichment ◽

Jakob Disease

AbstractSporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. Pathway and GO enrichment analyses of DEGs were performed. Furthermore, the protein-protein interaction (PPI) network was predicted using the IntAct Molecular Interaction Database and visualized with Cytoscape software. In addition, hub genes and important modules were selected based on the network. Finally, we constructed target genes - miRNA regulatory network and target genes - TF regulatory network. Hub genes were validated. A total of 891 DEGs 448 of these DEGs presented significant up regulated, and the remaining 443 down regulated were obtained. Pathway enrichment analysis indicated that up regulated genes were mainly linked with glutamine degradation/glutamate biosynthesis, while the down regulated genes were involved in melatonin degradation. GO enrichment analyses indicated that up regulated genes were mainly linked with chemical synaptic transmission, while the down regulated genes were involved in regulation of immune system process. hub and target genes were selected from the PPI network, modules, and target genes - miRNA regulatory network and target genes - TF regulatory network namely YWHAZ, GABARAPL1, EZR, CEBPA, HSPB8, TUBB2A and CDK14. The current study sheds light on the molecular mechanisms of sCJD and may provide molecular targets and diagnostic biomarkers for sCJD.

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Identification of biomarkers, pathways and potential therapeutic targets for heart failure using bioinformatics analysis

10.1101/2021.08.05.455244 ◽

2021 ◽

Author(s):

Basavaraj Mallikarjunayya Vastrad ◽

Chanabasayya Mallikarjunayya Vastrad

Keyword(s):

Heart Failure ◽

Gene Regulatory Network ◽

Regulatory Network ◽

Characteristic Curve ◽

Topological Analysis ◽

Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Hub Gene ◽

Gene Regulatory

Heart failure (HF) is a complex cardiovascular diseases associated with high mortality. To discover key molecular changes in HF, we analyzed next-generation sequencing (NGS) data of HF. In this investigation, differentially expressed genes (DEGs) were analyzed using limma in R package from GSE161472 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network, miRNA-hub gene regulatory network and TF-hub gene regulatory network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), REACTOME pathway, STRING, HiPPIE, miRNet, NetworkAnalyst and Cytoscape. Finally, we performed receiver operating characteristic curve (ROC) analysis of hub genes. A total of 930 DEGs 9464 up regulated genes and 466 down regulated genes) were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections and the citric acid (TCA) cycle and respiratory electron transport. Subsequently, the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed, and 10 hub genes in these network were focused on by centrality analysis and module analysis. Furthermore, data showed that HSP90AA1, ARRB2, MYH9, HSP90AB1, FLNA, EGFR, PIK3R1, CUL4A, YEATS4 and KAT2B were good diagnostic values. In summary, this study suggests that HSP90AA1, ARRB2, MYH9, HSP90AB1, FLNA, EGFR, PIK3R1, CUL4A, YEATS4 and KAT2B may act as the key genes in HF.

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Comprehensive Analyses of miRNA-mRNA Network and Potential Drugs in Idiopathic Pulmonary Arterial Hypertension

BioMed Research International ◽

10.1155/2020/5156304 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Chan Li ◽

Zeyu Zhang ◽

Qian Xu ◽

Ruizheng Shi

Keyword(s):

Pulmonary Arterial Hypertension ◽

Arterial Hypertension ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Idiopathic Pulmonary Arterial Hypertension ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Pulmonary Arterial

Introduction. Idiopathic pulmonary arterial hypertension (IPAH) is a severe cardiopulmonary disease with a relatively low survival rate. Moreover, the pathogenesis of IPAH has not been fully recognized. Thus, comprehensive analyses of miRNA-mRNA network and potential drugs in IPAH are urgent requirements. Methods. Microarray datasets of mRNA and microRNA (miRNA) in IPAH were searched and downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMIs) were identified. Then, the DEMI-DEG network was conducted with associated comprehensive analyses including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis, while potential drugs targeting hub genes were investigated using L1000 platform. Results. 30 DEGs and 6 DEMIs were identified in the lung tissue of IPAH. GO and KEGG pathway analyses revealed that these DEGs were mostly enriched in antimicrobial humoral response and African trypanosomiasis, respectively. The DEMI-DEG network was conducted subsequently with 4 DEMIs (hsa-miR-34b-5p, hsa-miR-26b-5p, hsa-miR-205-5p, and hsa-miR-199a-3p) and 16 DEGs, among which 5 DEGs (AQP9, SPP1, END1, VCAM1, and SAA1) were included in the top 10 hub genes of the PPI network. Nimodipine was identified with the highest CMap connectivity score in L1000 platform. Conclusion. Our study conducted a miRNA-mRNA network and identified 4 miRNAs as well as 5 mRNAs which may play important roles in the pathogenesis of IPAH. Moreover, we provided a new insight for future therapies by predicting potential drugs targeting hub genes.

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Multi‐omics analysis reveals the interaction between the complement system and the coagulation cascade in the development of endometriosis

Scientific Reports ◽

10.1038/s41598-021-90112-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Liang Yu ◽

Huaji Shen ◽

Xiaohan Ren ◽

Anqi Wang ◽

Shu Zhu ◽

...

Keyword(s):

Complement System ◽

Quantitative Polymerase Chain Reaction ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Coagulation Cascade ◽

Coagulation System ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Pathway Enrichment

AbstractEndometriosis (EMS) is a disease that shows immune dysfunction and chronic inflammation characteristics, suggesting a role of complement system in its pathophysiology. To find out the hub genes and pathways involved in the pathogenesis of EMs, three raw microarray datasets were recruited from the Gene Expression Omnibus database (GEO). Then, a series of bioinformatics technologies including gene ontology (GO), Hallmark pathway enrichment, protein–protein interaction (PPI) network and gene co-expression correlation analysis were performed to identify hub genes. The hub genes were further verified by the Real-time quantitative polymerase chain reaction (RT-PCR) and Western Blot (WB). We identified 129 differentially expressed genes (DEGs) in EMs, of which 78 were up-regulated and 51 were down-regulated. Through GO functional enrichment analysis, we found that the DEGs are mainly enriched in cell adhesion, extracellular matrix remodeling, chemokine regulation, angiogenesis regulation, epithelial cell proliferation, et al. In Hallmark pathway enrichment analysis, coagulation pathway showed great significance and the terms in which included the central complement factors. Moreover, the genes were dominating in PPI network. Combined co-expression analysis with experimental verification, we found that the up-regulated expression of complement (C1S, C1QA, C1R, and C3) was positively related to tissue factor (TF) in EMs. In this study, we discovered the over expression complement and the positive correlation between complement and TF in EMs, which suggested that interaction of complement and coagulation system may play a role within the pathophysiology of EMS.

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POS0743 GENE EXPRESSION MICROARRAY IN LUPUS NEPHRITIS BY BIOINFORMATIC ANALYSIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.2062 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 623.1-623

Author(s):

C. Wang ◽

S. X. Zhang ◽

S. Song ◽

J. Qiao ◽

R. Zhao ◽

...

Keyword(s):

Lupus Nephritis ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Differential Expression Analysis ◽

Deep Understanding ◽

Enrichment Analysis ◽

Shanxi Province ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes

Background:Nephritis is one of the predominant causes of morbidity and mortality in patients with lupus1 2.The lack of understanding regarding the molecular mechanisms of lupus nephritis(LN) hinders the development of specific targeted therapy for this progressive disease3.Objectives:In this study, we use bioinformatics method to analyze the genes involved in regulating the potential pathogenesis of LN.Methods:The expression profile of LN(GSE104948 and GSE32591) was obtained from the GEO database.GSE104948 was a memory chip, which included 32 LN glomerular biopsy tissues and 3 glomerular tissues from living donors.GSE32591 dataset included 32 LN glomerular biopsy tissues and 15 glomerular tissues from living donors. The Oligo package was used to process the data to obtain the expression matrix files of all the related genes.P<0.05 and |log2(FC)|>2 were setted as cut-off criteria for the DEGs.Ggplot2, heatmap packages were used to DEGs visualization. Metascape online tool was used to annotating DEGs for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis performed.We used STRING online database to construct protein-protein interaction (PPI) network. Hub genes were identified by Cytoscape.Results:In differential expression analysis,357 DEGs were identified,including 248 up-regulated genes and 109 down-regulated genes (Figure 1A,B).GO enrichment showed that these DEGs were primarily enriched in biological pathways, cell localization and molecular function and revealed that LN-related genes mainly involved in immune response.KEGG pathway annotation enrichment analysis revealed these DEGs were closely associated with Staphylococcus aureus infection,Complement and coagulation cascades (Figure 1D). Fourteen hub genes(IFT3,IRF7,OAS3,GBP2,RSAD2,MX1,IFIT2,IFI6,MX2,ISF15,IFIT1,QAS2,OASL,OAS1) were identified from PPI network (Figure 1C,E).Conclusion:Illuminating the molecular mechanisms of LN was help for deep understanding of LN.References:[1]Song J, Zhao L, Li Y. Comprehensive bioinformatics analysis of mRNA expression profiles and identification of a miRNA-mRNA network associated with lupus nephritis. Lupus 2020;29(8):854-61. doi: 10.1177/0961203320925155 [published Online First: 2020/05/22].[2]Yao F, Sun L, Fang W, et al. HsamiR3715p inhibits human mesangial cell proliferation and promotes apoptosis in lupus nephritis by directly targeting hypoxiainducible factor 1alpha. Mol Med Rep 2016;14(6):5693-98. doi: 10.3892/mmr.2016.5939 [published Online First: 2016/11/24].[3]Dall’Era M. Treatment of lupus nephritis: current paradigms and emerging strategies. Curr Opin Rheumatol 2017;29(3):241-47. doi: 10.1097/BOR.0000000000000381 [published Online First: 2017/02/17].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

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Bioinformatic analysis reveals hub genes and pathways that promote melanoma metastasis

10.21203/rs.3.rs-25246/v4 ◽

2020 ◽

Author(s):

Wenxing Su ◽

Yi Guan ◽

Biao Huang ◽

Juanjuan Wang ◽

Yuqian Wei ◽

...

Keyword(s):

Differentially Expressed Gene ◽

Primary Melanoma ◽

Enrichment Analysis ◽

Gene Interaction ◽

Underlying Mechanism ◽

Bioinformatic Analysis ◽

Pathway Enrichment Analysis ◽

Melanoma Metastasis ◽

Ppi Network ◽

Hub Genes

Abstract Background: Melanoma has the highest mortality rate of all skin tumors, and metastases are the major cause of death from it. The molecular mechanism leading to melanoma metastasis is currently unclear. Methods: With the goal of revealing the underlying mechanism, three data sets with accession numbers GSE8401, GSE46517 and GSE7956 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed gene (DEG) of primary melanoma and metastatic melanoma, three kinds of analyses were performed, namely functional annotation, protein‐protein interaction (PPI) network and module construction, and co-expression and drug-gene interaction prediction analysis. Results: A total of 41 up-regulated genes and 79 down-regulated genes was selected for subsequent analyses. Results of pathway enrichment analysis showed that extracellular matrix organization and proteoglycans in cancer are closely related to melanoma metastasis. In addition, seven pivotal genes were identified from PPI network, including CXCL8, THBS1, COL3A1, TIMP3, KIT, DCN, and IGFBP5, which have all been verified in the TCGA database and clinical specimens, but only CXCL8, THBS1 and KIT had significant differences in expression. Conclusions: To conclude, CXCL8, THBS1 and KIT may be the hub genes in the metastasis of melanoma and thus may be regarded as therapeutic targets in the future.

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Prognostic values and prospective pathway signaling of MicroRNA-182 in ovarian cancer: a study based on gene expression omnibus (GEO) and bioinformatics analysis

Journal of Ovarian Research ◽

10.1186/s13048-019-0580-7 ◽

2019 ◽

Vol 12 (1) ◽

Author(s):

Yaowei Li ◽

Li Li

Keyword(s):

Gene Expression ◽

Target Genes ◽

Gynecological Cancer ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Protein Protein Interaction

Abstract Background Ovarian carcinoma (OC) is a common cause of death among women with gynecological cancer. MicroRNAs (miRNAs) are believed to have vital roles in tumorigenesis of OC. Although miRNAs are broadly recognized in OC, the role of has-miR-182-5p (miR-182) in OC is still not fully elucidated. Methods We evaluated the significance of miR-182 expression in OC by using analysis of a public dataset from the Gene Expression Omnibus (GEO) database and a literature review. Furthermore, we downloaded three mRNA datasets of OC and normal ovarian tissues (NOTs), GSE14407, GSE18520 and GSE36668, from GEO to identify differentially expressed genes (DEGs). Then the targeted genes of hsa-miR-182-5p (TG_miRNA-182-5p) were predicted using miRWALK3.0. Subsequently, we analyzed the gene overlaps integrated between DEGs in OC and predicted target genes of miR-182 by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. STRING and Cytoscape were used to construct a protein-protein interaction (PPI) network and the prognostic effects of the hub genes were analyzed. Results A common pattern of up-regulation for miR-182 in OC was found in our review of the literature. A total of 268 DEGs, both OC-related and miR-182-related, were identified, of which 133 genes were discovered from the PPI network. A number of DEGs were enriched in extracellular matrix organization, pathways in cancer, focal adhesion, and ECM-receptor interaction. Two hub genes, MCM3 and GINS2, were significantly associated with worse overall survival of patients with OC. Furthermore, we identified covert miR-182-related genes that might participate in OC by network analysis, such as DCN, AKT3, and TIMP2. The expressions of these genes were all down-regulated and negatively correlated with miR-182 in OC. Conclusions Our study suggests that miR-182 is essential for the biological progression of OC.

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