Identification of Hub Genes Associated With Melanoma Development by Comprehensive Bioinformatics Analysis

IntroductionThis study aimed to identify important genes associated with melanoma to further develop new target gene therapies and analyze their significance concerning prognosis.Materials and methodsGene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO, and KEGG enrichment analysis and construction of the PPI visualized with Cytoscape and screened for the top 10 Hub genes using CytoHubba. We validated the Hub gene’s protein levels with an immunohistochemical assay to confirm the accuracy of our analysis.ResultsA total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1,\ EXO1, KIF20A, TPX2, and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). Immunohistochemistry showed that all five genes were expressed at higher protein levels in melanoma than in paracancerous tissues.ConclusionFOXM1, EXO1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with the low prognosis of melanoma patients and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

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Identification of Hub Genes Associated with Melanoma Development by Comprehensive Bioinformatics Analysis

10.21203/rs.3.rs-101310/v1 ◽

2020 ◽

Author(s):

Jie Jiang ◽

Guoyong Xu ◽

Tuo Liang ◽

Chaojie Yu ◽

Shian Liao ◽

...

Keyword(s):

Target Gene ◽

Enrichment Analysis ◽

High Expression ◽

Expression Data ◽

Hub Genes ◽

Gene Therapies ◽

Protein Levels ◽

Melanoma Diagnosis ◽

Melanoma Patients ◽

Core Genes

Abstract Introduction: This study aimed to identify important genes associated with melanoma to further develop new target gene therapies and analyze their significance concerning prognosis.Materials and methods: Gene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO, and KEGG enrichment analysis and construction of the PPI visualized with Cytoscape and screened for the top 10 Hub genes using CytoHubba. We validated the Hub gene's protein levels with an immunohistochemical assay to confirm the accuracy of our analysis.Results: A total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1, EXO1, KIF20A, TPX2, and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). Immunohistochemistry showed that all five genes were expressed at higher protein levels in melanoma than in paracancerous tissues.Conclusion: FOXM1, EXO1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with the low prognosis of melanoma patients and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

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Identification of Hub Genes Associated with Melanoma Development by Comprehensive Bioinformatics Analysis

10.21203/rs.3.rs-87468/v1 ◽

2020 ◽

Author(s):

Jie Jiang ◽

Guoyong Xu ◽

Tuo Liang ◽

Chaojie Yu ◽

Shian Liao ◽

...

Keyword(s):

Enrichment Analysis ◽

High Expression ◽

Hub Genes ◽

Gene Therapies ◽

Protein Levels ◽

Normal Tissues ◽

Melanoma Diagnosis ◽

Melanoma Patients ◽

Further Development ◽

Core Genes

Abstract Introduction: The aim of this study was to identify important genes associated with melanoma for further development of new target gene therapies and to analyze their significance in relation to prognosis.Materials and methods: Gene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO and KEGG enrichment analysis as well as construction of the PPI, visualized with Cytoscape, and screened for the top 10 Hub genes using CytoHubba. We verified the protein levels of the Hub gene using the HPA database.Results: A total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1, EXO1, KIF20A, TPX2 and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). The HPA database results showed that FOXM1, KIF20A, TPX2 and CDC20 showed upregulated expression in melanoma compared to normal tissues.Conclusion: FOXM1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with low prognosis of melanoma patients, and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

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Transcriptome Signatures Reveal Candidate Key Genes in the Peripheral Blood Mononuclear Cells of Patients With Coronary Artery Disease

10.21203/rs.3.rs-122558/v1 ◽

2020 ◽

Author(s):

Vijayakrishna Kolur ◽

Basavaraj Vastrad ◽

Chanabasayya Vastrad ◽

Iranna Kotturshetti ◽

Anandkumar Tengli

Keyword(s):

Coronary Artery Disease ◽

Gene Ontology ◽

Coronary Artery ◽

Regulatory Network ◽

Target Gene ◽

Enrichment Analysis ◽

Hub Genes ◽

Go Enrichment ◽

Artery Disease ◽

Go Enrichment Analysis

Abstract BackgroundCoronary artery disease (CAD) is one of the most common disorders in the cardiovascular system. This study aims to explore potential signaling pathways and important biomarkers that drive CAD development. MethodsThe CAD GEO Dataset GSE113079 was featured to screen differentially expressed genes (DEGs). The pathway and Gene Ontology (GO) enrichment analysis of DEGs were analyzed using the ToppGene. We screened hub and target genes from protein-protein interaction (PPI) networks, target gene - miRNA regulatory network and target gene - TF regulatory network, and Cytoscape software. Validations of hub genes were performed to evaluate their potential prognostic and diagnostic value for CAD. Results1,036 DEGs were captured according to screening criteria (525upregulated genes and 511downregulated genes). Pathway and Gene Ontology (GO) enrichment analysis of DEGs revealed that these up and down regulated genes are mainly enriched in thyronamine and iodothyronamine metabolism, cytokine-cytokine receptor interaction, nervous system process, cell cycle and nuclear membrane. Hub genes were validated to find out potential prognostic biomarkers, diagnostic biomarkers and novel therapeutic target for CAD. ConclusionsIn summary, our findings discovered pivotal gene expression signatures and signaling pathways in the progression of CAD. CAPN13, ACTBL2, ERBB3, GATA4, GNB4, NOTCH2, EXOSC10, RNF2, PSMA1 and PRKAA1 might contribute to the progression of CAD, which could have potential as biomarkers or therapeutic targets for CAD.

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MicroRNA-143 Regulates Adipocyte Differentiation

Journal of Biological Chemistry ◽

10.1074/jbc.c400438200 ◽

2004 ◽

Vol 279 (50) ◽

pp. 52361-52365 ◽

Cited By ~ 666

Author(s):

Christine Esau ◽

Xiaolin Kang ◽

Eigen Peralta ◽

Elaine Hanson ◽

Eric G. Marcusson ◽

...

Keyword(s):

Antisense Oligonucleotides ◽

Target Gene ◽

Adipocyte Differentiation ◽

Biological Function ◽

Protein Translation ◽

Functional Assay ◽

Expression Data ◽

Mirna Microarray ◽

Protein Levels ◽

Human Mirnas

MicroRNAs (miRNAs) are endogenously expressed 20-24 nucleotide RNAs thought to repress protein translation through binding to a target mRNA (1-3). Only a few of the more than 250 predicted human miRNAs have been assigned any biological function. In an effort to uncover miRNAs important during adipocyte differentiation, antisense oligonucleotides (ASOs) targeting 86 human miRNAs were transfected into cultured human pre-adipocytes, and their ability to modulate adipocyte differentiation was evaluated. Expression of 254 miRNAs in differentiating adipocytes was also examined on a miRNA microarray. Here we report that the combination of expression data and functional assay results identified a role for miR-143 in adipocyte differentiation. miR-143 levels increased in differentiating adipocytes, and inhibition of miR-143 effectively inhibited adipocyte differentiation. In addition, protein levels of the proposed miR-143 target ERK5 (4) were higher in ASO-treated adipocytes. These results demonstrate that miR-143 is involved in adipocyte differentiation and may act through target gene ERK5.

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Using Weighted Gene Co-Expression Network Analysis to Identify Key Genes Related to the Onset of Preeclampsia

10.21203/rs.3.rs-87182/v1 ◽

2020 ◽

Author(s):

Xinyang Shen ◽

Zhijian Wang ◽

Zhirui Zeng ◽

Zhenqin Huang ◽

Xiaowei Huang ◽

...

Keyword(s):

Enrichment Analysis ◽

Diagnostic Value ◽

Functional Enrichment ◽

Immune Response Gene ◽

Control Group ◽

Ppi Network ◽

Hub Genes ◽

Ontology Term ◽

Gene Data ◽

Core Genes

Abstract Background: Preeclampsia is a form of hypertension in pregnancy, which induced by complicated factors. However, the pathogenesis of the disease is unclear. The present study was aimed to discover the critical biomarkers associated with the occurrence and development of preeclampsia. Methods：Gene data profile GSE75010 was downloaded from the Gene Expression Omnibus (GEO) database and used as discovery cohort to establish a WGCNA network determining significant modules which associated with clinical traits. Subsequently, functional enrichment analysis, pathway analysis and protein-protein interaction (PPI) network construction were performed on the core genes in significant modules to identify hub genes. Then, gene data profile GSE25906 was used as verified cohort to determine their diagnostic value of hub genes. The protein expression levels of these hub genes in preeclampsia and control placental tissues were verified using immunohistochemistry method. Finally, GSEA was performed to analyze their enrichment pathways. Results: Total 33 co-expression modules were identified after the establishment of WGCNA, of which 4 gene modules were identified as significant modules because they were related to multiple (>3) clinical traits. Total 75 core genes in significant modules were analyzed, and results showed that they were mainly enriched in adaptive immune response (Gene Ontology term) and platelet activation (Kyoto Encyclopedia of Genes and Genomes term). Finally, a total of 5 genes including TYROBP, PLEK, LCP2, HCK, ITGAM were identified as hub genes which scored high in PPI network and had high diagnostic value. Furthermore, the protein level of these 5 genes in placental tissues of preeclampsia was lower than that of the control group. Moreover, these 5 genes were all enriched in 17 pathways, including autoimmunity pathway. Conclusions：These 5 genes (TYROBP, PLEK, LCP2, HCK, ITGAM) may be closely related to the pathogenesis of preeclampsia, which may also help the diagnosis and therapy of preeclampsia.

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Bioinformatics analysis of potential core genes for glioblastoma

Bioscience Reports ◽

10.1042/bsr20201625 ◽

2020 ◽

Vol 40 (7) ◽

Author(s):

Yu Zhang ◽

Xin Yang ◽

Xiao-Lin Zhu ◽

Jia-Qi Hao ◽

Hao Bai ◽

...

Keyword(s):

Survival Analysis ◽

Protein Interactions ◽

Poor Prognosis ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Normal Brain ◽

Hub Genes ◽

Potential Core ◽

Core Genes

Abstract Background: Glioblastoma (GBM) has a high degree of malignancy, aggressiveness and recurrence rate. However, there are limited options available for the treatment of GBM, and they often result in poor prognosis and unsatisfactory outcomes. Materials and methods: In order to identify potential core genes in GBM that may provide new therapeutic insights, we analyzed three gene chips (GSE2223, GSE4290 and GSE50161) screened from the GEO database. Differentially expressed genes (DEG) from the tissues of GBM and normal brain were screened using GEO2R. To determine the functional annotation and pathway of DEG, Gene Ontology (GO) and KEGG pathway enrichment analysis were conducted using DAVID database. Protein interactions of DEG were visualized using PPI network on Cytoscape software. Next, 10 Hub nodes were screened from the differentially expressed network using MCC algorithm on CytoHubba software and subsequently identified as Hub genes. Finally, the relationship between Hub genes and the prognosis of GBM patients was described using GEPIA2 survival analysis web tool. Results: A total of 37 up-regulated and 187 down-regulated genes were identified through microarray analysis. Amongst the 10 Hub genes selected, SV2B appeared to be the only gene associated with poor prognosis in glioblastoma based on the survival analysis. Conclusion: Our study suggests that high expression of SV2B is associated with poor prognosis in GBM patients. Whether SV2B can be used as a new therapeutic target for GBM requires further validation.

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Identification of the Crucial Gene in Overflow Arteriovenous Fistula by Bioinformatics Analysis

Frontiers in Physiology ◽

10.3389/fphys.2021.621830 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhengde Zhao ◽

Qining Fu ◽

Liangzhu Hu ◽

Yangdong Liu

Keyword(s):

Signaling Pathways ◽

Signaling Pathway ◽

Intimal Hyperplasia ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Mapk Signaling Pathway ◽

Biological Processes ◽

Hub Genes ◽

Av Fistula ◽

Core Genes

Objective: The aim was to study the preliminary screening of the crucial genes in intimal hyperplasia in the venous segment of arteriovenous (AV) fistula and the underlying potential molecular mechanisms of intimal hyperplasia with bioinformatics analysis.Methods: The gene expression profile data (GSE39488) was analyzed to identify differentially expressed genes (DEGs). We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of DEGs. Gene set enrichment analysis (GSEA) was used to understand the potential activated signaling pathway. The protein–protein interaction (PPI) network was constructed with the STRING database and Cytoscape software. The Venn diagram between 10 hub genes and gene sets of 4 crucial signaling pathways was used to obtain core genes and relevant potential pathways. Furthermore, GSEAs were performed to understand their biological functions.Results: A total of 185 DEGs were screened in this study. The main biological function of the 111 upregulated genes in AV fistula primarily concentrated on cell proliferation and vascular remodeling, and the 74 downregulated genes in AV fistula were enriched in the biological function mainly relevant to inflammation. GSEA found four signaling pathways crucial for intimal hyperplasia, namely, MAPK, NOD-like, Cell Cycle, and TGF-beta signaling pathway. A total of 10 hub genes were identified, namely, EGR1, EGR2, EGR3, NR4A1, NR4A2, DUSP1, CXCR4, ATF3, CCL4, and CYR61. Particularly, DUSP1 and NR4A1 were identified as core genes that potentially participate in the MAPK signaling pathway. In AV fistula, the biological processes and pathways were primarily involved with MAPK signaling pathway and MAPK-mediated pathway with the high expression of DUSP1 and were highly relevant to cell proliferation and inflammation with the low expression of DUSP1. Besides, the biological processes and pathways in AV fistula with the high expression of NR4A1 similarly included the MAPK signaling pathway and the pathway mediated by MAPK signaling, and it was mainly involved with inflammation in AV fistula with the low expression of NR4A1.Conclusion: We screened four potential signaling pathways relevant to intimal hyperplasia and identified 10 hub genes, including two core genes (i.e., DUSP1 and NR4A1). Two core genes potentially participate in the MAPK signaling pathway and might serve as the therapeutic targets of intimal hyperplasia to prevent stenosis after AV fistula creation.

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Screening a prognosis-related target gene in patients with HER-2 positive breast cancer by bioinformatics analysis

Medical Principles and Practice ◽

10.1159/000516322 ◽

2021 ◽

Author(s):

Song Wang ◽

Yi Quan

Keyword(s):

Breast Cancer ◽

Target Gene ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Hub Genes ◽

Study Objective ◽

Her 2 ◽

Positive Breast Cancer

Objective: HER-2 positive breast cancer has a high risk of for relapse, metastasis and drug resistance, and is related to a poor prognosis. Thus, the study objective was to determine a target gene and explore the associated molecular mechanisms in HER-2 positive breast cancer. Methods: Three RNA expression profiles were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), and were used to identify differentially expressed genes (DEGs) using R software. A Protein-Protein Interaction (PPI) network was constructed and hub genes were determined. Subsequently, the relationship between clinical parameters and hub genes was examined to screen target gene. Next, DNA methylation and genomic alterations of the target gene were evaluated. To further explore potential molecular mechanisms, genes co-expressed with the target gene were performed functional enrichment analysis Results: The differential expression analysis revealed 217 DEGs in HER-2 positive breast cancer tissues compared to normal breast tissues. RRM2 was the only hub gene closely associated with lymphatic metastasis and prognosis in HER-2 positive breast cancer. Additionally, RRM2 was frequently often amplified and negatively associated with the methylation level. Functional enrichment analysis showed that the co-expression genes were mainly involved in cell cycle. Conclusions: The present study identified RRM2 as a target gene associated with the initiation, progression and prognosis of HER-2 positive breast cancer, which may contribute to provide a new biomarker and therapeutic target.

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Transcriptome signatures reveal candidate key genes in the peripheral blood mononuclear cells of patients with coronary artery disease and prediction of small drug molecules

10.21203/rs.3.rs-122558/v2 ◽

2020 ◽

Author(s):

Vijayakrishna Kolur ◽

Basavaraj Vastrad ◽

Anandkumar Tengli ◽

Chanabasayya Vastrad ◽

Iranna Kotturshetti

Keyword(s):

Coronary Artery Disease ◽

Gene Ontology ◽

Coronary Artery ◽

Regulatory Network ◽

Target Gene ◽

Enrichment Analysis ◽

Hub Genes ◽

Go Enrichment ◽

Artery Disease ◽

Go Enrichment Analysis

Abstract Coronary artery disease (CAD) is one of the most common disorders in the cardiovascular system. This study aims to explore potential signaling pathways and important biomarkers that drive CAD development. The CAD GEO Dataset GSE113079 was featured to screen differentially expressed genes (DEGs). The pathway and Gene Ontology (GO) enrichment analysis of DEGs were analyzed using the ToppGene. We screened hub and target genes from protein-protein interaction (PPI) networks, target gene - miRNA regulatory network and target gene - TF regulatory network, and Cytoscape software. Validations of hub genes were performed to evaluate their potential prognostic and diagnostic value for CAD. A final, molecular docking study was performed. 1,036 DEGs were captured according to screening criteria (525upregulated genes and 511downregulated genes). Pathway and Gene Ontology (GO) enrichment analysis of DEGs revealed that these up and down regulated genes are mainly enriched in thyronamine and iodothyronamine metabolism, cytokine-cytokine receptor interaction, nervous system process, cell cycle and nuclear membrane. Hub genes were validated to find out potential prognostic biomarkers, diagnostic biomarkers and novel therapeutic target for CAD. A small drug molecule was predicted. In summary, our findings discovered pivotal gene expression signatures and signaling pathways in the progression of CAD. CAPN13, ACTBL2, ERBB3, GATA4, GNB4, NOTCH2, EXOSC10, RNF2, PSMA1 and PRKAA1 might contribute to the progression of CAD, which could have potential as biomarkers or therapeutic targets for CAD.

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Identification of Prognostic Biomarkers of Potential Hub Genes in Urothelial Carcinoma and Function in Microenvironment

10.21203/rs.3.rs-502631/v1 ◽

2021 ◽

Author(s):

Wei Chu ◽

Bing Zhang ◽

Haifeng Gong ◽

Qianqian Zhao ◽

Jun Chen ◽

...

Keyword(s):

T Cells ◽

Urothelial Carcinoma ◽

Checkpoint Inhibitors ◽

Expression Profiles ◽

Enrichment Analysis ◽

Receptor Interaction ◽

Hub Genes ◽

Database Analysis ◽

Protein Levels ◽

Normal Tissues

Abstract Background Urothelial carcinoma (UC) is the most common histological type of urinary system. In the past decades, despite the advances in UC diagnosis and therapy, there are still challenges to improve the overall survival (OS) of UC patients. PD-L1 inhibitor and PD-1 inhibitor have been approved for treating invasive UC, however, only about 20% of patients with metastatic UC show clinical benefits from immune checkpoint inhibitors. Therefor, bioinformatics tools were utilized to screen prognostic-related biomarkers, and analyze their relationship with immunocyte in UC, hoping to provide new ideas for the clinical treatment of UC patients.Methods Three gene expression profiles (i.e. GSE32548, GSE32894 and GSE48075) were selected from GEO, and divide them into invasive and superficial UC group for study. NetworkAnalyst tool was used to construct gene regulatory network of DEGs, while DAVID and Metascape were utilized to perform gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of DEGs. The hub genes were screened by STRING and cytoscape, and the ONCOMINE, GEPIA, UALCAN, cBioPortal and HPA databases were used to analyze the expression differences and survival curves of UC at the DNA, RNA, protein levels and protein levels. TIMER was used to analyze the relationship between hub genes and immunocyte infiltration.Results In total, 63 DEGs were identified from the GEO database of UC, of which 31 and 32 were up-and down-regulated. GO/KEGG pathway analysis identified DEGs were mainly enriched in the collagen catabolic process, extracellular matrix (ECM) organization, ECM structural constituent and ECM-receptor interaction. Nine hub genes (i.e. COL1A1, COL1A2, COL3A1, COL5A2, MMP9, POSTN, SPP1, VCAN and THBS2) upregulated in invasive UC compared with superficial UC were identified. cBioportal database analysis showed that 35% of UC patients presented genetic variants in the hub genes, of which amplification and deletion mutations were the most common. ONCOMINE and UALCAN database analysis showed that the mRNA expression of all hub genes in invasive UC was significantly higher than that in superficial UC and normal tissues. HPA database analysis showed that there was up-regulation of COL3A1, SPP1, POSTN and VCAN protein in UC tissues than in normal tissues. GEPIA showed that COL1A2, COL3A1, THBS2, and VCAN were positively correlated with the OS rate among patients with UC (P < 0.05). UALCAN showed that UC patients with high expression of COL1A1, COL1A2, COL5A2 and POSTN had a poorer prognosis (P < 0.05). TRRUST database analysis indicated that there was a significant correlation between the expression of the hub genes and the infiltration of CD4 + T cells, CD8 + T cells, macrophages, neutrophils and dendritic cells.Conclusion Hub genes played important roles in pathogenesis and treatment prognosis of UC. Hub genes analysis provides new predictive biomolecules for UC immunotherapy and prognosis judgment.

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