Identification of key genes involved in Brg1 mutation-induced cataract using bioinformatics analyses with publicly available microarray data

Background: Cataract is a common and frequently occurring disease in the elderly. The Brahma-related gene 1 (Brg1) is believed to be related to the formation of cataract, but its mechanisms still remain unclear. This study aimed to investigate how a Brg1 mutation affects lens development and promotes the formation of cataract in mice. Methods: We used mRNA profiles downloaded from the Gene Expression Omnibus (GEO) database to compare the tissue samples of lenses from 4 dominant-negative Brg1(dnBrg1) transgenic mice and 4 wild-type mice. Then, the NetworkAnalyst online tool was employed to screen for the significantly differentially expressed genes (DEGs). Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway analysis were examined in DEGs by using Metascape. In addition, we applied the STRING online tool and Cytoscape software to build the protein-protein interaction (PPI) network. Finally, the CytoNCA plug-in was used to choose the central modules from the PPI network. Results: 323 DEGs were filtered in total, 222 of which were up-regulated genes and enriched in the cell cycle process regulation, mitotic G1-G1/S phase, mRNA splicing, etc., while 101 of which were down-regulated genes and enriched in the organ hydroxy compound transport, synaptic vesicle cycle and neuron migration. Within this network of PPI, we found that the heat shock protein 90 alpha (cytosolic), class B member 1 (HSP90ab1), the polymerase (RNA) II (DNA directed) polypeptide E (Polr2e), the cell division cycle 20 (Cdc20) and the polymerase (RNA) II (DNA directed) polypeptide C (Polr2c) had higher connectivity degrees and may interact and influence each other. Conclusions: The Brg1 mutation affected expression of various genes in mice, such as HSP90ab1, Polr2e, Cdc20, and Polr2c. These genes may have some effects on the occurrence and development of cataract, and may serve as potential therapeutic targets for the cataract treatment.

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Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

10.21203/rs.3.rs-21667/v3 ◽

2021 ◽

Author(s):

Lu Gao ◽

Yu Zhao ◽

Xuelei Ma ◽

Ling Zhang

Keyword(s):

Survival Analysis ◽

Kegg Pathway ◽

Gene Prediction ◽

Expression Profiles ◽

Gene Expression Omnibus ◽

Integrated Analysis ◽

Ppi Network ◽

Tissue Samples ◽

Pathway Enrichment ◽

Cerna Network

Abstract Background: Competitive endogenous RNA (ceRNA) has revealed a new mechanism of interaction between RNAs and been demonstrated to play crucial roles in multiple biological processes and in the development of neoplasms that potentially serve as diagnostic and prognosis markers as well as therapeutic targets.Methods：In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcoma by comparing the genes expression profiles between sarcoma samples and normal tissue samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed in Cytoscape. In addition, the protein-protein interaction (PPI) network was constructed and survival analysis was performed.Results: A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG pathway enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA-miRNA-mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients.Conclusions: Overall, we constructed a ceRNA network in sarcomas, which likely provides insights for further research on the molecular mechanism and potential prognosis biomarkers.

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Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

10.21203/rs.3.rs-21667/v2 ◽

2020 ◽

Author(s):

Lu Gao ◽

Yu Zhao ◽

Xuelei Ma ◽

Ling Zhang

Keyword(s):

Survival Analysis ◽

Kegg Pathway ◽

Gene Prediction ◽

Expression Profiles ◽

Gene Expression Omnibus ◽

Integrated Analysis ◽

Ppi Network ◽

Tissue Samples ◽

Pathway Enrichment ◽

Cerna Network

Abstract Background: Competitive endogenous RNA (ceRNA) has been demonstrated to play crucial roles in multiple biological processes and in the development of neoplasms that potentially serve as diagnostic and prognosis markers as well as therapeutic targets.Methods: In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcoma by comparing the genes expression profiles between sarcoma samples and normal tissue samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed in Cytoscape. In addition, the protein-protein interaction (PPI) network was constructed and survival analysis was performed.Results: A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG pathway enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA-miRNA-mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients.Conclusions: Overall, we constructed a ceRNA network in sarcomas, which likely provides insights for further research on the molecular mechanism and potential prognosis biomarkers.

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Comprehensive Analysis of Pertinent Genes and Pathways in Atrial Fibrillation

Computational and Mathematical Methods in Medicine ◽

10.1155/2021/4530180 ◽

2021 ◽

Vol 2021 ◽

pp. 1-20

Author(s):

Yanzhe Wang ◽

Wenjuan Cai ◽

Liya Gu ◽

Xuefeng Ji ◽

Qiusheng Shen

Keyword(s):

Atrial Fibrillation ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

Cell Counting ◽

Ppi Network ◽

Hub Genes ◽

Bioinformatics Analyses ◽

Protein Protein Interaction ◽

Endothelial Growth Factor

Purpose. Atrial fibrillation (AF) is the most frequent arrhythmia in clinical practice. The pathogenesis of AF is not yet clear. Therefore, exploring the molecular information of AF displays much importance for AF therapy. Methods. The GSE2240 data were acquired from the Gene Expression Omnibus (GEO) database. The R limma software package was used to screen DEGs. Based on the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) databases, we conducted the functions and pathway enrichment analyses. Then, the STRING and Cytoscape software were employed to build Protein-Protein Interaction (PPI) network and screen for hub genes. Finally, we used the Cell Counting Kit-8 (CCK-8) experiment to explore the effect of hub gene knockdown on the proliferation of AF cells. Result. 906 differentially expressed genes (DEGs), including 542 significantly upregulated genes and 364 significantly downregulated genes, were screened in AF. The genes of AF were mainly enriched in vascular endothelial growth factor-activated receptor activity, alanine, regulation of histone deacetylase activity, and HCM. The PPI network constructed of significantly upregulated DEGs contained 404 nodes and 514 edges. Five hub genes, ASPM, DTL, STAT3, ANLN, and CDCA5, were identified through the PPI network. The PPI network constructed by significantly downregulated genes contained 327 nodes and 301 edges. Four hub genes, CDC42, CREB1, AR, and SP1, were identified through this PPI network. The results of CCK-8 experiments proved that knocking down the expression of CDCA5 gene could inhibit the proliferation of H9C2 cells. Conclusion. Bioinformatics analyses revealed the hub genes and key pathways of AF. These genes and pathways provide information for studying the pathogenesis, treatment, and prognosis of AF and have the potential to become biomarkers in AF treatment.

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Bioinformatics Analysis of the Molecular Mechanism of Aging on Fracture Healing

BioMed Research International ◽

10.1155/2018/7530653 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Shu-Jie Zhao ◽

Fan-Qi Kong ◽

Jin Fan ◽

Ying Chen ◽

Shuai Zhou ◽

...

Keyword(s):

Fracture Healing ◽

Bone Fracture ◽

Wnt Signaling Pathway ◽

The Elderly ◽

Gene Expression Omnibus ◽

Fracture Repair ◽

Ppi Network ◽

Network Analyses ◽

Delayed Fracture Healing ◽

Effects Of Aging

Increasing age negatively affects different phases of bone fracture healing. The present study aimed to explore underlying mechanisms related to bone fracture repair in the elderly. GSE17825 public transcriptome data from the Gene Expression Omnibus database were used for analysis. First, raw data were normalized and differentially expressed genes (DEGs) were identified. Next, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were implemented to evaluate pathways and DEGs. A protein–protein interaction (PPI) network was then constructed. A total of 726, 861, and 432 DEGs were identified between the young and elderly individuals at 1, 3, and 5 days after fracture, respectively. The results of GO, KEGG, and PPI network analyses suggested that the inflammatory response, Wnt signaling pathway, vascularization-associated processes, and synaptic-related functions of the identified DEGs are markedly enriched, which may account for delayed fracture healing in the elderly. These findings provide valuable clues for investigating the effects of aging on fracture healing but should be validated through further experiments.

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The abnormal regulation of spliceosome may be a key factor for coronary heart disease: a simple bioinformatics analysis

10.21203/rs.3.rs-62278/v1 ◽

2020 ◽

Author(s):

Zhaoshui Li ◽

Wei Sheng ◽

Yifan Chi

Keyword(s):

Gene Expression ◽

Coronary Heart Disease ◽

Heart Disease ◽

Gene Expression Omnibus ◽

Network Control ◽

Biological Database ◽

Bioinformatics Analyses ◽

Chain Reactions ◽

Go Annotation ◽

Key Factor

Abstract Background: Cardiovascular Diseases (CVDs) has become a major disease threatening human health. As the main species of CVDs, coronary heart disease (CHD) is becoming more and more common. The pathogenesis of CHD, especially at the molecular level, is not entirely clear up to now. Explaining the pathogenesis of CHD is particularly important for its treatment and prognosis. Biological database data analysis via bioinformatics has been an important method for studying gene expression strategy in multiple human disease. The aim of this study was to identify key different expressed genes (DEGs) in CHD and elucidate the biological process of it.Methods: A total of two published microarray datasets of CHD was downloaded from the Gene Expression Omnibus (GEO). Then, bioinformatics analyses including differentially expressed genes (DEGs) analysis, venn analysis, gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein and protein interaction (PPI) network construction was performed. Quantitative real-time polymerase chain reactions (RT-qPCR) were used to detect the expression levels of DEGs in CHD.Results: A total of 122 dysregulated genes were selected as DEGs in CHD. The GO annotation analysis displayed these DEGs involved in DNA transcription and mRNA splicing regulation. The DEGs regulatory network showed the downregulated genes LUC7L3, HNRNPA1, SF3B1, ARGLU1, SRSF5, SRSF11, SREK1, PNISR, DIDO1, ZRSR2 and NKTR were located in the network control center, which were the spliceosome related genes. The RT-qPCR results were consistent with our microarray analysis.Conclusion: The abnormal regulation of spliceosome might be a key factor in the development of CHD, which must play key roles in cardiovascular disease (CVD), especially in CHD. Our study has provided a new idea for the treatment and prognosis of CHD, and the spliceosome might be the potential prognostic biomarkers of it.

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Identification of Key Pathways and Genes in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis

10.21203/rs.3.rs-135813/v1 ◽

2020 ◽

Author(s):

Hao Li ◽

Shimin Zong ◽

Yingying Wen ◽

Peiyu Du ◽

Wenting Yu ◽

...

Keyword(s):

Bioinformatics Analysis ◽

Gene Expression Omnibus ◽

Cell Cycle Checkpoints ◽

Ppi Network ◽

Hub Genes ◽

Tissue Samples ◽

Protein Protein Interaction ◽

Nasopharyngeal Tissue ◽

Microarray Datasets ◽

Selection Of

Abstract Purpose: The purpose of this study is to identify novel molecular markers and potential molecular targets for NPC based on bioinformatics analysis.Methods: We used bioinformatics to analyze one miRNA and two mRNA expression microarray datasets from the Gene Expression Omnibus database. The study included nasopharyngeal tissue samples from 57 patients with NPC and 32 patients without NPC. Fifty-one screened differentially expressed genes (DEGs) were evaluated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment analyses, and a protein-protein interaction (PPI) network was constructed. Results: The GO analysis results showed that the DEGs were mainly related to cell cycle checkpoints, cell division, and DNA synthesis during DNA repair. The KEGG analysis results suggested that the DEGs were mainly associated with extracellular matrix receptor interactions. In the PPI network, we identified RAD51AP1, MAD2L1, SPP1, CCNE2, CNTNAP2, and MELK as hub genes, clustered a key module, and identified eight key transcription factors: TFII-I, Pax-5, STAT4, GR-alpha, YY1, C/EBPβ, GRβ, and TFIID. Conclusion: The hub genes and signaling pathways identified above may play an important role in NPC development and provide ideas for the selection of valuable prognostic markers and the development of new molecular-targeted drugs.

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Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽

10.1186/s12885-021-08173-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ping Yan ◽

Zuotian Huang ◽

Tong Mou ◽

Yunhai Luo ◽

Yanyao Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Malignant Tumors ◽

Expression Profiles ◽

Clinical Information ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

High Rate ◽

Competing Endogenous Rna ◽

Tissue Samples ◽

Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

BioMed Research International ◽

10.1155/2020/4505720 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Weishuang Xue ◽

Jinwei Li ◽

Kailei Fu ◽

Weiyu Teng

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Peripheral Blood ◽

Bioinformatics Analysis ◽

Gene Expression Omnibus ◽

Venn Diagram ◽

Ppi Network ◽

Hub Genes ◽

Protein Protein Interaction ◽

Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

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The Screening and Identification of Key Biomarkers in Adrenocortical Carcinoma: Evidence from a Bioinformatics Analysis

Journal of Biomaterials and Tissue Engineering ◽

10.1166/jbt.2022.2834 ◽

2022 ◽

Vol 12 (3) ◽

pp. 523-532

Author(s):

Xin Yan ◽

Chunfeng Liang ◽

Xinghuan Liang ◽

Li Li ◽

Zhenxing Huang ◽

...

Keyword(s):

Cell Cycle ◽

Gene Ontology ◽

Protein Interaction ◽

Adrenocortical Carcinoma ◽

Gene Expression Omnibus ◽

Heparin Binding ◽

Ppi Network ◽

Hub Genes ◽

Protein Protein Interaction ◽

Upregulated Genes

<sec> <title>Objective:</title> This study aimed to identify the potential key genes associated with the progression and prognosis of adrenocortical carcinoma (ACC). </sec> <sec> <title>Methods:</title> Differentially expressed genes (DEGs) in ACC cells and normal adrenocortical cells were assessed by microarray from the Gene Expression Omnibus database. The biological functions of the classified DEGs were examined by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein–protein interaction (PPI) network was mapped using Cytoscape software. MCODE software was also used for the module analysis and then 4 algorithms of cytohubba software were used to screen hub genes. The overall survival (OS) examination of the hub genes was then performed by the ualcan online tool. </sec> <sec> <title>Results:</title> Two GSEs (GSE12368, GSE33371) were downloaded from GEO including 18 and 43 cases, respectively. One hundred and sixty-nine DEGs were identified, including 57 upregulated genes and 112 downregulated genes. The Gene Ontology (GO) analyses showed that the upregulated genes were significantly enriched in the mitotic cytokines is, nucleus and ATP binding, while the downregulated genes were involved in the positive regulation of cardiac muscle contraction, extracellular space, and heparin-binding (P < 0.05). The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway examination showed significant pathways including the cell cycle and the complement and coagulation cascades. The protein– protein interaction (PPI) network consisted of 162 nodes and 847 edges, including mitotic nuclear division, cytoplasmic, protein kinase binding, and cell cycle. All 4 identified hub genes (FOXM1, UBE2C, KIF11, and NDC80) were associated with the prognosis of adrenocortical carcinoma (ACC) by survival analysis. </sec> <sec> <title>Conclusions:</title> The present study offered insights into the molecular mechanism of adrenocortical carcinoma (ACC) that may be beneficial in further analyses. </sec>

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Abstract MP216: Identification Of Novel Phosphoprotein Signaling Pathways In Human Dilated Cardiomyopathy By Integrative Proteomic And Phosphoproteomic Analysis

Circulation Research ◽

10.1161/res.129.suppl_1.mp216 ◽

2021 ◽

Vol 129 (Suppl_1) ◽

Author(s):

Cristine J Reitz ◽

Marjan Tavassoli ◽

Da Hye Kim ◽

Sina Hadipour-Lakmehsari ◽

Saumya Shah ◽

...

Keyword(s):

Dilated Cardiomyopathy ◽

Cardiac Tissue ◽

Regulatory Element ◽

Critical Role ◽

Left Ventricular ◽

Confocal Imaging ◽

Intercalated Disc ◽

Bioinformatics Analyses ◽

Tissue Samples ◽

And Function

Dilated cardiomyopathy (DCM) is one of the most common causes of heart failure, yet the majority of the underlying signaling mechanisms remain poorly characterized. Protein phosphorylation is a key regulatory element with profound effects on the activity and function of signaling networks; however, there is a lack of comprehensive phosphoproteomic studies in human DCM patients. We assessed the hypothesis that an integrative phosphoproteomics analysis of human DCM would reveal novel phosphoprotein candidates involved in disease pathophysiology. Combined proteomic and phosphoproteomic analysis of explanted left ventricular tissue samples from DCM patients ( n =4) and non-failing controls ( n =4) identified 5,570 unique proteins with 13,624 corresponding phosphorylation sites. From these analyses, we identified αT-catenin as a unique candidate protein with a cluster of 4 significantly hyperphosphorylated sites in DCM hearts ( P <0.0001), with no change in total αT-catenin expression at the protein level. Bioinformatics analyses of human datasets and confocal imaging of human and mouse cardiac tissue show highly cardiac-enriched expression of αT-catenin, localized to the cardiomyocyte intercalated disc. High resolution 3-dimensional reconstruction shows elongated intercalated disc morphology in DCM hearts (10.07±0.76 μm in controls vs. 17.20±1.87 μm in DCM, P <0.05, n =3/group), with significantly increased colocalization of αT-catenin with the intercalated disc membrane protein N-cadherin (Pearson’s coefficient 0.55±0.04 in controls vs. 0.71±0.02 in DCM, P <0.05, n =3/group). To investigate the functional role of cardiac αT-catenin phosphorylation, we overexpressed WT protein vs. non-phosphorylatable forms based on the loci identified in DCM hearts, in adult mouse cardiomyocytes using lentiviral transduction. Confocal imaging revealed significant internalization of the phospho-null form, as compared to the prominent intercalated disc staining of the WT protein (17.78±0.79% of WT vs. 9.25±0.49% of 4A mutant, P <0.0001, n =50 cells/group). Together, these findings suggest a critical role for αT-catenin phosphorylation in maintaining cardiac intercalated disc organization in human DCM.

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