scholarly journals Identification of differentially expressed genes in asthma by bioinformatics analysis

2021 ◽  
Vol 3 (2) ◽  
pp. 28-36
Author(s):  
Zhaojun Wang ◽  
Zhifeng Mo ◽  
Hongsen Liang ◽  
Qiwei Zhang ◽  
Wei Li ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Microarray Dataset ◽  
Underlying Mechanism ◽  
Gene Expression Omnibus ◽  
The Novel ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Healthy Donors

Objective Asthma is a common inflammatory disease of the airway, and its underlying mechanism is complex. The role of microRNAs (miRNAs) in asthma is unclear. The present study aimed to investigate miRNA-mRNA regulatory networks underlying asthma. Methods One microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. Differential expression of miRNAs (DEMs) was identified in bronchial epithelial cells (BECs) isolated from healthy donors and patients with asthma. MiRTarBase, mirDIP, and miRDB were used to predict target genes, followed by protein-protein interaction (PPI) network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Ontology (GO) analysis; cytoHubba was used to predict the important nodes in the network. The miRNA-hub genes sub-network of interest was determined. Results This study constructed an asthma-associated miRNA-mRNA network, in which seven key miRNAs and 10 hub genes were identified. Conclusions The novel miRNAs and hub genes identified in the present study could be potential diagnostic and treatment biomarkers for asthma.

scholarly journals Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses

2020 ◽  
Author(s):  
Basavaraj Vastrad ◽  
Chanabasayya Vastrad
Keyword(s):  
Gastric Cancer ◽  
Regulatory Network ◽  
Target Genes ◽  
Characteristic Curve ◽  
Interaction Network ◽  
Microarray Dataset ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Protein Protein Interaction

AbstractThe high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a protein protein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. The pathways and GO functions of the up and down regulated genes were mainly enriched in pyrimidine deoxyribonucleosides degradation, extracellular structure organization, allopregnanolone biosynthesis and digestion. FN1, PLK1, ANLN, MCM7, MCM2, EEF1A2, PTGER3, CKB, ERBB4 and PRKAA2 were identified as the most important genes of GC, and validated by TCGA database, The Human Protein Atlas database, receiver operating characteristic curve (ROC) analysis and RT-PCR. Bioinformatics analysis might be useful method to explore the molecular pathogensis of GC. In addition, FN1, PLK1, ANLN, MCM7, MCM2, EEF1A2, PTGER3, CKB, ERBB4 and PRKAA2 might be the most important genes of GC.

scholarly journals Construction of a MicroRNA-mRNA Network Underlying Decidualized Endometriotic Cyst Stromal Cells Using Bioinformatics Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Junzui Li ◽  
Bin Zhao ◽  
Cui Yang ◽  
Qionghua Chen
Keyword(s):  
Stromal Cells ◽  
Regulatory Networks ◽  
Target Genes ◽  
Malignant Tumors ◽  
Gene Expression Omnibus ◽  
Overlapping Genes ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
Endometriotic Cyst

Background. Decidualization of ectopic endometrium often leads to the extensive proliferation of local tissue and is easily misdiagnosed as malignant tumors. The study is aimed at constructing a microRNA- (miRNA-) mRNA network underlying decidualized endometriotic cyst stromal cells (ECSCs). Methods. All data were collected from the Gene Expression Omnibus (GEO) database. Firstly, the differentially expressed genes (DEGs, adj. P‐Val<0.05, | log FC | ≥1) and miRNAs (DEMs, P‐Val<0.05, ∣log FC∣≥1) were analyzed by the limma package. Secondly, we predicted the target genes (TGs) of these DEMs through the TargetScan, miRDB, and miRTarBase databases. The overlapping genes between DEGs and TGs were screened out. Thirdly, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses of the overlapping genes were performed for integrated discovery, visualization, and annotation. Then, the protein-protein interaction (PPI) network of the overlapping genes was conducted by the STRING database. Finally, we combined the PPI network and the miRNA-mRNA pairs to build a miRNA-mRNA network. Results. There are 29 DEMs and 523 DEGs. Fourteen overlapping genes were screened out, and these genes were significantly enriched in metabolism and immunity. What is more, a miRNA-mRNA network, including 14 mRNAs and 9 miRNAs, was successfully constructed. Conclusions. Taken together, the miRNA-mRNA regulatory networks described in this study may provide new insights in the decidualization of ECSCs, suggesting further investigations in novel pathogenic mechanisms.

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

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

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

scholarly journals Identification of key miRNA and hub genes in lung adenocarcinoma by bioinformatics and functional analysis

2020 ◽  
Author(s):  
Jiayao Zhu ◽  
Yan Zhang ◽  
Jingjing Lu ◽  
Le Wang ◽  
Xiaoren Zhu ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Target Gene ◽  
Target Genes ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Kaplan Meier ◽  
Differentially Expressed Mirnas

Abstract Background: lung adenocarcinoma is the main subtype of lung cancer and the most fatal malignant disease in the world. However, the pathogenesis of lung adenocarcinoma has not been fully elucidated.Methods: Three LUAD-associated datesets (GSE118370, GSE43767 and GSE74190) were downloaded from the Gene Expression Omnibus (GEO) datebase and the differentially expressed miRNAs (DEMs) and genes (DEGs) were screened by GEO2R. The prediction of target gene of differentially expressed miRNA were used miRWALK. Metascape was used to enrich the overlapped genes of DEGs and target genes. Then, the protein-protein interaction(PPI) and DEMs-DEGs regulatory network were created via String datebase and Cytoscape. Finally, overall survival analysis was established via the Kaplan–Meier curve and look for the possible prognostic biomarkers.Result: In this study, 433 differential genes were identified. There were 267 genes overlapped with the target gene of Dems, and eight hub genes (CDH1, CDH5, CAV1, MMP9, PECAM1, CD24, ENG, MME) were screened out. There were 85 different miRNAs in total, among which 16 miRNA target genes intersect with DEGs, 12 miRNAs with the highest interaction were screened out, and survival analysis of miRNA and hub genes was carried out.Conclusion: we found that miRNA-940, miRNA-125a-3p, miRNA-140-3p, miRNA-542-5p, CDH1, CDH5, CAV1, MMP9, PECAM1 may be related to the development of LUAD.

scholarly journals Prognostic values and prospective pathway signaling of miR-126 in non-small cell lung cancer: a study based on gene expression omnibus and bioinformatics analysis

2020 ◽  
Author(s):  
Zichen Jiao ◽  
Ao Yu ◽  
Xiaofeng He ◽  
Yulong Xuan ◽  
He Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Gene Expression Omnibus ◽  
Data Sets ◽  
Hub Genes ◽  
Biological Regulation ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Go Enrichment ◽  
Nsclc Patients

Abstract Objective MiRNAs are considered to be crucial for NSCLC’s initiation and development. MiRNAs have been widely identified in NSCLC. However, the role of miR-126 in NSCLC has not been fully explained.Methods miR-126 Expression in NSCLC was evaluated by analyzing the common data sets in Gene Expression Omnibus(GEO) database and reviewing former thesis papers. Three mRNA datasets, GSE18842, GSE19804 and GSE101929, from GEO to indentify the differentially expressed genes (DEG). We prognosed the target genes of hsa-miR-126-5p using TargetScan and analyzed the gene overlap between the target genes of miR-126 and DEG in NSCLC. Subsequently, we analyzed Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We used STRING and Cytoscape to construct a protein-protein interaction (PPI) network, and analyzed the influence of HUB gene on the prognosis of NSCLC.Results A common pattern of mir-126 downregulation in NSCLC was identified in the literature review. A total of 187 DEGs were identified, both NSCLC-related and miR-126-related. Many DEGs are extendedly enriched in cell membranes, signal receptor binding, and biological regulation. Among the 10 main Hub genes analyzed by PPI, 4 HUB genes (NCAP-G,MELK,KIAA0101,TPX2) were obviously related to the poor recuperation of NSCLC patients. When these genes highly expressed, survival rate of NSCLC patients was low. Furthermore, we identified the recessive miR-126-related genes that may be involved in NSCLC, such as TPX2, HMMR, and ANLN through network analysis.Conclusion this study suggests that mir-126 is radical for the biological processing of NSCLC.

Bioinformatics Analysis of Prognostic value and prospective Pathway signal of miR-30a in Ovarian Cancer

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

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

Identification of the Expression Signature and Potential Mechanisms of miR-493-3p in NSCLC using Bioinformatics Strategy: A Comprehensive Study from TCGA and GEO Datasets

2020 ◽  
Author(s):  
hongbo zou ◽  
Hong Zou ◽  
Mao Luo ◽  
Qichao Xie ◽  
Lijun Zhong
Keyword(s):  
Target Genes ◽  
Tumor Stage ◽  
Tissue Expression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Ph Domain ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Human Protein Atlas ◽  
Protein Phosphatase 2

Abstract Background Recent evidence highlights that miR-493-3p serve as crucial regulators of tumorigenesis. Nevertheless, the expression and clinical roles of miR-493-3p has been rarely reported in non-small cell lung cancer (NSCLC). Thus, this study was aim to investigate the expression status and potential mechanism of miR-493-3p in NSCLC progression. Methods We initially examined the expression of miR-493-3p in NSCLC through The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) microarrays. The overlap of the conjecture miR-493-3p target genes and down-regulated genes in NSCLC from TCGA were identified as the possible miR-493-3p target genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and protein-protein interaction (PPI) network were constructed to explore the biological function and hub genes of miR-493-3p targets. The expression pattern and prognosis value of key hub genes were examined by Genotype-Tissue Expression (GTEx) database, The Human Protein Atlas and Kaplan- Meier Plotter database. Results miR-493-3p was significantly increased in NSCLC tissues and connected with tumor stage in TCGA and GEO database. A total of 46 genes were identified as miR-493-3p targets, and those involved in various key pathways by GO and KEGG analysis. Furthermore, PH domain and leucine-rich repeat protein phosphatase 2 (PHLPP2) was indicated of miR-493-3p key targets, which low-expressed in NSCLC and predicted better overall survival. Conclusions Our study emphasized that up-regulated miR-493-3p may target PHLLP2 and predicate worse prognosis of NSCLC patients.

scholarly journals Bioinformatics analysis of prognostic value and prospective pathway signal of miR-30a in ovarian cancer

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Weijia Lu ◽  
Yunyu Wu ◽  
Can Xiong Lu ◽  
Ting Zhu ◽  
Zhong Lu Ren ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Target Genes ◽  
Ovarian Tissue ◽  
Critical Role ◽  
Differentially Expressed Gene ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Go Enrichment

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

scholarly journals Identification of drought-responsive hub genes and their related miRNAs in Arabidopsis thaliana

2021 ◽  
Author(s):  
Maryam Pasandideh Arjmand ◽  
Habibollah Samizadeh Lahiji ◽  
Mohammad Hassan Biglouei ◽  
Mohammad Mohsenzadeh Golfazani
Keyword(s):  
Gene Ontology ◽  
Stress Response ◽  
Target Genes ◽  
Plant Stress ◽  
Microarray Dataset ◽  
Venn Diagram ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Drought Conditions ◽  
Response To Water

Abstract Drought is important environmental stress that reduces the yield and quality of crops all around the world. The drought-responsive regulatory network is very complex in plants. MicroRNAs are an important gene expression regulator under drought conditions. Identifying drought-responsive genes and their related miRNAs helps us to provide valuable information on plant stress regulation by miRNAs in stress conditions. In this study, a microarray dataset of drought stress and well-water samples of Arabidopsis were analyzed to identify the common root and shoot genes in drought. GEO2R tool was used for identifying differentially expressed genes. Gene ontology enrichment, protein-protein interaction, pathway analysis, and potential miRNAs for hub genes were performed using bioinformatics tools. There were 486 and 288 DEGs of root and shoot tissue respectively. Venn diagram analysis demonstrated that 59 DEGs were common in both root and shoot tissues, including 51 upregulated genes and 8 downregulated genes enriched in response to water deprivation, response to osmotic stress, response to abscisic acid, response to oxidative stress, response to salt stress and other related pathways. Gene ontology and protein network analysis showed that TSPO, LTI78, AFP1, RAB18, LTI65, HAI1, HAI2, LEA4-5, LEA7, and F16B3.11 genes are hub genes in drought conditions. All hub genes except LEA7 and F16B3.11 were target genes of miRNAs. It seems that these genes and their related miRNAs can play a crucial role in drought response adaptation and they can be considered in breeding programs and genetic engineering for the production of drought-tolerant plants.

scholarly journals Analysis of key genes and pathways associated with the pathogenesis of intervertebral disc degeneration

2020 ◽  
Author(s):  
Shiyu Hu ◽  
Yucheng Fu ◽  
Bin Yan ◽  
Zhe Shen ◽  
Tao Lan
Keyword(s):  
Intervertebral Disc ◽  
Disc Degeneration ◽  
Intervertebral Disc Degeneration ◽  
Target Genes ◽  
Underlying Mechanism ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Matrix Organization ◽  
Underlying Mechanisms ◽  
Upregulated Genes

Abstract Background: Intervertebral disc degeneration (IDD) is widely known as a main contributor to low back pain which has a negative socioeconomic impact worldwide. However, the underlying mechanism remains unclear. This study aims to analyze the dataset GSE23130 using bioinformatics methods to identify the pivotal genes and pathways associated with IDD.Material/Methods: The gene expression data of GSE23130 was downloaded and differentially expressed genes (DEGs) were extracted from 8 samples and 15 controls. GO and KEGG pathway enrichment analyses were performed. Also, Protein–protein interaction (PPI) network was constructed and visualized, followed by identification of hub genes and key module.Results: A total of 30 downregulated and 79 upregulated genes were identified. The DEGs mainly enriched in regulation of protein catabolic process, extracellular matrix organization, collagen fibril organization, and extracellular structure organization. Meanwhile, we found that most of DEGs were primarily enriched in PI3K-Akt signaling pathway. The top 10 hub genes were FN1, COL1A2, SPARC, COL3A1, CTGF, LUM, TIMP1, THBS2, COL5A2, and TGFB1.Conclusions: In summary, key candidate genes and pathway were identified by using integrated bioinformatics analysis, which may provide insights into underlying mechanisms and offer potential target genes for the treatment of IDD.

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