scholarly journals Identification of Potential Serum Exosomal microRNAs Involved in Acinar-Ductal Metaplasia That is A Precursor of Pancreatic Cancer Associated with Chronic Pancreatitis

2020 ◽  
Author(s):  
Li-Ping Sheng ◽  
Chao-Qun Han ◽  
Chi Nie ◽  
Tao Xu ◽  
Kun Zhang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Chronic Pancreatitis ◽  
Early Diagnosis ◽  
Regulatory Network ◽  
Target Genes ◽  
Software Tool ◽  
Gene Expression Omnibus ◽  
String Database ◽  
Protein Protein Interaction ◽  
Pathway Analyses

Abstract Backgrounds Due to difficulty in early diagnosis of chronic pancreatitis (CP), it is urgent to find novel biomarkers to detect CP. Exosomal microRNAs (Exo-miRNAs) located in the serum may be potential diagnostic and therapeutic targets for CP. In our study, we performed a bioinformatics analysis to identify differentially expressed Exo-miRNAs (DE-Exo-miRNAs) in the serum of CP patients. Methods The dataset GSE128508 was downloaded from the Gene Expression Omnibus (GEO) database. The analysis was carried out using BRB-ArrayTools and Significance Analysis of Microarrays (SAM). The target genes of DE-S-Exo-miRNAs were predicted by miRWalk databases. Further gene ontology (GO) term and Kyoto Encyclopedia of Genomes (KEGG) pathway analyses were performed with plug-in ClueGO in Cytoscape software 3.7.0. Subsequently, the interaction regulatory network between encoded proteins of target genes was performed with the Search Tool for the Retrieval of Interacting Genes (STRING) database and analyzed using plug-in MCODE and cytoHubba in Cytoscape software 3.7.0. Results We identified 227 DE-Exo-miRNAs in the serum. Further analysis using the miRWalk database identified 5164 target genes of these miRNAs. The protein-protein interaction (PPI) regulatory network of 1912 potential target genes for hub 10 up-regulated miRNAs with high degrees and one down-regulated miRNAs were constructed using the STRING database and Cytoscape software. The functional analysis using Cytoscape software tool highlighted that target genes involved in pancreatic cancer. Acinar-ductal metaplasia (ADM) in the inflammatory environment of CP is a precursor of pancreatic cancer. Subsequently, we constructed a network of target genes associated with ADM and their miRNAs. Conclusions Exo-miRNAs in the serum as well as their target genes may be promising targets for the early diagnosis and treatment of CP. In addition, we identified potential Exo-miRNAs involved in ADM that is a precursor of pancreatic cancer associated with CP.

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 Comprehensive analysis of IgA nephropathy expression profiles: identification of potential biomarkers and therapeutic agents

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Alieh Gholaminejad ◽  
Yousof Gheisari ◽  
Sedigheh Jalali ◽  
Amir Roointan
Keyword(s):  
Iga Nephropathy ◽  
Regulatory Network ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Integrative Approach ◽  
Potential Factors ◽  
Ngf Signaling ◽  
Underlying Mechanisms

Abstract Background IgA nephropathy (IgAN) is a kidney disease recognized by the presence of IgA antibody depositions in kidneys. The underlying mechanisms of this complicated disease are remained to be explored and still, there is an urgent need for the discovery of noninvasive biomarkers for its diagnosis. In this investigation, an integrative approach was applied to mRNA and miRNA expression profiles in PBMCs to discover a gene signature and novel potential targets/biomarkers in IgAN. Methods Datasets were selected from gene expression omnibus database. After quality control checking, two datasets were analyzed by Limma to identify differentially expressed genes/miRNAs (DEGs and DEmiRs). Following identification of DEmiR-target genes and data integration, intersecting mRNAs were subjected to different bioinformatic analyses. The intersecting mRNAs, DEmiRs, related transcription factors (from TRRUST database), and long-non coding RNAs (from LncTarD database) were used for the construction of a multilayer regulatory network via Cytoscape. Result “GSE25590” (miRNA) and “GSE73953” (mRNA) datasets were analyzed and after integration, 628 intersecting mRNAs were identified. The mRNAs were mainly associated with “Innate immune system”, “Apoptosis”, as well as “NGF signaling” pathways. A multilayer regulatory network was constructed and several hub-DEGs (Tp53, STAT3, Jun, etc.), DEmiRs (miR-124, let-7b, etc.), TFs (NF-kB, etc.), and lncRNAs (HOTAIR, etc.) were introduced as potential factors in the pathogenesis of IgAN. Conclusion Integration of two different expression datasets and construction of a multilayer regulatory network not only provided a deeper insight into the pathogenesis of IgAN, but also introduced several key molecules as potential therapeutic target/non-invasive biomarkers.

scholarly journals Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Guangyu Gao ◽  
Zhen Yao ◽  
Jiaofeng Shen ◽  
Yulong Liu
Keyword(s):  
Drug Resistance ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Obvious Association

Dabrafenib resistance is a significant problem in melanoma, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism of drug resistance of dabrafenib and to explore the key genes and pathways that mediate drug resistance in melanoma. GSE117666 was downloaded from the Gene Expression Omnibus (GEO) database and 492 melanoma statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Besides, differentially expressed miRNAs (DEMs) were identified by taking advantage of the R software and GEO2R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) and FunRich was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential pathways and functional annotations linked with melanoma chemoresistance. 9 DEMs and 872 mRNAs were selected after filtering. Then, target genes were uploaded to Metascape to construct protein-protein interaction (PPI) network. Also, 6 hub mRNAs were screened after performing the PPI network. Furthermore, a total of 4 out of 9 miRNAs had an obvious association with the survival rate ( P < 0.05 ) and showed a good power of risk prediction model of over survival. The present research may provide a deeper understanding of regulatory genes of dabrafenib resistance in melanoma.

scholarly journals Identification of microRNAs and genes as biomarkers of atrial fibrillation using a bioinformatics approach

2019 ◽  
Vol 47 (8) ◽  
pp. 3580-3589 ◽  
Author(s):  
Yingyuan Li ◽  
Wulin Tan ◽  
Fang Ye ◽  
Faling Xue ◽  
Shaowei Gao ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Control Groups ◽  
Protein Protein Interaction ◽  
Differentially Expressed Mirnas ◽  
Software Modules ◽  
And Control

Objective We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3. Conclusion The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.

scholarly journals Association Between Depression and Breast Cancer: TNF/TNFRSF1β and LEP/LEPR Axis

2022 ◽  
Author(s):  
Jiaying Lin ◽  
Guangman Cui ◽  
Wenwei Jiang ◽  
Zhousheng Lin ◽  
Xinyue Lan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Interaction Network ◽  
Epidemiological Studies ◽  
Gene Expression Omnibus ◽  
Inflammatory Factors ◽  
Biological Mechanism ◽  
Breast Cancer Patients ◽  
Protein Protein Interaction ◽  
Genes Encoding ◽  
Pathway Analyses

Abstract Depression contributes to enhanced initiation, development and metastasis of breast cancer. Despite epidemiological studies and experimental data suggest that depression and breast cancer may share a common biological mechanism, the results from these studies remain inconsistent. Here, we fully focus on the underlying biological mechanism behind the adverse effects of depression against breast cancer patients, and highlight the practical therapeutic intervention and improving quality of life. Publicly available datasets deposited in the Gene Expression Omnibus (GEO) were downloaded. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of the differentially expressed genes (DEGs), which were extracted by using R tools, were performed. The protein-protein interaction network of the target DEGs was constructed using Cytoscape software and the hub genes were identified. In our study, we found that genes encoding proinflammatory cytokine, such as IL-1β and TNF, had significantly increased expression in depression. Following chronically stimulated by TNFα and IL-1β (usually for 14-18 days), inflammatory cancer-associated fibroblasts (CAFs) had elevated expression of inflammatory genes. Furthermore, the TNF/TNFRSF1β and LEP/LEPR regulatory axes were proven to be hub pathways of the crosstalk between depression and breast cancer. Our findings demonstrate that inflammatory factors are messengers linking depression and breast cancer, and provided further guidance in clinical medication.

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 Development and analysis of long non-coding RNA-associated competing endogenous RNA network for osteosarcoma metastasis

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yucheng Fu ◽  
Qi Liu ◽  
Qiyuan Bao ◽  
Junxiang Wen ◽  
Zhuochao Liu ◽  
...  
Keyword(s):  
Malignant Neoplasm ◽  
Gene Expression Omnibus ◽  
Messenger Rnas ◽  
Competing Endogenous Rna ◽  
Survival Analyses ◽  
Protein Protein Interaction ◽  
Cerna Network ◽  
Competing Endogenous Rna Network ◽  
New Perspective ◽  
Pathway Analyses

Abstract Background Osteosarcoma is the primary bone malignant neoplasm that often develops metastasis. Increasing evidences have shown that non-coding RNAs (ncRNAs) relate to the progression of osteosarcoma. However, the ncRNAs’ roles in osteosarcoma metastasis are still unknown. Methods Differentially expressed (DE) RNAs were identified from Gene Expression Omnibus (GEO) database. Protein-protein interaction (PPI) of DE messenger RNAs (DEmRNAs) was built through STRING database. The target mRNAs and long ncRNAs (lncRNAs) of microRNAs (miRNA) were predicted through miRDB, Targetscan and Genecode databases, which then cross-checked with previously obtained DERNAs to construct competing endogenous RNA (ceRNA) network. All networks were visualized via Cytoscape and the hub RNAs were screened out through Cytoscape plug-in Cytohubba. The gene functional and pathway analyses were performed through DAVID and MirPath databases. The survival analyses of hub RNAs were obtained through Kaplan-Meier (KM) survival curves. Results Five hundred sixty-four DEmRNAs, 16 DElncRNAs and 22 DEmiRNAs were screened out. GO functional and KEGG pathway analyses showed that DERNAs were significantly associated with tumor metastasis. The ceRNA network including 6 lncRNAs, 55 mRNAs and 20 miRNAs were constructed and the top 10 hub RNAs were obtained. Above all, PI3K/AKT signaling pathway was identified as the most important osteosarcoma metastasis-associated pathway and its hub ceRNA module was constructed. The survival analyses showed that the RNAs in hub ceRNA module closely related to osteosarcoma patients’ prognosis. Conclusions The current study provided a new perspective on osteosarcoma metastasis. More importantly, the RNAs in hub ceRNA module might act as the novel therapeutic targets and prognostic factors for osteosarcoma patients.

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.

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