Comprehensive Analysis of Potential miRNA-Target mRNA-Immunocyte Subtype Network in Cerebral Infarction

2021 ◽  
pp. 1-14
Author(s):  
Xiuyan Qi ◽  
Huiqian Lin ◽  
Yongge Hou ◽  
Xiaohui Su ◽  
Yanfang Gao
Keyword(s):  
Cerebral Infarction ◽  
Mirna Target ◽  
Differential Expression Analysis ◽  
Diagnostic Value ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Target Mrna ◽  
Target Mrnas ◽  
Differentially Expressed Mirnas

<b><i>Introduction:</i></b> Cerebral infarction (CI) is one of the leading causes of serious long-term disability and mortality. <b><i>Objective:</i></b> We aimed to identify potential miRNAs and target mRNAs and assess the involvement of immunocyte infiltration in the process of CI. <b><i>Methods:</i></b> First, miRNA and mRNA data were downloaded from the Gene Expression Omnibus database, followed by differential expression analysis. Second, correlation analysis between differentially expressed mRNAs and differential immunocyte subtypes was performed through the CIBERSORT algorithm. Third, the regulatory network between miRNAs and immunocyte subtype-related mRNAs was constructed followed by the functional analysis of these target mRNAs. Fourth, correlation validation between differentially expressed mRNAs and differential immunocyte subtypes was performed in the GSE37587 dataset. Finally, the diagnostic ability of immunocyte subtype-related mRNAs was tested. <b><i>Results:</i></b> Up to 17 differentially expressed miRNAs and 3,267 differentially expressed mRNAs were identified, among which 310 differentially expressed mRNAs were significantly associated with immunocyte subtypes. Several miRNA-target mRNA-immunocyte subtype networks including hsa-miR-671-3p-ZC3HC1-neutrophils, hsa-miR-625-CD5-monocytes, hsa-miR-122-ACOX1/DUSP1/NEDD9-neutrophils, hsa-miR-455-5p-SLC24A4-monocytes, and hsa-miR-455-5p-SORL1-neutrophils were identified. LAT, ACOX1, DUSP1, NEDD9, ZC3HC1, BIN1, AKT1, DNMT1, SLC24A4, and SORL1 had a potential diagnostic value for CI. <b><i>Conclusions:</i></b> The network including miRNA, target mRNA, and immunocyte subtype may be novel regulators and diagnostic and therapeutic targets in CI.

scholarly journals Bioinformatic analysis reveals an exosomal miRNA-mRNA network in colorectal cancer

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jun Ma ◽  
Peilong Wang ◽  
Lei Huang ◽  
Jianxia Qiao ◽  
Jianhong Li
Keyword(s):  
Colorectal Cancer ◽  
Differential Expression Analysis ◽  
Rectal Adenocarcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Target Mrnas ◽  
Exosomal Mirnas ◽  
Differentially Expressed Mirnas ◽  
Exosomal Mirna

Abstract Background Exosomes play important roles in angiogenesis, drug resistance, and metastasis of colorectal cancer (CRC), but the underlying mechanism has seldom been reported. Herein, our study aimed to reveal an exosomal miRNA-mRNA network involved in CRC by performing bioinformatical analysis. Methods The mRNA and miRNA data of colon adenocarcinoma and rectal adenocarcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, and exosomal miRNAs data were downloaded from the GEO dataset GSE39833. The differential expression analysis was performed using “limma” and “edgeR”. Target mRNAs of miRNAs were predicted using FunRich 3.1.3, miRNAtap and multiMiR. The candidate mRNAs and exosomal miRNAs were obtained by intersecting two groups of differentially expressed miRNAs and intersection of the differential expressed mRNAs and the target mRNAs, respectively. Key mRNAs and exosomal miRNAs were identified by the least absolute shrinkage and selection operator regression analysis, and used to construct the exosomal miRNA-mRNA network. The network verified was by receiver operating characteristic curve, GEPIA and LinkedOmics. Functional enrichment analysis was also performed for studied miRNAs and mRNAs. Results A total of 6568 differentially expressed mRNAs and 531 differentially expressed miRNAs from TCGA data, and 166 differentially expressed exosomal miRNAs in GSE39833 dataset were identified. Next, 16 key mRNAs and five key exosomal miRNAs were identified from the 5284 candidate mRNAs and 61 candidate exosomal miRNAs, respectively. The exosomal miRNA-mRNA network with high connectivity contained 13 hub mRNAs (CBFB, CDH3, ETV4, FOXQ1, FUT1, GCNT2, GRIN2D, KIAA1549, KRT80, LZTS1, SLC39A10, SPTBN2, and ZSWIM4) and five hub exosomal miRNAs (hsa-miR-126, hsa-miR-139, hsa-miR-141, hsa-miR-29c, and hsa-miR-423). The functional annotation revealed that these hub mRNAs were mainly involved in the regulation of B cell receptor signaling pathway and glycosphingolipid biosynthesis related pathways. All hub mRNAs and hub exosomal miRNAs exhibited high diagnosis value for CRC. Furthermore, the association of the hub mRNAs with overall survival, stages, and MSI phenotype of CRC revealed their important roles in CRC progression. Conclusion This study constructed an exosomal miRNA-mRNA network which may play crucial roles in the carcinogenesis and progression of CRC, thus providing potential diagnostic biomarkers and therapeutic targets for CRC.

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.

Argonaute HITS-CLIP Reveals Global miRNA-mRNA Networks in Erythropoiesis

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 446-446 ◽  
Author(s):  
Vikram R Paralkar ◽  
Jing Luan ◽  
Srijani Sridhar ◽  
Anastassios Vourekas ◽  
Zissimos Mourelatos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mrna Stability ◽  
Mirna Target ◽  
Fetal Liver ◽  
Erythroid Cells ◽  
Protein Coding ◽  
Target Mrna ◽  
Target Mrnas ◽  
Primary Mouse ◽  
In Erythroid Cells

Abstract MicroRNAs (miRNAs) inhibit gene expression by recruiting the RNA-induced silencing complex (RISC) to specific sets of target mRNAs. However, it has been challenging to define precisely the miRNA-target mRNA interactions that occur within cells. One approach to rigorously characterizing these networks in cells of interest is to sequence mRNA fragments bound to the RISC component Argonaute using a method termed High-Throughput Sequencing of RNA isolated by Crosslinking Immunoprecipitation (HITS-CLIP). We used this approach to define miRNA-target mRNA interactions during erythropoiesis, a developmental process known to be regulated by miRNAs and dramatically impaired by loss of Argonaute function. We performed Argonaute HITS-CLIP on primary mouse fetal liver erythroblasts in 3 biological replicate experiments and used Bowtie tools to map the sequenced RNA fragments to the mouse genome. These sequences represent mature miRNAs and their bound RNA segments in erythroid cells. Remarkably, miR-451 accounted for 70% of the Ago-bound erythroid miRNA burden, with miR-142, miR-144, miR-21, miR-374 and miR-30 accounting for an additional 15%. The frequency of Ago-binding correlated well with total cellular miRNA abundance. To analyze miRNA-target interactions, we used Piranha tools to identify peaks of sequenced reads, focusing on those that map to protein coding mRNAs. We identified 3,670 peaks across the entire genome, most of which mapped to mRNA 3’ untranslated regions (UTRs) (45%) or protein coding regions (38%). The remaining peaks mapped to intergenic regions, introns, long noncoding RNA genes and pseudogenes. To identify miRNA-mRNA associations, we searched for base pair complementarity between HITS-CLIP peaks mapping to mRNAs and seed sequence matches to the top 20 miRNAs in erythroid cells, which account for 92% of total miRNAs. We matched 36% of all peaks to canonical seed sequences and 34% to non-canonical seed sequences of specific miRNAs. We compared miR451-target mRNA matches predicted by HITS-CLIP to mRNA expression datasets generated from wild-type (WT) and miR-144/451 knockout (KO) mouse fetal liver erythroblasts. mRNAs with canonical miR-451 peaks in 3’ UTRs were significantly upregulated in KO erythroblasts as compared to WT erythroblasts (p<0.0001), indicating that our HITS-CLIP study identifies true erythroid targets of miR-451. These include previously identified targets of miR-451 such as Cab39, Ywhaz and Vapa, further validating our study. We also identified previously unknown targets such as Copa and Reep5, which, along with Vapa, regulate vesicle trafficking in other cell systems, and Matr3, Patl1 and Ythdf2, which affect global mRNA stability. Study of these genes may provide further insight into the functions of miR-451 in erythropoiesis. In contrast, mRNAs with predicted miR-451 peaks within coding exons showed no change in expression. This indicates that not all Ago HITS-CLIP peaks reflect regulation of mRNA stability, and that the presence of 3’ UTR Ago peaks with canonical miRNA seed sequences predicts better this mode of post transcriptional control of gene expression. Analysis and comparison of mRNA translational regulation by 3’UTR and coding region-bound miRNAs is in progress. Overall, our results provide a comprehensive map of Ago-bound miRNAs and their biologically relevant target mRNAs in erythroid cells. This map will serve as a basis to better understand miRNA regulation of erythropoiesis. Disclosures No relevant conflicts of interest to declare.

Determining differentially expressed miRNAs and validating miRNA—target relationships using the SPRET/Ei mouse strain

2014 ◽  
Vol 26 (1-2) ◽  
pp. 94-107 ◽  
Author(s):  
S. Timmermans ◽  
F. Van Hauwermeiren ◽  
L. Puimège ◽  
L. Dejager ◽  
E. Van Wonterghem ◽  
...  
Keyword(s):  
Mouse Strain ◽  
Mirna Target ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

scholarly journals Global Transcriptome Profiling Identifies a Key Mir-185-PAK6 Axis That Promotes Survival of Leukemic Stem Cells and Drug-Insensitive Blasts in BCR-ABL+ Human Leukemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 931-931
Author(s):  
Andrew Wu ◽  
Lin Hanyang ◽  
Katharina Rothe ◽  
Min Chen ◽  
Jens Ruschmann ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Transcriptome Profiling ◽  
Differentially Expressed ◽  
Leukemic Stem Cells ◽  
Cd34 Cells ◽  
Differentially Expressed Mirnas ◽  
Resistant Cells

Abstract Chronic myeloid leukemia (CML) stem/progenitor cells and BCR-ABL+ acute lymphoblastic leukemia (ALL) blast cells are insensitive to tyrosine kinase inhibitor (TKI) monotherapies. These cells rapidly generate therapy-resistant clones in vitro and in vivo and are often responsible for disease relapse. Therefore, identification of predictive biomarkers and novel treatments that target key molecular events active in leukemic stem cells (LSCs) are needed. MicroRNAs (miRNAs) are small molecules that regulate the gene expression network and are highly deregulated in many cancers. Through global transcriptome profiling, we have recently identified 66 differentially expressed miRNAs in pre-treatment CD34+ stem/progenitor cells from CML patients (n=6) compared to healthy bone marrow (NBM) controls (n=3, adjusted P<0.05); 26 differentially expressed miRNAs were identified between subsequent IM-nonresponders and IM-responders (P<0.05). 21 differentially expressed miRNAs were successfully validated in additional IM-responders (n=11), IM-nonresponders (n=11) and NBM (n=11). Interestingly, miR-185 was discovered to be one of the most highly deregulated miRNAs, with significant reduction in CD34+ cells from IM-nonresponders compared to IM-responders (p=0.0006). This significant change was further demonstrated in CD34+ cells from CML patients (n=60) before and after 3-month TKI nilotinib treatment in a clinical trial (p<0.05). We further demonstrated that miR-185 functions as a tumor suppressor; its restored expression by lentiviral transduction in CD34+ IM-nonresponder cells significantly impaired survival of these cells and sensitized them to TKI treatment in vitro. Restored miR-185 expression in BCR-ABL+ ALL blasts led to a profound decrease in leukemia burden and significantly enhanced survival compared to controls in vivo (median survival 65 vs. 47 days, P=0.0005). Strikingly, mice injected with miR-185-transduced cells and treated with dasatinib (DA) survived much longer than recipients of control cells treated with DA (median survival 83 vs. 60 days, P=0.0018). Moreover, restoration of miR-185 expression combined with DA treatment greatly reduced in vivo long-term regenerative activity of LSCs from IM-nonresponders as compared to control cells treated with DA in NRG mice (<0.2% vs. 5% GFP+ patient cells in the BM, 25 weeks post-transplantation). We observed not only a marked reduction in GFP+CD34+ cells, but also a near elimination of GFP+CD34+CD38- LSCs that were transduced with miR-185 and treated with DA compared to control cells treated with DA, indicating that restored miR-185 expression combined with DA preferentially prevents the growth of patient-derived long-term leukemia-initiating cells in vivo. Several miRNA target genes were further identified by integrating miRNA expression profiles with gene expression profiles from the same patient samples using strand-specific RNA-seq. Based on three out of six prediction algorithms (mirBase, TargetScan, miRanda, tarBase, mirTarget2, and PicTar), PAK6, a serine/threonine-protein kinase, was found to be highly expressed in CD34+ IM-nonresponder cells compared to IM-responders (p<0.003), which correlated with reduced expression of miR-185 in these cells (p=0.0002). PAK6 was confirmed as a target gene of miR-185 by a luciferase reporter assay. Western blot analysis showed that restored miR-185 expression caused a marked decrease in protein levels of PAK6 in miR-185-transduced cells and suppression of PAK6 reduced viability of these cells. These results indicate that PAK6 is a critical target of miR-185, and that loss of miR-185 expression in CML may lead to up-regulation of PAK6, which in turn contributes to disease progression and drug resistance. Indeed, the use of a pre-clinically validated pan PAK inhibitor (PF-3758309) significantly inhibited the growth of IM-resistant cells and CD34+ IM-nonresponder cells and these effects could be enhanced by TKIs (p<0.05). Mechanistically, we observed that p-ERK and p-AKT were significantly reduced in PAK6 knockdown or miR185-restored IM-resistant cells in response to IM treatment. Thus, we infer that downregulation of PAK6 may sensitize TKI-resistant cells to TKI therapy through inhibition of the RAS/MAPK pathway. Taken together, PAK6, a novel target of miR-185, emerges as an attractive druggable target for combination therapy of TKI-resistant patients. Disclosures No relevant conflicts of interest to declare.

scholarly journals Identification and validation of key miRNAs and miRNA–mRNA regulatory network associated with uterine involution in postpartum Kazakh sheep

2021 ◽  
Vol 64 (1) ◽  
pp. 119-129
Author(s):  
Heng Yang ◽  
Lin Fu ◽  
Qifeng Luo ◽  
Licai Li ◽  
Fangling Zheng ◽  
...  
Keyword(s):  
Mirna Target ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Gene Prediction ◽  
Biological Effects ◽  
Differentially Expressed ◽  
Illumina Hiseq ◽  
Go Annotation ◽  
Uterine Involution ◽  
Differentially Expressed Mirnas

Abstract. MicroRNAs (miRNAs) are widely expressed in different mammalian tissues and exert their biological effects through corresponding target genes. miRNA target genes can be rapidly and efficiently identified and screened by combining bioinformatics prediction and experimental validation. To investigate the possible molecular regulatory mechanisms involving miRNAs during uterine involution in postpartum ewes, we used Illumina HiSeq sequencing technology to screen for the number and characteristics of miRNAs in faster uterine involution and normal uterine involution group. A total of 118 differentially expressed miRNAs, including 33 known miRNAs and 85 new miRNAs, were identified in the hypothalamic library, whereas 54 miRNAs, including 5 known miRNAs and 49 new miRNAs, were identified in the uterine library. Screening with four types of gene prediction software revealed 73 target genes associated with uterine involution, and subsequently, GO annotation and KEGG pathway analysis were performed. The results showed that, in the hypothalamic–uterine axis, uterine involution in postpartum ewes might primarily involve two miRNA-target gene pairs, namely, miRNA-200a–PTEN and miRNA-133–FGFR1, which can participate in GnRH signal transduction in the upstream hypothalamus and in the remodeling process at the downstream uterus, through the PI3K–AKT signaling pathway to influence the recovery of the morphology and functions of the uterus during the postpartum period in sheep. Therefore, identification of differentially expressed miRNAs in this study fills a gap in the research related to miRNAs in uterine involution in postpartum ewes and provides an important reference point for a comprehensive understanding of the molecular mechanisms underlying the regulation of postpartum uterine involution in female livestock.

scholarly journals MicroRNA and their target mRNAs change expression in whole blood of patients after intracerebral hemorrhage

2019 ◽  
Vol 40 (4) ◽  
pp. 775-786 ◽  
Author(s):  
Xiyuan Cheng ◽  
Bradley P Ander ◽  
Glen C Jickling ◽  
Xinhua Zhan ◽  
Heather Hull ◽  
...  
Keyword(s):  
Intracerebral Hemorrhage ◽  
Whole Blood ◽  
Killer Cell ◽  
Transcriptome Profiling ◽  
Rna Degradation ◽  
Differentially Expressed ◽  
Mrna Levels ◽  
Target Mrnas ◽  
Mrna Targets ◽  
Differentially Expressed Mirnas

Previous studies showed changes in mRNA levels in whole blood of rats and humans, and in miRNA in whole blood of rats following intracerebral hemorrhage (ICH). Thus, this study assessed miRNA and their putative mRNA targets in whole blood of humans following ICH. Whole transcriptome profiling identified altered miRNA and mRNA levels in ICH patients compared to matched controls. Target mRNAs of the differentially expressed miRNAs were identified, and functional analysis of the miRNA-mRNA targets was performed. Twenty-nine miRNAs (22 down, 7 up) and 250 target mRNAs (136 up, 114 down), and 7 small nucleolar RNA changed expression after ICH compared to controls (FDR < 0.05, and fold change ≥ |1.2|). These included Let7i, miR-146a-5p, miR210-5p, miR-93-5p, miR-221, miR-874, miR-17-3p, miR-378a-5p, miR-532-5p, mir-4707, miR-4450, mir-1183, Let-7d-3p, miR-3937, miR-4288, miR-4741, miR-92a-1-3p, miR-4514, mir-4658, mir-3689d-1, miR-4760-3p, and mir-3183. Pathway analysis showed regulated miRNAs/mRNAs were associated with toll-like receptor, natural killer cell, focal adhesion, TGF-β, phagosome, JAK-STAT, cytokine–cytokine receptor, chemokine, apoptosis, vascular smooth muscle, and RNA degradation signaling. Many of these pathways have been implicated in ICH. The differentially expressed miRNA and their putative mRNA targets and associated pathways may provide diagnostic biomarkers as well as point to therapeutic targets for ICH treatments in humans.

scholarly journals Identification of lncRNA and mRNA Biomarkers in Osteoarthritic Degenerative Meniscus by Weighted Gene Coexpression Network and Competing Endogenous RNA Network Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jun Zhao ◽  
Yu Su ◽  
Jianfei Jiao ◽  
Zhengchun Wang ◽  
Xiangchun Fang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Roc Curve ◽  
Diagnostic Value ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Coexpression Network ◽  
Competing Endogenous Rna ◽  
Roc Curve Analysis ◽  
Competing Endogenous Rna Network ◽  
Meniscus Degeneration

Background. Long noncoding RNAs (lncRNAs) play a crucial role in varieties of biological processes. This study is aimed at investigating meniscal degeneration-specific lncRNAs and mRNAs and their related networks in knee osteoarthritis (KOA). Methods. The dataset GSE98918, which included 24 meniscus samples and related clinical data, was downloaded from the Gene Expression Omnibus database. The differentially expressed lncRNAs and mRNAs in the meniscus between KOA and control groups were identified. Based on the enriched differentially expressed lncRNAs and mRNAs, we constructed the coexpression network using WGCNA (weighted correlation network analysis) and identified the critical module related to KOA. For mRNAs in the key module, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were carried out using the DAVID database. A competing endogenous RNA network (ceRNA) based on the screened mRNAs, lncRNAs, and related miRNAs was constructed to reveal presumptive biomarkers further. Finally, the hub lncRNAs and mRNAs were screened, and the diagnostic value was evaluated using a receiver operating characteristic (ROC) curve. Hub mRNAs were validated using the dataset GSE113825. Results. We screened 208 significantly differentially expressed lncRNAs and mRNAs in menisci between the KOA and non-KOA samples, which were enriched in sixteen modules using WGCNA, especially the green module. Coexpression network based on the enriched differentially expressed lncRNAs and mRNAs in the green module uncovered 5 lncRNAs and 56 mRNAs. The lncRNA-miRNA-mRNA ceRNA network revealed that lnc-HLA-DQA1-5, lnc-RP11-127H5.1.1-1, lnc-RTN2-1, IGFBP4 (insulin-like growth factor binding protein 4), and KLF2 (Kruppel-like factor 2) were significantly correlated with the meniscus degeneration of KOA. ROC curve analysis revealed that these hub lncRNAs and mRNAs showed excellent diagnostic value for KOA. Conclusions. These hub lncRNAs and mRNAs were potential prognostic biomarkers for the meniscus degeneration of KOA. Further studies are required to validate these new biomarkers and better understand the pathological process of the meniscus degeneration of KOA.

scholarly journals Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

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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