Identification of novel survival-related lncRNA-miRNA-mRNA competing endogenous RNA network associated with immune infiltration in colorectal cancer.
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ABSTRACT:
SUBMITTER: Li J
PROVIDER: S-EPMC8290742 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues.MethodsThe oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp.ResultsA total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein-protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined analysis of the constructed PPI network and the MCODE results, 10 hub genes, including IL6, IL8, PTPRC, IL1B, TLR2, ITGAM, CCL2, PIK3CG, ICAM1, and PIK3CD, were detected in the network. Next, a ceRNA regulatory relationship consisting of one lncRNA (PVT1), one miRNA (hsa-miR-455-5p) and two mRNAs (SOCS3 and PLXNC1) was established. Then, we constructed the network in which the regulatory relationship between ceRNA and hub genes was summarized. Finally, our qRT-PCR results confirmed significantly higher levels of PVT1 transcript in inflamed pulp than in normal pulp tissues (p = 0.03).ConclusionOur study identified a novel lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of pulpitis.
| S-EPMC6609876 | biostudies-literature
Project description:BackgroundCholangiocarcinoma (CCA) is the second most common malignant primary liver tumor and has shown an alarming increase in incidence over the last two decades. However, the mechanisms behind tumorigenesis and progression remain insufficient. The present study aimed to uncover the underlying regulatory mechanism on CCA and find novel biomarkers for the disease prognosis.MethodThe RNA-sequencing (RNA-seq) datasets of lncRNAs, miRNAs, and mRNAs in CCA as well as relevant clinical information were obtained from the Cancer Genome Atlas (TCGA) database. After pretreatment, differentially expressed RNAs (DERNAs) were identified and further interrogated for their correlations with clinical information. Prognostic RNAs were selected using univariate Cox regression. Then, a ceRNA network was constructed based on these RNAs.ResultsWe identified a total of five prognostic DEmiRNAs, 63 DElncRNAs, and 90 DEmRNAs between CCA and matched normal tissues. Integrating the relationship between the different types of RNAs, an lncRNA-miRNA-mRNA network was established and included 28 molecules and 47 interactions. Screened prognostic RNAs involved in the ceRNA network included 3 miRNAs (hsa-mir-1295b, hsa-mir-33b, and hsa-mir-6715a), 7 lncRNAs (ENSG00000271133, ENSG00000233834, ENSG00000276791, ENSG00000241155, COL18A1-AS1, ENSG00000274737, and ENSG00000235052), and 18 mRNAs (ANO9, FUT4, MLLT3, ABCA3, FSCN2, GRID2IP, NCK2, MACC1, SLC35E4, ST14, SH2D3A, MOB3B, ACTL10, RAB36, ATP1B3, MST1R, SEMA6A, and SEL1L3).ConclusionsOur study identified novel prognostic makers and predicted a previously unknown ceRNA regulatory network in CCA and may provide novel insight into a further understanding of lncRNA-mediated ceRNA regulatory mechanisms in CCA.
| S-EPMC6451803 | biostudies-literature
Project description:The competing endogenous RNA (ceRNA) axis has been shown to play a critical role in the pathogenesis of various viral infections. Generally, the ceRNA network involves long non-coding RNAs (lncRNAs) that act as sponges for miRNA to regulate mRNA expression. However, no information is available regarding the involvement of ceRNA networks in Enterovirus type 71 (EV71) infections. In the present study, data obtained from Gene Expression Omnibus (GEO) database was analyzed using various bioinformatics tools. EV71 infection in rhabdomyosarcoma (RD) cells was associated with differential expression of six lncRNAs, 28 miRNAs, and 349 mRNAs. Gene function enrichment analysis suggested induction of cytoplasmic vesicle process upon EV71 infection. The ceRNA networks were constructed, in which 20 hub genes were predicted by protein-protein interaction. To confirm the MALAT1/miR-194-5p/DUSP1 ceRNA regulatory axis in EV71 infection, real-time quantitative polymerase chain reaction (qRT-PCR) and luciferase reporter assay were performed. The results of the study also revealed the involvement of the MALAT1/miR-194-5p axis in apoptosis induced by EV71 infection, while no association with autophagy was observed. Thus, the present study provided novel insights into the pathogenic mechanism of EV71 infection.
| S-EPMC8340214 | biostudies-literature
Project description:AimsTo construct the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network based on our microarray chip data for providing new insights into the pathogenesis of autoimmune hepatitis.MethodsThe ceRNA pairs were obtained by calculating the co-expression relationships among the differentially expressed lncRNAs (DELs), differentially expressed microRNAs (DEMis), and differentially expressed mRNAs (DEMs) with Pearson correlation analysis and hypergeometric distribution. The data of the differentially expressed genes were obtained from our previous studies in the concanavalin A-induced AIH mouse model. The biological functions of the ceRNA network were revealed by carrying out the GO and KEGG enrichment analysis. The expression of some differentially expressed genes constructed in the ceRNA pair was validated, and the correlation to liver injury was analyzed.ResultsThe mRNAs constructed in the ceRNA network were most significantly annotated in the GO terms of "inflammatory response" and enriched in "Cytokine-cytokine receptor interaction" and "MAPK signaling pathway". The differences in the expression of Gm38975, mmu-miR-125a-3p, and Map3k13 between the model group and control group were significant, and the expression of these genes at a transcriptional level was positively or negatively correlated to the activity of ALT and AST as well as the amount of MDA and NO.ConclusionOur work is the first in its kind to predict and illustrate the comprehensive lncRNA-miRNA-mRNA ceRNA network associated with the etiopathogenesis of AIH. This study indicates to lay the foundation for revealing the potential roles of ceRNAs in the occurrence of AIH and provide novel treatment targets for this disease.
| S-EPMC9790135 | biostudies-literature
Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a life-threatening lung disorder with an unknown aetiology. The roles of long non-coding RNAs (lncRNAs) and its related competing endogenous RNAs (ceRNA) network in IPF remains poorly understood. In this study, we aimed to build a lncRNA-miRNA-mRNA network and explore the pathogenesis of IPF.MethodsWe screened differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between IPF and control lung tissues from two datasets. The ceRNA network was built according to the interactions between DElncRNA, miRNA, and DEmRNA. Functional enrichment analysis of DemRNAs was performed using Metascape. CIBERSORT (Cell type Identification by Estimating Relative Subsets Of known RNA Transcripts) was applied to estimate the fraction of 22 immune cells in IPF and controls lung tissue samples. Then we investigated the correlation between immune cells and clinical traits.ResultsWe constructed a lncRNA-miRNA-mRNA network, which was composed of two DElncRNAs, 18 miRNAs, 66 DemRNAs. Functional enrichment analysis showed that the DEmRNAs mainly participated in MicroRNAs in cancer. By applying CIBERSORT, we found that IPF tissue samples had a higher proportion of plasma cells, resting mast cells and a lower proportion of resting NK cells, monocytes, neutrophils compared with control tissue samples. Also, our results indicated that immune cells were associated with the severity of IPF.ConclusionsIn summary, this is the first study to build lncRNA-miRNA-mRNA ceRNA network of IPF, which may improve our understanding of IPF pathogenesis. Our study indicates that immune cells in lung tissues may predict disease severity and participate in the development of IPF. Future prospective studies are required to confirm the findings of the current study.
| S-EPMC7330328 | biostudies-literature
Project description:BackgroundRecently, increasing evidence has uncovered the roles of mRNA-miRNA-lncRNA network in multiple human cancers. However, a systematic mRNA-miRNA-lncRNA network linked to pancreatic cancer prognosis is still absent.MethodsDifferentially expressed genes (DEGs) were first identified by mining GSE16515 and GSE15471 datasets. DAVID database was utilized to conduct functional enrichment analysis. Protein-protein interaction (PPI) network was built using STRING database, and hub genes were identified by Cytoscape plug-in CytoHubba. Upstream miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and miRNet, respectively. Expression, survival and correlation analysis for genes, miRNAs and lncRNAs were performed via GEPIA, Kaplan-Meier plotter and starBase.Results734 and 180 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analysis revealed that they were significantly enriched in focal adhesion, pathways in cancer and metabolic pathways. According to node degree, hub genes in the PPI networks were screened, such as TGFB1 and ALB. Among the top 20 hub genes, 7 upregulated genes and 2 downregulated hub genes had significant prognostic values in pancreatic cancer. 33 miRNAs were predicted to target the 9 key genes. But only high expression of 8 miRNAs indicated favorable prognosis in pancreatic cancer. Then, 90 lncRNAs were predicted to potentially bind to the 8 miRNAs. SCAMP1, HCP5, MAL2 and LINC00511 were finally identified as key lncRNAs. By combination of results from expression, survival and correlation analysis demonstrated that MMP9/ITGB1-miR-29b-3p-HCP5 competing endogenous RNA (ceRNA) sub-network was linked to prognosis of pancreatic cancer.ConclusionsIn a word, we established a novel mRNA-miRNA-lncRNA sub-network, among which each RNA may be utilized as a prognostic biomarker of pancreatic cancer.
| S-EPMC6535056 | biostudies-literature
Project description:BackgroundAccumulated studies have revealed that long non-coding RNAs (lncRNAs) play critical roles in human diseases by acting as competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-mediated ceRNA in atrial fibrillation (AF) remain unknown. In the present study, we aimed to construct the lncRNA-miRNA-mRNA network based on ceRNA theory in AF by using bioinformatic analyses of public datasets.MethodsMicroarray data sets of GSE115574 and GSE79768 from the Gene Expression Omnibus database were downloaded. Twenty-one AF right atrial appendage (RAA) samples and 22 sinus rhythm (SR) subjects RAA samples were selected for subsequent analyses. After merging all microarray data and adjusting for batch effect, differentially expressed genes were identified. Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out. A ceRNA network was constructed.ResultA total of 8 lncRNAs and 43 mRNAs were significantly differentially expressed with fold change >1.5 (p < 0.05) in RAA samples of AF patients when compared with SR. GO and KEGG pathway analysis showed that cardiac muscle contraction pathway were involved in AF development. The ceRNA was predicted by co-expressing LOC101928304/ LRRC2 from the constructional network analysis, which was competitively combined with miR-490-3p. The expression of LOC101928304 and LRRC were up-regulated in myocardial tissue of patients with AF, while miR-490-3p was down-regulated.ConclusionWe constructed the LOC101928304/miR-490-3p/LRRC2 network based on ceRNA theory in AF in the bioinformatic analyses of public datasets. The ceRNA network found from this study may help improve our understanding of lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of AF.
| S-EPMC8818759 | biostudies-literature
Project description:Colorectal cancer (CRC) is a malignant tumor with high morbidity and mortality worldwide. Recent studies have shown that long noncoding RNAs (lncRNAs) play an important role in almost all human tumors, including CRC. Competitive endogenous RNA (ceRNA) regulatory networks have become hot topics in cancer research. Tumor-infiltrating immune cells (TICs) have also been reported to be closely related to the survival and prognosis of CRC patients. In this study, we used the lncRNA-miRNA-mRNA regulatory network combined with tumor immune cell infiltration to predict the survival and prognosis of 598 CRC patients. First, we downloaded the lncRNA, mRNA, and miRNA transcriptome data of CRC patients from The Cancer Genome Atlas (TCGA) database and identified differentially expressed genes through "limma" package of R software. The ceRNA regulatory network was established by using the "GDCRNATools" R package. Then, univariate Cox analysis and least absolute shrinkage and selection operator analysis were performed to identify the optimal prognostic network nodes, including SRPX, UST, H19, SNHG7, hsa-miR-29b-3p, and TTYH3. Next, we analyzed the differences in 22 types of TICs between 58 normal subjects and 206 CRC patients and included memory CD4 T cells, dendritic cells and neutrophils in the construction of a prognostic model. Finally, we identified the relationship between the ceRNA prognostic model and the infiltrating immune cell prognostic model. In conclusion, we constructed two prognostic models that provide insights on the prognosis and treatment strategy of CRC.
| S-EPMC8281064 | biostudies-literature
Project description:BackgroundIncreasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the development and progression of tumors. Nevertheless, lncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients.MethodsThe RNA sequencing data and clinical characteristics of BC patients were obtained from the Cancer Genome Atlas database, and differentially expressed lncRNA (DElncRNAs), DEmRNAs, and DEmiRNAs were then identified between BC and normal breast tissue samples. Subsequently, the lncRNA-miRNA-mRNA ceRNA network of BC was established, and the gene oncology enrichment analyses for the DEmRNAs interacting with lncRNAs in the ceRNA network was implemented. Using univariate and multivariate Cox regression analyses, a four-lncRNA signature was developed and used for predicting the survival in BC patients. We applied receiver operating characteristic analysis to assess the performance of our model.ResultsA total of 1061 DElncRNAs, 2150 DEmRNAs, and 82 DEmiRNAs were identified between BC and normal breast tissue samples. A lncRNA-miRNA-mRNA ceRNA network of BC was established, which comprised of 8 DEmiRNAs, 48 DElncRNAs, and 10 DEmRNAs. Further gene oncology enrichment analyses revealed that the DEmRNAs interacting with lncRNAs in the ceRNA network participated in cell leading edge, protease binding, alpha-catenin binding, gamma-catenin binding, and adenylate cyclase binding. A univariate regression analysis of the DElncRNAs revealed 7 lncRNAs (ADAMTS9-AS1, AC061992.1, LINC00536, HOTAIR, AL391421.1, TLR8-AS1 and LINC00491) that were associated with OS of BC patients. A multivariate Cox regression analysis demonstrated that 4 of those lncRNAs (ADAMTS9-AS1, LINC00536, AL391421.1 and LINC00491) had significant prognostic value, and their cumulative risk score indicated that this 4-lncRNA signature independently predicted OS in BC patients. Furthermore, the area under the curve of the 4-lncRNA signature associated with 3-year survival was 0.696.ConclusionsThe current study provides novel insights into the lncRNA-related ceRNA network in BC and the 4 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of BC patients.
| S-EPMC6161429 | biostudies-literature
Project description:Cholangiocarcinoma (CCA) is a biliary malignancy which is prone to lymphatic metastasis and has a high mortality rate. This disease lacks effective therapeutic targets and prognostic molecular biomarkers. The aim of the current study was to investigate differentially expressed genes and elucidate their association with CCA and the underlying mechanisms of action. mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) obtained from 36 CCA samples and nine normal samples from The Cancer Genome Atlas were integrated. Subsequently, 1,095 differentially expressed (DE) mRNAs and 75 DE miRNAs were identified using a threshold of |log2 fold change|>2 and an adjusted P<0.01. Weighted gene co-expression network analysis was used to identify the DEmRNAs that could be key target genes in CCA. A total of 12 hub DEmRNAs were identified as targetable genes. Furthermore, the hub DEmRNAs-DElncRNAs pairs were identified using the miRTarBase and miRcode databases. Cytoscape software was used to construct and visualize the protein-protein interactions and the competing endogenous RNA network. Survival time analysis and correlation analysis were used to further evaluate the hub genes. The results obtained in the current study suggested that spalt like transcription factor 3 and OPCML intronic transcript 1 may serve an important role in the development and progression of CCA.
| S-EPMC6781644 | biostudies-literature