Construction of a lncRNA-mRNA Co-Expression Network for Nasopharyngeal Carcinoma.
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ABSTRACT:
SUBMITTER: Fan C
PROVIDER: S-EPMC9302896 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Nasopharyngeal carcinoma is a type of head and neck cancer with a high incidence in men. In the past decades, the survival rate of NPC has remained around 70%, but it often leads to treatment failure due to its distant metastasis or recurrence. The lncRNA-mRNA regulatory network has not been fully elucidated. We downloaded the NPC-related gene expression datasets GSE53819 and GSE12452 from the Gene Expression Omnibus database; GSE53819 included 18 NPC tissues and 18 normal tissues, and GSE12452 included 31 NPC tissues and 10 normal tissues. Weighted gene co-expression network analysis was performed on mRNA and lncRNA to screen out modules that were highly correlated with tumor progression. The two datasets were subjected to differential analysis after removing batch effects, and then Venn diagrams were used to screen for overlapping genes in the module genes and differential genes. The lncRNA-mRNA co-expression network was then constructed, and key mRNAs were identified by MCODE analysis and expression analysis. GSEA analysis and qRT-PCR were performed on key mRNAs. Through a series of analyses, we speculated that BTK, CD72, PTPN6, and VAV1 may be independent predictors of the prognosis of NPC patients.Taken together, our study provides potential candidate biomarkers for NPC diagnosis, prognosis, or precise treatment.
| S-EPMC9360529 | biostudies-literature
Project description:Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial-mesenchymal transition (EMT) in this resistance. Epithelial-like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial-like and mesenchymal-like cells, the module identification analysis was performed using weighted gene co-expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein-protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co-expression of miRNA-lncRNA-TF with the hub genes was reconstructed. The co-expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non-preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co-expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.
| S-EPMC9357632 | biostudies-literature
Project description:BackgroundActinic keratosis (AK) is a common premalignant lesion induced by chronic exposure to ultraviolet radiation and may develop into invasive cutaneous squamous carcinoma (cSCC). The identification of specific biomarkers in AK are still unclear. Long non-coding RNAs (lncRNAs), as transcripts of more than 200 nucleotides, significantly involving in multiple biologic processes, especially in the development of tumors.MethodsIn our study, we obtained data from RNA-sequencing analysis using two AK lesion tissues and three normal cutaneous tissues to comparatively analyze the differentially expressed (DE) lncRNAs and messenger RNAs (mRNAs). Firstly, we used microarray analyses to identify DE lncRNAs and DE mRNAs. Secondly, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to analyze the primary function and find out significant pathways of these DE mRNA and lncRNAs. Finally, we used the top ten DE lncRNAs to construct a lncRNA-mRNA co-expression network.ResultsOur results showed that there were a total of 2,097 DE lncRNAs and 2,043 DE mRNAs identified. GO and KEGG analysis and the lncRNA-mRNA co-expression network (using the top 10 DE lncRNAs comprises 130 specific co-expressed mRNAs to construct) indicated that lncRNA uc011fnr.2 may negatively regulate SCIMP and Toll-like receptor 4 (TLR4) and play an important role in Janus kinase-signal transducer and activator of transcription 3 (JAK-STAT3) signaling pathway of AK.ConclusionslncRNA uc011fnr.2 may play an important role in JAK-STAT3 signaling pathway of AK by modulating SCIMP, TLR4 and IL-6. Further research is required to validate the value of lncRNA uc011fnr.2 in the progression of AK.
| S-EPMC9745357 | biostudies-literature
Project description:Increasing evidence indicated that aberrant expression of long noncoding RNAs (lncRNAs) are involved in tumorigenesis of nasopharyngeal carcinoma (NPC). The purpose of this study was to construct a lncRNA-mediated ceRNA network based on weighted correlation network analysis (WGCNA). First, modules with highly correlated genes were identified from GSE102349 via WGCNA, and the preservation of the modules was evaluated by GSE68799. Then, the differentially expressed lncRNAs and mRNAs identified from GSE12452 which belonged to the same WGCNA modules and the differentially expressed miRNAs identified from GSE32960 were used to construct a ceRNA network. The prognostic value of the network was evaluated by survival analysis. Furthermore, a risk score model for predicting progression-free survival (PFS) of NPC patients was established via LASSO-penalized Cox regression, and the differences in the expression of the lncRNAs between high- and low-risk groups were investigated. Finally, 14 stable modules were identified, and a ceRNA network composed of 11 lncRNAs, 15 miRNAs, and 40 mRNAs was established. The lncRNAs and mRNAs in the network belonged to the turquoise and salmon modules. Survival analysis indicated that ZNF667-AS1, LDHA, LMNB2, TPI1, UNG, and hsa-miR-142-3p were significantly correlated with the prognosis of NPC. Gene set enrichment analysis indicated that the upregulation of ZNF667-AS1 was associated with some immune-related pathways. Besides, a risk score model consisting of 12 genes was constructed and showed a good performance in predicting PFS for NPC patients. Among the 11 lncRNAs in the ceRNA network, SNHG16, SNHG17, and THAP9-AS1 were upregulated in the high-risk group of NPC, while ZNF667-AS1 was downregulated in the high-risk group of NPC. These results will promote our understanding of the crosstalk among lncRNAs, miRNAs, and mRNAs in the tumorigenesis and progression of NPC.
| S-EPMC7569441 | biostudies-literature
Project description:Long noncoding RNAs (lncRNAs) have been shown to play important roles in various tumors including colorectal cancer (CRC). Here, we obtained data from RNA-sequencing analysis using 3 paired of CRC tissues and corresponding normal tissues. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, the biological functions of these dysregulated genes were identified. Moreover, we analyzed the expression levels of lncRNA PGM5-AS1 and B3GALT5-AS1 by quantitative real-time PCR (qRT-PCR) assay. To evaluate the accuracy of the lncRNA-mRNA co-expression network we built, we also detected PGM5 expression and analyzed the relationship between PGM5-AS1 and PGM5 in CRC. In addition, we explored the potential function of PGM5-AS1 in vitro and in vivo. In conclusion, we identified dysregulated lncRNAs and constructed the lncRNA-mRNA co-expression network in CRC. Then, we showed that the expression levels of PGM5-AS1, B3GALT5-AS1 and PGM5 were significantly downregulated in CRC tissues compared with corresponding normal tissues. Besides, PGM5-AS1 expression was positively associated with PGM5 expression. These findings were consistent with our RNA-sequencing data. Functionally, overexpression of PGM5-AS1 could induce cell apoptosis and cell cycle arrest in CRC. Animal study indicated that PGM5-AS1 overexpression inhibited CRC growth in vivo. This work provides dysregulated lncRNAs as candidates for further study in CRC. The lncRNA-mRNA co-expression network brings novel insights into further function research. More importantly, PGM5-AS1 is a critical tumor suppressor in CRC.
| S-EPMC7012094 | biostudies-literature
Project description:Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein-protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan-Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.
| S-EPMC8051809 | biostudies-literature
Project description:Long non-coding RNAs (lncRNAs) are ncRNA transcripts >200 nucleotides that are important genetic regulators. LncRNAs can directly regulate mRNA through a lncRNA-mRNA regulatory mode and can also regulate mRNA through competitive binding to micro (mi)RNA, which is generally known as the competitive endogenous RNA (ceRNA) network. The present study evaluated the functional roles and regulatory networks of lncRNAs in chronic glomerulonephritis (CGN). The proliferative ability of mouse glomerular mesangial cells (GMCs) induced by different concentrations of lipopolysaccharide (LPS) was assessed using the Cell Counting Kit-8 assay, and RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs in LPS-induced GMCs. Based on the sequencing results, six lncRNAs were selected for validation using reverse transcription-quantitative PCR (RT-qPCR). Furthermore, the lncRNA-mRNA regulatory network and the lncRNA-miRNA-mRNA ceRNA network were constructed to assess the role and mechanism of CGN-related lncRNAs. To elucidate the biological functions of lncRNAs, Gene Ontology (GO) biological process term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on all mRNAs involved in the lncRNA-mRNA regulatory network and in the ceRNA network. A total of 1,532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were identified using RNA-seq. The results of RT-qPCR validation were consistent with RNA-seq results. An lncRNA-mRNA regulatory network, including 236 lncRNAs and 556 mRNAs, and a ceRNA network, including 6 lncRNAs, 18 miRNAs and 419 mRNAs, were successfully constructed. The GO biological process term enrichment and KEGG pathway enrichment analyses demonstrated that those lncRNAs were often related to inflammatory response and substance metabolism. The present study identified key CGN-related lncRNAs in LPS-induced GMCs, and further demonstrated a global view of the lncRNA-mRNA regulatory network and ceRNA network involved in CGN. These results offered novel insights into the roles of lncRNAs in the pathogenesis of CGN and identified potential diagnostic biomarkers.
| S-EPMC10375445 | biostudies-literature
Project description: Not available
| S-EPMC7905107 | biostudies-literature
Project description:BackgroundIntracerebral hemorrhage (ICH) is a severe subtype of stroke lacking effective pharmacological targets. Long noncoding RNA (lncRNA) has been confirmed to participate in the pathophysiological progress of various neurological disorders. However, how lncRNA affects ICH outcomes in the acute phase is not completely clear. In this study, we aimed to reveal the relationship of lncRNA-miRNA-mRNA following ICH.MethodWe conducted the autologous blood injection ICH model and extracted total RNAs on day 7. Microarray scanning was used to obtain mRNA and lncRNA profiles, which were validated by RT-qPCR. GO/KEGG analysis of differentially expressed mRNAs was performed using the Metascape platform. We calculated the Pearson correlation coefficients (PCCs) of lncRNA-mRNA for co-expression network construction. A competitive endogenous (Ce-RNA) network was established based on DIANALncBase and miRDB database. Finally, the Ce-RNA network was visualized and analyzed by Cytoscape.ResultsIn total, 570 differentially expressed mRNAs and 313 differentially expressed lncRNAs were identified (FC ≥ 2 and value of p <0.05). The function of differentially expressed mRNAs was mainly enriched in immune response, inflammation, apoptosis, ferroptosis, and other typical pathways. The lncRNA-mRNA co-expression network contained 57 nodes (21 lncRNAs and 36 mRNAs) and 38 lncRNA-mRNA pairs. The ce-RNA network was generated with 303 nodes (29 lncRNAs, 163 mRNAs, and 111 miRNAs) and 906 edges. Three hub clusters were selected to indicate the most significant lncRNA-miRNA-mRNA interactions.ConclusionOur study suggests that the top differentially expressed RNA molecules may be the biomarker of acute ICH. Furthermore, the hub lncRNA-mRNA pairs and lncRNA-miRNA-mRNA correlations may provide new clues for ICH treatment.
| S-EPMC10175784 | biostudies-literature
Project description:Background: Accumulating evidence indicates that non-coding RNAs (ncRNA), including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), can function as competitive endogenous RNAs (ceRNAs) by binding to microRNAs (miRNAs) and regulating host gene expression at the transcriptional or post-transcriptional level. Dysregulation in ceRNA network regulation has been implicated in the occurrence and development of cancer. However, the lncRNA/circRNA-miRNA-mRNA regulatory network is still lacking in nasopharyngeal carcinoma (NPC). Methods: Differentially expressed genes (DEGs) were obtained from our previous sequencing data and Gene Expression Omnibus (GEO). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) were used to explore the biological functions of these common DEGs. Through a series of bioinformatic analyses, the lncRNA/circRNA-miRNA-mRNA network was established. In additional, the external data GSE102349 was used to test the prognostic value of the hub mRNAs through the Kaplan-Meier method. Results: We successfully constructed a lncRNA/circRNA-miRNA-mRNA network in NPC, consisting of 16 lncRNAs, 6 miRNAs, 3 circRNAs and 10 mRNAs and found that three genes (TOP2A, ZWINT, TTK) were significantly associated with overall survival time (OS) in patients. Conclusion: The regulatory network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving NPC, and provide novel candidate biomarkers for evaluating the prognosis of NPC.
| S-EPMC10905391 | biostudies-literature