Identification and Validation of Immune-Related Biomarker Gene and Construction of ceRNA Networks in Septic Cardiomyopathy.
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ABSTRACT:
SUBMITTER: Li J
PROVIDER: S-EPMC9243365 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Immune targeted therapy has become an attractive therapeutic approach for patients with dilated cardiomyopathy (DCM) recently. Genetic predisposition and gender play a critical role in immune-related responses of DCM. This study aimed to perform a bioinformatics analysis of molecular differences between male and female samples and identify immune-related ceRNA network in DCM. Methods: The gene expression microarray and clinical features dataset of GSE19303 was downloaded from the GEO. The raw data were preprocessed, followed by identification of differentially expressed genes (DEGs) between male and female DCM samples. Crucial functions and pathway enrichment analysis of DEGs were investigated through GO analysis and KEGG pathway analysis, respectively. A lncRNA-miRNA-mRNA network was constructed and a central module was extracted from the ceRNA network. Results: Compared with the female group, the male group benefits more from IA/IgG immunotherapy. Male patients of DCM had a significant positive correlation with the abundance of inflammatory cells (B cells, memory B cells, CD8+ Tem cells, and NK cells). Sex difference DEGs had a widespread impact on the signaling transduction, transcriptional regulation, and metabolism in DCM. Subsequently, we constructed an immune-related ceRNA network based on sex differences in DCM, including five lncRNAs, six miRNAs, and 29 mRNAs. Furthermore, we extracted a central module from the ceRNA network, including two lncRNAs (XIST and LINC00632), three miRNAs (miR-1-3p, miR-17-5p, and miR-22-3p), and six mRNAs (CBL, CXCL12, ESR1, IGF1R, IL6ST, and STC1). Among these DEGs, CBL, CXCL12, and IL6ST expression was considered to be associated with inflammatory cell infiltration in DCM. Conclusions: The identified ceRNA network and their enriched pathways may provide genetic insights into the phenotypic diversity of female and male patients with DCM and may provide a basis for development of sex-related individualization of immunotherapy.
| S-EPMC9214033 | biostudies-literature
Project description:BackgroundThe immune infiltration and molecular mechanisms underlying septic cardiomyopathy (SC) have not been completely elucidated. This study aimed to identify key genes related to SC and elucidate the potential molecular mechanisms.MethodsThe weighted correlation network analysis (WGCNA), linear models for microarray analysis (LIMMA), protein-protein interaction (PPI) network, CIBERSORT, Kyoto Encyclopedia of Genes and Genomes pathway (KEGG), and gene set enrichment analysis (GSEA) were applied to assess the key pathway and hub genes involved in SC.ResultsWe identified 10 hub genes, namely, LRG1, LCN2, PTX3, E LANE, TCN1, CLEC4D, FPR2, MCEMP1, CEACAM8, and CD177. Furthermore, we used GSEA for all genes and online tools to explore the function of the hub genes. Finally, we took the intersection between differential expression genes (DEGs) and hub genes to identify LCN2 and PTX3 as key genes. We found that immune-related pathways played vital roles in SC. LCN2 and PTX3 were key genes in SC progression, which mainly showed an anti-inflammatory effect. The significant immune cells in cardiomyocytes of SC were neutrophils and M2 macrophages.ConclusionThese cells may have the potential to be prognostic and therapeutic targets in the clinical management of SC. Excessive anti-inflammatory function and neutrophil infiltration are probably the primary causes of SC.
| S-EPMC10002421 | biostudies-literature
Project description:Septic cardiomyopathy (SCM) is a cardiac dysfunction caused by severe sepsis and septic shock that increases the risk of heart failure and death and its molecular mechanism remains unclear. Ferroptosis, a novel form of programmed cell death, has been reported to be present in the heart tissue of patients with sepsis, which demonstrated that ferroptosis may be a potential mechanism of myocardial injury in SCM. Therefore, we explored the role of ferroptosis-related genes (FRGs) in SCM and aimed to identify pivotal ferroptosis-related targets in SCM and potential therapeutic targets involved in the pathological process of SCM. To explore the regulatory mechanisms of ferroptosis in SCM, we identified differentially expressed genes (DEGs) in SCM and FRGs by bioinformatics analysis, and further identified hub genes. And the crucial microRNAs (miRNAs)-FRGs regulatory network was subsequently constructed. Finally, several candidate drugs associated with the hub genes were predicted, and Real-time quantitative reverse Transcription PCR (qRT-PCR) and western blotting analysis were performed to confirm the abnormal expression of hub genes. In this study, we identified several FRGs that may be involved in the pathogenesis of SCM, which helps us further clarify the role of ferroptosis in SCM and deeply understand the molecular mechanisms and potential therapeutic targets of SCM.
| S-EPMC9043284 | biostudies-literature
Project description:Diabetic cardiomyopathy (DCM), a common complication of diabetes, is defined as ventricular dysfunction in the absence of underlying heart disease. Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), play a crucial role in the development of DCM. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key modules in DCM-related pathways. DCM-related miRNA-mRNA network and DCM-related ceRNA network were constructed by miRNA-seq to identify hub genes in these modules. We identified five hub genes that are associated with the onset of DCM, including Troponin C1 (Tnnc1), Phospholamban (Pln), Fatty acid binding proteins 3 (Fabp3), Popeye domain containing 2 (Popdc2), and Tripartite Motif-containing Protein 63 (Trim63). miRNAs that target the hub genes were mainly involved in TGF-β and Wnt signaling pathways. GO BP enrichment analysis found these miRNAs were involved in the signaling of TGF-β and glucose homeostasis. Q-PCR results found the gene expressions of Pln, Fabp3, Trim63, Tnnc1, and Popdc2 were significantly increased in DCM. Our study identified five hub genes (Tnnc1, Pln, Fabp3, Popdc2, Trim63) whose associated ceRNA networks are responsible for the onset of DCM.
| S-EPMC10290640 | biostudies-literature
Project description:MicroRNAs (miRNAs) play multiple roles in tumor biology. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration. Specifically, computational models predicted and experimental assays confirmed that miRNA activity is dependent on miRNA target abundance, and consequently, changes in the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. The resulting indirect regulatory influence between miRNA targets resembles competition and has been dubbed competitive endogenous RNA (ceRNA). Recent studies have questioned the physiological relevance of ceRNA interactions, our ability to accurately predict these interactions, and the number of genes that are impacted by ceRNA interactions in specific cellular contexts.To address these concerns, we reverse engineered ceRNA networks (ceRNETs) in breast and prostate adenocarcinomas using context-specific TCGA profiles, and tested whether ceRNA interactions can predict the effects of RNAi-mediated gene silencing perturbations in PC3 and MCF7 cells._ENREF_22 Our results, based on tests of thousands of inferred ceRNA interactions that are predicted to alter hundreds of cancer genes in each of the two tumor contexts, confirmed statistically significant effects for half of the predicted targets.Our results suggest that the expression of a significant fraction of cancer genes may be regulated by ceRNA interactions in each of the two tumor contexts.
| S-EPMC5450082 | biostudies-other
Project description:IntroductionHodgkin lymphoma (HL) is a type of lymphoma common throughout the western countries. However, the detailed mechanisms and special biomarkers of HL remain to be further investigated. Emerging studies have shown that long non-coding RNAs play a key role in human cancers.Material and methodsIn the present work, we constructed relapse-related lncRNA-mediated ceRNA networks in HL. Additionally, we constructed co-expression networks for these relapse-related lncRNAs. We also constructed a relapse-related lncRNA-miRNA-mRNA network to study the potential mechanism of these lncRNAs. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to explore functions of DEGs in Hodgkin lymphoma.ResultsA total of 18 lncRNAs were found to be dysregulated between early relapse and late relapse HL. Six lncRNAs (PCBP1-AS1, HCG18, GAS5, PSMD6-AS2, PRKCQ-AS1, SNHG6), 116 mRNAs and 121 miRNAs were included in the ceRNA network. Bioinformatics analyses revealed that these lncRNAs were significantly involved in regulating immune system processes, responses to chemical stimuli and responses to stress. Among them, HCG18 and PCBP1-AS1 were identified as key lncRNAs in HL relapse.ConclusionsOur results for the first time constructed the key relapse-related lncRNA-mediated ceRNA networks in Hodgkin lymphoma progression. We trust that this work will provide a new therapeutic and prognostic target for HL.
| S-EPMC7667426 | biostudies-literature
Project description:BackgroundSepsis is a high mortality disease which seriously threatens human life and health, for which the pathogenetic mechanism still unclear. There is increasing evidence showed that immune and inflammation responses are key players in the development of sepsis pathology. LncRNAs, which act as ceRNAs, have critical roles in various diseases. However, the regulatory roles of ceRNA in the immunopathogenesis of sepsis have not yet been elucidated.ResultsIn this study, we aimed to identify immune biomarkers associated with sepsis. We first generated a global immune-associated ceRNA (IMCE) network based on data describing interactions pairs of gene-miRNA and miRNA-lncRNA. Afterward, we excavated a dysregulated sepsis immune-associated ceRNA (SPIMC) network from the global IMCE network by means of a multi-step computational approach. Functional enrichment indicated that lncRNAs in SPIMC network have pivotal roles in the immune mechanism underlying sepsis. Subsequently, we identified module and hub genes (CD4 and STAT4) via construction of a sepsis immune-related PPI network. Then, we identified hub genes based on the modular structure of PPI network and generated a ceRNA subnetwork to analyze key lncRNAs associated with sepsis. Finally, 6 lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) that identified as immune biomarkers of sepsis. Moreover, the CIBERSORT algorithm and the infiltration of circulating immune cells types were performed to identify the inflammatory state of sepsis. Correlation analyses between immune cells and sepsis immune biomarkers showed that the LINC00265 was strongly positive correlated with the macrophages M2 (r = 0.77).ConclusionCollectively, these results may suggest that these lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) played important roles in the immune pathogenesis of sepsis and provide potential therapeutic targets for further researches on immune therapy treatment in patients with sepsis.
| S-EPMC10464037 | biostudies-literature
Project description:Ulcerative colitis (UC) is a common disease with great variability in severity, with a high recurrence rate and heavy disease burden. In recent years, the different biological functions of competing endogenous RNA (ceRNA) networks of long noncoding RNAs (lncRNAs) and microRNAs (miRs) have aroused wide concerns, the ceRNA network of ulcerative colitis (UC) may have potential research value, and these expressed noncoding RNAs may be involved in the molecular basis of inflammation recurrence and progression. This study analyzed 490 colon samples associated with UC from 4 gene expression microarrays from the GEO database and identified gene modules by weighted correlation network analysis (WGCNA). CIBERSORT detected tissue-infiltrating leukocyte profiling by deconvolution of microarray data. LncBase and multiMIR were used to identify lncRNA-miRNA-mRNA interaction. We constructed a ceRNA network which includes 4 lncRNAs (SH3BP5-AS1, MIR4435-2HG, ENTPD1-AS1, and AC007750.1), 5 miRNAs (miR-141-3p, miR-191-5p, miR-192-5p, miR-194-5p, and miR196-5p), and 52 mRNAs. Those genes are involved in interleukin family signals, neutrophil degranulation, adaptive immunity, and cell adhesion pathways. lncRNA MIR4435-2HG is a variable in the decision tree for moderate-to-severe UC diagnostic prediction. Our work identifies potential regulated inflammation-related lncRNA-miRNA-mRNA regulatory axes. The regulatory axes are dysregulated during the deterioration of UC, suggesting that it is a risk factor for UC progression.
| S-EPMC8277522 | biostudies-literature
Project description:BackgroundsApproximately 75% of bladder cancer occurrences are of the non-muscle-invasive type. The estimated five-year survival rate is 26%-55%. Currently, there is no reliable biomarker available for early diagnosis and prognosis of bladder cancer. The present study aims to identify a biomarker using bioinformatic approaches to provide a new insight in clinical research for early diagnosis and prognosis of bladder cancer.MethodsClinical data and a transcriptome of bladder cancer were obtained from TCGA, GEO, GETx, and UCSC Xena. The differential expressed gene (DEG) analysis, weighted gene co-expression network analysis (WGCNA), and survival analysis using the Kaplan-Meier and Cox proportional-hazards models were used to identify the Microtubule-associated Proteins 1A (MAP1A). on overall survival (OS) and disease-free survival (DFS) was analyzed using GEPIA and GETx databases. The TIMER 2.0 database predicted the correlation between MAP1A and immunocytes and immune checkpoints. Target prediction of the regulated competing endogenous RNAs (ceRNAs) network of MAP1A was performed using starBase and TargetScan. Cystoscope v3.7.2 software was used to visualize the ceRNA coexpression network. The R programming language v4.0.2 was applied as an analytic tool. Gene expression of MAP1A verified by RT-qPCR.ResultsThe low expression of MAP1A was verified in bladder cancer tissues and bladder cancer cell lines SW780 and 5637. P < 0.001 were obtained by Kaplan-Meier survival analysis and Cox proportional hazards model, with a hazard ratio (HR) of 1.4. Significant correlations between MAP1A and OS (P < 0.001, HR = 1.9) as well as DFS (P < 0.05, HR = 1.7) in bladder cancer were identified through gene expression profiling interactive analysis (GEPIA), indicating MAP1A may be a high-risk factor. Significant correlation in single copy-number variation of MAP1A gene with CD8+ T cells, and myeloid dendritic cells (MDCs) (P < 0.05) was noted. MAP1A expression was shown to be significantly correlated with the amount of CD4+ T cells and CD8+ T cells, MDCs, macrophages, and neutrophils in a statistically significant positive manner (P < 0.001). However, the MAP1A expression demonstrated a strong negative connection with B cells (P < 0.001). Except for macrophage M1 genes IRF5 and PTGS2, MAP1A expression was significantly correlated with the gene levels in immunocytes such as CD4+ T cells, CD8+ T cells, B cells, dendritic cells (DCs), macrophages, and neutrophils (Cor > 0.2, P < 0.001), as well as immune checkpoint related genes including cytotoxic t-lymphocyte-associated protein 4 (CTLA-4), programmed death 1 (PD-1), programmed death ligand 1 (PD-L1) (P < 0.001). Finally, we predicted that the MAP1A-interacting miRNA was miR-34a-5p, and the MAP1A endogenous competing RNAs were LNC00667, circ_MAP1B, and circ_MYLK, respectively. These findings support the need for further studies on the mechanism underlying the pathogenesis of this disease.ConclusionMAP1A is considered as a prospective biomarker for early diagnosis, therapeutic observation, and prognosis analysis in bladder cancer.
| S-EPMC9667867 | biostudies-literature
Project description:ObjectivesTo identify long noncoding RNAs (lncRNAs) and construct a competing endogenous RNA (ceRNA) network for essential hypertension.MethodsAn RNA microarray and two-step quantitative real-time PCR were applied to identify differentially expressed RNAs (DE-RNAs), and a luciferase assay was performed to explore the binding relationship between RNAs. A generalized linear model and logistic regression model were used to analyze the associations between different RNAs and of RNAs with hypertension. Receiver operating characteristic curve analysis was executed to evaluate the diagnostic performance. Bioinformatics analysis was applied for network construction.ResultsIn total, 439 DE-RNAs (387 lncRNAs and 52 mRNAs) were identified in the microarray, and 71 'lncRNA-miRNA-mRNA' loops formed the ceRNA network. The first validation confirmed that five RNAs (NR_104160, lnc-GPR63-8:1, lnc-HPRT1-9:1, ID1 and RSL24D1) were significantly upregulated in hypertensives (P < 0.05). NR_104160 was significantly associated with hypertension (OR = 2.863, 95% CI: 1.143-7.172; P = 0.025) after adjusting for confounding factors. NR_104160 was included in the hypertension diagnostic model, with an area under the curve of 0.852 (95% CI: 0.761-0.944). In the second validation, NR_104160 showed a constant significant difference (P = 0.001). An elevated expression level of NR_104160 was associated with the expression of ID1 (β = 0.2235, P = 0.005). Luciferase assays showed hsa-miR-101-3p stimulation significantly inhibited the reporter gene activation ability of the NR_104160 wild-type plasmid (P < 0.001).ConclusionsOur study constructed a ceRNA network to provide hypotheses regarding the mechanism of hypertension development. lncRNA-NR_104160 was identified as a hub element that participates in hypertension transcriptional regulation and as a potential biomarker.
| S-EPMC7653565 | biostudies-literature