Bioinformatics Analysis of the MicroRNA-Metabolic Gene Regulatory Network in Neuropathic Pain and Prediction of Corresponding Potential Therapeutics.
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ABSTRACT:
SUBMITTER: Zhang HG
PROVIDER: S-EPMC8476070 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Neuropathic pain is a chronic pain condition seen in patients with diabetic neuropathy, cancer chemotherapy-induced neuropathy, idiopathic neuropathy as well as other diseases affecting the nervous system. Only a small percentage of people with neuropathic pain benefit from current medications. The complexity of the disease, poor identification/lack of diagnostic and prognostic markers limit current strategies for the management of neuropathic pain. Multiple genes and pathways involved in human diseases can be regulated by microRNA (miRNA) which are small non-coding RNA. Several miRNAs are found to be dysregulated in neuropathic pain. These miRNAs regulate expression of various genes associated with neuroinflammation and pain, thus, regulating neuropathic pain. Some of these key players include adenylate cyclase (Ac9), toll-like receptor 8 (Tlr8), suppressor of cytokine signaling 3 (Socs3), signal transducer and activator of transcription 3 (Stat3) and RAS p21 protein activator 1 (Rasa1). With advancements in high-throughput technology and better computational power available for research in present-day pharmacology, biomarker discovery has entered a very exciting phase. We dissect the architecture of miRNA biological networks encompassing both human and rodent microRNAs involved in the development of neuropathic pain. We delineate various microRNAs, and their targets, that may likely serve as potential biomarkers for diagnosis, prognosis, and therapeutic intervention in neuropathic pain. miRNAs mediate their effects in neuropathic pain by signal transduction through IRAK/TRAF6, TLR4/NF-κB, TXIP/NLRP3 inflammasome, MAP Kinase, TGFβ and TLR5 signaling pathways. Taken together, the elucidation of the landscape of signature miRNA regulatory networks in neuropathic pain will facilitate the discovery of novel miRNA/target biomarkers for more effective management of neuropathic pain.
| S-EPMC8914318 | biostudies-literature
Project description:Neuropathic pain (NP) is poorly managed, and in-depth mechanisms of gene transcriptome alterations in NP pathogenesis are not yet fully understood. To determine microRNA-related molecular mechanisms of NP and their transcriptional regulation in NP, PubMed, Embase, Web of Science and CINAHL Complete (EBSCO) were searched from inception to April 2021. Commonly dysregulated miRNAs in NP were assessed. The putative targets of these miRNAs were determined using TargetScan, Funrich, Cytoscape and String database. A total of 133 literatures containing miRNA profiles studies and experimentally verify studies were included. Venn analysis, target gene prediction analysis and functional enrichment analysis indicated several miRNAs (miR-200b-3p, miR-96, miR-182, miR-183, miR-30b, miR-155 and miR-145) and their target genes involved in known relevant pathways for NP. Targets on transient receptor potential channels, voltage-gated sodium channels and voltage-gated calcium channels may be harnessed for pain relief. A further delineation of signal processing and modulation in neuronal ensembles is key to achieving therapeutic success in future studies.
| S-EPMC8794747 | biostudies-literature
Project description:The molecular mechanisms underlying neuropathic pain (NP) remain poorly understood. Emerging evidence has suggested the role of microRNAs (miRNAs) in the initiation and development of NP, but the specific effects of miRNAs in NP are largely unknown. Here, we use network- and pathway-based methods to investigate NP-induced miRNA changes and their biological functions by conducting a systematic search through multiple electronic databases. Thirty-seven articles meet the inclusion criteria. Venn analysis and target gene forecasting are performed and the results indicate that 167 overlapping target genes are co-regulated by five down-regulated miRNAs (rno-miR-183, rno-miR-96, rno-miR-30b, rno-miR-150 and rno-miR-206). Protein-protein interaction network analysis shows that 77 genes exhibit interactions, with cyclic adenosine monophosphate (cAMP)-dependent protein kinase catalytic subunit beta (degree = 11) and cAMP-response element binding protein 1 (degree = 10) having the highest connectivity degree. Gene ontology analysis shows that these target genes are enriched in neuron part, neuron projection, somatodendritic compartment and nervous system development. Moreover, analysis of Kyoto Encyclopedia of Genes and Genomes reveals that three pathways, namely, axon guidance, circadian entrainment and insulin secretion, are significantly enriched. In addition, rno-miR-183, rno-miR-96, rno-miR-30b, rno-miR-150 and rno-miR-206 are consistently down-regulated in the NP models, thus constituting the potential biomarkers of this disease. Characterizing these miRNAs and their target genes paves way for their future use in clinical practice.
| S-EPMC6584487 | biostudies-literature
Project description:ObjectiveTo reveal the involvement of molecules in the pathogenesis of B-cell acute lymphoblastic leukemia (B-ALL) by bioinformatics analyses.MethodsThe microarray data of B-ALL were downloaded from the Gene Expression Omnibus (GEO) database and Qlucore Omics Explorer software was used to screen differentially expressed miRNA. Based on the differentially expressed miRNAs, we predicted the target genes, long non-coding RNAs (lncRNA) and transcription factors (TFs). Then we constructed the miRNAs-centered comprehensive regulatory network. In addition, we performed functional enrichment analysis to analyze the functions of target genes.ResultsOf all the 15 differentially expressed miRNAs, 7 miRNAs were of overexpression, 8 miRNAs underexpressed. From the miRNAs comprehensive regulatory network, we found that hsa-miR-486-3p and hsa-miR-126 regulated a large number of target genes, hsa-miR-126 including target genes MYC. The hsa-miR-29a, hsa-miR-130a and hsa-miR-181c regu- lated a lot of lncRNAs containing X-inactive-specific transcript (XIST). The hsa-miR-181a-2, hsa-miR- 181b-2 and hsa-miR-663 were regulated by a host of TFs including caudal- related homeobox transcription fact2 (CDX2). Additionally, the target genes of has-miR-126 were enriched in Wnt pathways.ConclusionsThe expression of hsa-miR-29a , hsa-miR-126 and has-miR-181 family were significantly different in B-ALL. Target gene of MYC, TFs of CDX2 and lncRNA of XIST may play important roles in the development of B-ALL, serving as a potential therapeutic target.
| S-EPMC7365002 | biostudies-literature
Project description:MicroRNA (miRNA) expression has been found to be deregulated in human cancer, contributing, in part, to the interest of the research community in using miRNAs as alternative therapeutic targets. Although miRNAs could be potential targets, identifying which miRNAs to target for a particular type of cancer has been difficult due to the limited knowledge on their regulatory roles in cancer. We address this challenge by integrating miRNA-target prediction, metabolic modeling and context-specific gene expression data to predict therapeutic miRNAs that could reduce the growth of cancer.We developed a novel approach to simulate a condition-specific metabolic system for human hepatocellular carcinoma (HCC) wherein overexpression of each miRNA was simulated to predict their ability to reduce cancer cell growth. Our approach achieved >80% accuracy in predicting the miRNAs that could suppress metastasis and progression of liver cancer based on various experimental evidences in the literature. This condition-specific metabolic system provides a framework to explore the mechanisms by which miRNAs modulate metabolic functions to affect cancer growth. To the best of our knowledge, this is the first computational approach implemented to predict therapeutic miRNAs for human cancer based on their functional role in cancer metabolism. Analyzing the metabolic functions altered by the miRNA-identified metabolic genes essential for cell growth and proliferation that are targeted by the miRNAs.See supplementary protocols and http://www.egr.msu.edu/changroup/Protocols%20Index.html CONTACT: krischan@egr.msu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
| S-EPMC3982155 | biostudies-literature
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) noncoding RNAs and disseminated throughout the genome, either in the intergenic regions or in the intronic sequences of protein-coding genes. MiRNAs have been proved to play important roles in regulating gene expression. Hence, understanding the transcriptional mechanism of miRNA genes is a very critical step to uncover the whole regulatory network. A number of miRNA promoter prediction models have been proposed in the past decade. This review summarized several most popular miRNA promoter prediction models which used genome sequence features, or other features, for example, histone markers, RNA Pol II binding sites, and nucleosome-free regions, achieved by high-throughput sequencing data. Some databases were described as resources for miRNA promoter information. We then performed comprehensive discussion on prediction and identification of transcription factor mediated microRNA regulatory networks.
| S-EPMC5474535 | biostudies-literature
Project description:Colorectal cancer (CRC) is one of the most malignant cancers with high morbidity and mortality. MicroRNAs (miRNAs) are small non-coding RNAs that affect biological processes by binding to mRNAs and regulating their expression, and epigenetic alterations including miRNA dysregulation are significantly involved in CRC development. Determining the effect of the miRNA-mRNA network on CRC could be helpful for developing novel therapeutic targets and prognostic biomarkers, and even improving survival. In this study, microarray assays were used to screen differentially expressed miRNAs (DE miRNAs) and mRNAs (DE mRNAs) in CRC and the adjacent normal tissues. Among the detected genes, 42 miRNAs and 142 mRNAs were significantly upregulated in CRC, while 23 miRNAs and 279 mRNAs were significantly downregulated. Through overlapping of predicted targets of DE miRNAs and anti-expressed DE mRNAs, networks of DE miRNAs and DE mRNAs in CRC were established. Additionally, the formation of a protein-protein interaction network of DE mRNAs possibly targeted by DE miRNAs, functional annotation and pathway analysis, stable subnetwork mining, and determination of hub genes provided the probable mechanism used by DE miRNAs and DE mRNAs to regulate CRC growth. Finally, validation of expression and prognostic potential of hub genes provided further support for the results above and indicated that CCL-28, GPR15, PNOC, NUSAP1, and their interacted miRNAs may be a potential signature for prognosis of CRC patients. In sum, we successfully established miRNA-mRNA regulatory networks based on microarray results targeting CRC, and these findings may elucidate the mechanisms used for CRC growth and identify miRNA-related signatures for prognosis and treatment of CRC.
| S-EPMC7644864 | biostudies-literature
Project description:BackgroundLung adenocarcinoma (LUAD) is a common lung cancer with a high mortality, for which microRNAs (miRNAs) play a vital role in its regulation. Multiple messenger RNAs (mRNAs) may be regulated by miRNAs, involved in LUAD tumorigenesis and progression. However, the miRNA-mRNA regulatory network involved in LUAD has not been fully elucidated.MethodsDifferentially expressed miRNAs and mRNA were derived from the Cancer Genome Atlas (TCGA) dataset in tissue samples and from our microarray data in plasma (GSE151963). Then, common differentially expressed (Co-DE) miRNAs were obtained through intersected analyses between the above two datasets. An overlap was applied to confirm the Co-DEmRNAs identified both in targeted mRNAs and DEmRNAs in TCGA. A miRNA-mRNA regulatory network was constructed using Cytoscape. The top five miRNA were identified as hub miRNA by degrees in the network. The functions and signaling pathways associated with the hub miRNA-targeted genes were revealed through Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The key mRNAs in the protein-protein interaction (PPI) network were identified using the STRING database and CytoHubba. Survival analyses were performed using Gene Expression Profiling Interactive Analysis (GEPIA).ResultsThe miRNA-mRNA regulatory network consists of 19 Co-DEmiRNAs and 760 Co-DEmRNAs. The five miRNAs (miR-539-5p, miR-656-3p, miR-2110, let-7b-5p, and miR-92b-3p) in the network were identified as hub miRNAs by degrees (>100). The 677 Co-DEmRNAs were targeted mRNAs from the five hub miRNAs, showing the roles in the functional analyses of the GO analysis and KEGG pathways (inclusion criteria: 836 and 48, respectively). The PPI network and Cytoscape analyses revealed that the top ten key mRNAs were NOTCH1, MMP2, IGF1, KDR, SPP1, FLT1, HGF, TEK, ANGPT1, and PDGFB. SPP1 and HGF emerged as hub genes through survival analysis. A high SPP1 expression indicated a poor survival, whereas HGF positively associated with survival outcomes in LUAD.ConclusionThis study investigated a miRNA-mRNA regulatory network associated with LUAD, exploring the hub miRNAs and potential functions of mRNA in the network. These findings contribute to identify new prognostic markers and therapeutic targets for LUAD patients in clinical settings.
| S-EPMC7930498 | biostudies-literature
Project description:BackgroundNeuropathic pain (NP) is a debilitating and refractory chronic pain with a higher prevalence especially in elderly patients. Cell senescence considered a key pathogenic factor in NP. The objective of this research is to discover genes associated with aging in peripheral blood of individuals with NP using bioinformatics techniques.MethodsTwo cohorts (GSE124272 and GSE150408) containing peripheral blood samples of NP were downloaded from the GEO database. By merging the two cohorts, differentially expressed aging-related genes (DE-ARGs) were obtained by intersection with aging-related genes. The potential biological mechanisms of DE-ARGs were further analyzed through GO and KEGG. Three machine learning methods, namely, LASSO, SVM-RFE, and Random Forest, were utilized to identify diagnostic biomarkers. A Nomogram model was developed to assess their diagnostic accuracy. The validation of biomarker expression and diagnostic effectiveness was conducted in three distinct pain cohorts. The CIBERSORT algorithm was employed to evaluate the immune cell composition in the peripheral blood of patients with NP and investigate its association with the expression of diagnostic biomarkers.ResultsThis study identified a total of 24 DE-ARGs, mainly enriched in "Chemokine signaling pathway," "Inflammatory mediator regulation of TRP channels," "HIF-1 signaling pathway" and "FOXO signaling pathway". Three machine learning algorithms identified a total of four diagnostic biomarkers (CEBPA, CEACAM1, BTG3 and IL-1R1) with good diagnostic performance and the similar expression difference trend in different types of pain cohorts. The expression levels of CEACAM1 and IL-1R1 exhibit a positive correlation with the percentage of neutrophils.ConclusionUsing machine learning techniques, our research identified four diagnostic biomarkers related to aging in peripheral blood, providing innovative approaches for the diagnosis and treatment of NP.
| S-EPMC11303200 | biostudies-literature
Project description:Pyroptosis is defined as inflammation-induced programmed cell death. However, gene expression levels related to pyroptosis and their role in neuropathic pain (NP) remain unclear. The present study aimed to develop and validate an NP-predictive signature based on the genes associated with pyroptosis. Gene expression level profiles were downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis was used to identify the pyroptotic genes most highly associated with NP. NP-related pyroptosis gene signature was constructed using multivariate logistic regression. A rat model of neuropathic pain was established through chronic constriction injury to analyse the inflammatory infiltration and myelin damage around the sciatic nerve, and examine the expression levels of macrophage markers S100 calcium-binding protein β (S100β) and ionized calcium-binding adapter molecule 1 (Iba-1). Finally, flow cytometry analysis was used to examine the lipopolysaccharide (LPS)-induced cell death ratio of RSC96 cells (Schwann cells), while the expression levels of LPS-induced pyroptosis-related genes in RSC96 cells were measured via reverse transcription-quantitative PCR. The results demonstrated that pyroptosis-related genes (gasdermin D, NLR family pyrin domain containing 3, neuronal apoptosis inhibitory protein and NLR family CARD domain containing 4) were identified to increase the risk of NP. NP-related pyroptosis signatures were constructed based on these four genes. Moreover, the high-risk group had a higher level of macrophage infiltration compared with the low-risk group, as determined by the CIBERSORT algorithm. H&E staining results showed that the myelin structure of the sciatic nerve tissue of chronic constriction injury (CCI) rats was destroyed and inflammatory cells infiltrated around neurons. The results of immunohistochemistry showed that compared with in the sham group, the expression levels of Iba-1 and sS100β in the sciatic nerve of the CCI group were increased. Furthermore, the expression levels of cell death and pyroptosis-related genes in Schwann cells induced by LPS were increased compared with in the control group. In conclusion, an NP-related pyroptosis gene signature was constructed based on four pyroptosis-related genes and it was found that the expression of pyroptosis-related genes was upregulated in the early steps of the neuroinflammatory process in RSC96 cells.
| S-EPMC9780700 | biostudies-literature