ceRNA Network Research Articles

Exosome-mediated secretion of miR-127-3p regulated by RAB27A accelerates metastasis in renal cell carcinoma

BackgroundThe exosome-mediated extracellular secretion of miRNAs occurs in many cancers, and RAB27A is a potent regulator of exosome secretion. For metastatic renal cell carcinoma (RCC), this study examines the mechanisms of cancer metastasis via the RAB27A-regulated secretion of specific miRNAs.MethodsRAB27A knockdown (KD) and overexpressing (OE) RCC cells were used to examine cell migration and adhesion. The particle counts and sizes of exosomes in RAB27A OE cells were analyzed using Exoview, and those of intraluminal vesicles (ILV) and multivesicular bodies (MVB) were measured using an electron microscope. Analysis of RNA sequences, protein–protein interaction networks, and the competing endogenous RNA (ceRNA) network were used to identify representative downregulated miRNAs that are likely to undergo cargo-sorting into exosomes and subsequent secretion. A molecular beacon of miR-137-3p, one of the most representatively downregulated genes with a fold change of 339, was produced, and its secretion was analyzed using Exoview. RAB27A OE and control cells were incubated in an exosome-containing media to determine the uptake of tumor suppressor miRNAs that affect cancer cell metastasis.ResultsMigration and cell adhesion were higher in RAB27A OE cells than in RAB27A KD cells. Electron microscopy revealed that the numbers of multivesicular bodies and intraluminal vesicles per cell were higher in RAB27A OE cells than in control cells, suggesting their secretion. The finding revealed that miR-127-3p was sorted into exosomes and disposed of extracellularly. Protein–protein interaction analysis revealed MYCN to be the most significant hub for RAB27A-OE RCC cells. ceRNA network analysis revealed that MAPK4 interacted strongly with miR-127-3p.ConclusionThe disposal of miR-127-3p through exosome secretion in RAB27A overexpressing cells may not inhibit the MAPK pathway to gain metastatic potential by activating MYCN. The exosomes containing miRNAs are valuable therapeutic targets for cancer treatment.

Study on the Mechanism of Competing Endogenous Network of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' in the Treatment of NSCLC based on Bioinformatics, Molecular Dynamics and Experimental Verification.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Traditional Chinese medicine, known for its multi-target and multi-pathway characteristics, offers a potential treatment approach for NSCLC. This study aimed to explore the mechanism of the competitive endogenous network of 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' in treating NSCLC through bioinformatics analysis and in vitro experiments. Various databases and ceRNA networks were utilized to collect and screen components and target genes, molecular docking and molecular dynamics simulations to determine the binding ability of ligand-receptor complexes. In vitro experiments were conducted to validate the effects of active ingredients of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' on non-small cell lung cancer cell line A549. The key target proteins CCL2, EDN1, MMP9, PPARG, and SPP1 were docked well with their corresponding TCM ligands. Among the ligand-receptor complexes, MMP9-Luteolin and MMP9-Quercetin demonstrated the weaking binding force, while the SPP1-Quercetin complex, associated with NSCLC prognosis, exhibited stable structure formation through hydrogen bond interaction during MD simulation. In vitro experiments confirmed the inhibitory effect of Quercetin on SPP1 expression, as well as the proliferation and migration of A549 cells. The findings suggest that 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' may potentially treat lung cancer by suppressing the expression of SPP1. This study provides valuable insights and novel research directions for understanding the mechanism of traditional Chinese medicine in combating lung cancer.

Identification of ceRNA networks in type H and L vascular endothelial cells through integrated bioinformatics methods.

Type H blood vessels are a subtype of bone-specific microvessels (CD31hiEmcnhi) that play an important regulatory role in the coupling of angiogenesis and osteogenesis. Despite reports on the distinct roles of type H and L vessels under physiological and pathological bone conditions, their genetic differences remain to be elucidated. This study aims to construct a competitive endogenous RNA (ceRNA) network of key gene for differencial expression (DE) in type H and L vascular endothelial cells (ECs) through integrated bioinformatic methods. We downloaded relevant raw data from the ArrayExpress and the Gene Expression Omnibus (GEO) database and used the Limma R-Bioconductor package to screen for DE lncRNAs, DE miRNAs, and DE mRNAs between type H and L vascular ECs. A total ceRNA network was constructed based on their interactions, followed by refinement using protein-protein interaction (PPI) networks to select upregulated and downregulated key genes. Enrichment analysis was performed on these key genes. Random validation was conducted using flow cytometry and real-time RT-PCR. A total of 1 761 DE mRNAs, 187 DE lncRNAs, and 159 DE miRNAs were identified, and a comprehensive ceRNA network was constructed based on their interactions. Six upregulated (Itga5, Kdr, Tjp1, Pecam1, Cdh5, and Ptk2) and 2 downregulated (Csf1r and Il10) key genes were selected via PPI network to construct a subnetwork of ceRNAs related to these key genes. Upregulated key genes were mainly enriched in negative regulation of angiogenesis and vascular apoptosis. Results from flow cytometry and real-time RT-PCR were consistent with bioinformatics analysis. This study proposes a ceRNA network associated with upregulated and downregulated type H and L vascular ECs based on selected key genes, providing new insights into the regulatory mechanisms of type H and L vascular ECs in bone metabolism.

Integrating Bulk RNA and Single-Cell Sequencing Data Unveils Efferocytosis Patterns and ceRNA Network in Ischemic Stroke.

Excessive inflammatory response following ischemic stroke (IS) injury is a key factor affecting the functional recovery of patients. The efferocytic clearance of apoptotic cells within ischemic brain tissue is a critical mechanism for mitigating inflammation, presenting a promising avenue for the treatment of ischemic stroke. However, the cellular and molecular mechanisms underlying efferocytosis in the brain after IS and its impact on brain injury and recovery are poorly understood. This study explored the roles of inflammation and efferocytosis in IS with bioinformatics. Three Gene Expression Omnibus Series (GSE) (GSE137482-3m, GSE137482-18m, and GSE30655) were obtained from NCBI (National Center for Biotechnology Information) and GEO (Gene Expression Omnibus). Differentially expressed genes (DEGs) were processed for GSEA (Gene Set Enrichment Analysis), GO (Gene Ontology Functional Enrichment Analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Efferocytosis-related genes were identified from the existing literature, following which the relationship between Differentially Expressed Genes (DEGs) and efferocytosis-related genes was examined. The single-cell dataset GSE174574 was employed to investigate the distinct expression profiles of efferocytosis-related genes. The identified hub genes were verified using the dataset of human brain and peripheral blood sample datasets GSE56267 and GSE122709. The dataset GSE215212 was used to predict competing endogenous RNA (ceRNA) network, and GSE231431 was applied to verify the expression of differential miRNAs. At last, the middle cerebral artery (MCAO) model was established to validate the efferocytosis process and the expression of hub genes. DEGs in two datasets were significantly enriched in pathways involved in inflammatory response and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related genes (Abca1, C1qc, Ptx3, Irf5, and Pros1) and key transcription factors (Stat5). The scRNA-seq analysis showed that these hub genes were mainly expressed in microglia and macrophages which are the main cells with efferocytosis function in the brain. We then identified miR-125b-5p as a therapeutic target of IS based on the ceRNA network. Finally, we validated the phagocytosis and clearance of dead cells by efferocytosis and the expression of hub gene Abca1 in MCAO mice models.

WGCNA and machine learning analysis identifi ed SAMD9 and IFIT3 as primary Sjögren's Syndrome key genes

BackgroundCurrent treatments for primary Sjögren's Syndrome (pSS) are with limited effect, partially due to the heterogeneity and uncleared mechanism. MethodsWe got GSE40568 (Japan) and GSE40611 (USA), and analyzed them with WGCNA to find key Differentially expressed genes (DEGs) between pSS and healthy salivary glands (SG). Key pSS genes (KPGs) were further selected through 3 machine-learning methods. The expression of KPGs was validated via two other GEO datasets (GSE127952 and GSE154926). Infiltrated immune cells, ceRNA network, and potential compounds were explored. ResultsOur study identified 376 DEGs from the pSS patients, with 186 genes located in the “plum2" module, showing the strongest correlation with clinical characteristics. SAMD9 and IFIT3 emerged as KPGs with excellent diagnostic potential. SAMD9 demonstrated close association with immune cell infiltration. We constructed a lncRNA-miRNA-mRNA network comprising 2 KPGs, 12 miRNAs, 124 lncRNAs, and potential therapeutic targets. ConclusionIn the investigation of pSS public datasets, our study revealed two potential critical mediators in the pathological process of pSS salivary glands, namely SAMD9 and IFIT3. Furthermore, we put forth a hypothesis regarding the ceRNA network and made predictions regarding potential therapeutic drugs targeting these two genes.

Prognostic model and ceRNA network of m7G- and radiosensitivity-related genes in hepatocellular carcinoma

BackgroundRadiotherapy is an effective treatment for hepatocellular carcinoma (HCC). Recent studies indicated that N7-methylguanosine (m7G)-associated genes are involved in radioresistance and prognosis of HCC. However, the prognostic value and underlying mechanism of m7G-and radiosensitivity-associated genes are still lacking. MethodsThe related statistics of HCC were downloaded from The Cancer Genome Atlas (TCGA). M7G- and radiosensitivity-associated genes were screened and evaluated using correlation, differential, univariate, and multivariate analysis. The least absolute shrinkage and selection operator (LASSO) algorithm was used to establish a prognostic model. Prognostic efficacy, functional analysis, immune cell infiltration,and drug sensitivity of the prognostic model were assessed. The ceRNA network was predicted and evaluated through the StarBase database, correlation analysis, expression analysis, and survival analysis. ResultMETTL1, EIF3D, NCBP2, and WDR4 participated in prognosis model construction. The favorable prediction efficiency has been verified in both the training and verification sets. Different risk groups have differences in prognosis outcome, function analysis, immune cell infiltration, and drug sensitivity. NCBP2 can be used to predict the prognosis and has excellent potential in immunotherapy. A prognostic ceRNA network based on the NCBP2/miR-122-5p axis was established. ConclusionThe prognosis model of m7G- and radiosensitivity-related genes is constructed, and widely used in clinical prognosis, immunotherapy, and drug therapy. NCBP2, as a hub gene, may be a prognostic biomarker for HCC and is related to immunotherapy. Establishing the NCBP2/miR-122-5p axis helps study the mechanism of ceRNA and provides new ideas for finding a new candidate biomarker.

Follicular fluid-derived exosomal LncRNA LIPE-AS1 modulates steroid metabolism and survival of granulosa cells leading to oocyte maturation arrest in polycystic ovary syndrome.

Women who are of reproductive age can suffer from polycystic ovary syndrome (PCOS), an endocrine disorder. Anovulatory infertility is mostly caused by aberrant follicular development, which is seen in PCOS patients. Due to the dysfunction of reproductive and endocrine function in PCOS patients, assisted reproduction treatment is one of the main means to obtain clinical pregnancy for PCOS patients. Long non-coding RNA (lncRNA) as a group of functional RNA molecules have been found to participate in the regulation of oocyte function, hormone metabolism, and proliferation and apoptosis of granulosa cells. In this study, we investigated the role of lncRNAs in follicular fluid-derived exosomes and the underlying mechanism of lncRNA LIPE-AS1. We used RNA sequencing to analyze the lncRNA profiles of follicular fluid-derived exosomes in PCOS patients and controls. RT-qPCR was performed to detect the expression levels of these lncRNAs in control (n = 30) and PCOS (n = 30) FF exosome samples. Furthermore, we validated the performance of lncRNA LIPE-AS1 in oocyte maturation by in vitro maturation (IVM) experiments in mouse and steroid metabolism in granulosa cells. We found 501 lncRNAs were exclusively expressed in the control group and another 273 lncRNAs were found to be specifically expressed in the PCOS group. LncRNA LIPE-AS1, highly expressed in PCOS exosomes, was related to a poor oocyte maturation and embryo development in PCOS patients. Reduced number of MII oocytes were observed in the LIPE-AS1 group by in vitro maturation (IVM) experiments in mouse. LIPE-AS1 was also shown to modulate steroid metabolism and granulosa cell proliferation and apoptosis by LIPE-AS1/miR-4306/LHCGR axis. These findings suggested that the increased expression of LIPE-AS1, facilitated by follicular fluid exosomes, had a significant impact on both oocyte maturation and embryo development. We demonstrated the ceRNA mechanism involving LIPE-AS1, miR-4306, and LHCGR as a regulator of hormone production and metabolism. These findings indicate that LIPE-AS1 is essential in PCOS oocyte maturation and revealed a ceRNA network of LIPE-AS1 and provided new information on abnormal steroid metabolism and oocyte development in PCOS.

Identification of different myofiber types in pigs muscles and construction of regulatory networks

BackgroundSkeletal muscle is composed of muscle fibers with different physiological characteristics, which plays an important role in regulating skeletal muscle metabolism, movement and body homeostasis. The type of skeletal muscle fiber directly affects meat quality. However, the transcriptome and gene interactions between different types of muscle fibers are not well understood.ResultsIn this paper, we selected 180-days-old Large White pigs and found that longissimus dorsi (LD) muscle was dominated by fast-fermenting myofibrils and soleus (SOL) muscle was dominated by slow-oxidizing myofibrils by frozen sections and related mRNA and protein assays. Here, we selected LD muscle and SOL muscle for transcriptomic sequencing, and identified 312 differentially expressed mRNA (DEmRs), 30 differentially expressed miRNA (DEmiRs), 183 differentially expressed lncRNA (DElRs), and 3417 differentially expressed circRNA (DEcRs). The ceRNA network included ssc-miR-378, ssc-miR-378b-3p, ssc-miR-24-3p, XR_308817, XR_308823, SMIM8, MAVS and FOS as multiple core nodes that play important roles in muscle development. Moreover, we found that different members of the miR-10 family expressed differently in oxidized and glycolytic muscle fibers, among which miR-10a-5p was highly expressed in glycolytic muscle fibers (LD) and could target MYBPH gene mRNA. Therefore, we speculate that miR-10a-5p may be involved in the transformation of muscle fiber types by targeting the MYHBP gene. In addition, PPI analysis of differentially expressed mRNA genes showed that ACTC1, ACTG2 and ACTN2 gene had the highest node degree, suggesting that this gene may play a key role in the regulatory network of muscle fiber type determination.ConclusionsWe can conclude that these genes play a key role in regulating muscle fiber type transformation. Our study provides transcriptomic profiles and ceRNA interaction networks for different muscle fiber types in pigs, providing reference for the transformation of pig muscle fiber types and the improvement of meat quality.

Key mRNAs and lncRNAs of pituitary that affect the reproduction of FecB + + small tail han sheep

BackgroundThe pituitary directly regulates the reproductive process through follicle-stimulating hormone (FSH) and luteinizing hormone (LH). Transcriptomic research on the pituitaries of ewes with different FecB (fecundity Booroola) genotypes has shown that some key genes and lncRNAs play an important role in pituitary function and sheep fecundity. Our previous study found that ewes with FecB + + genotypes (without FecB mutation) still had individuals with more than one offspring per birth. It is hoped to analyze this phenomenon from the perspective of the pituitary transcriptome.ResultsThe 12 Small Tail Han Sheep were equally divided into polytocous sheep in the follicular phase (PF), polytocous sheep in the luteal phase (PL), monotocous sheep in the follicular phase (MF), and monotocous sheep in the luteal phase (ML). Pituitary tissues were collected after estrus synchronous treatment for transcriptomic analysis. A total of 384 differentially expressed genes (DEGs) (182 in PF vs. MF and 202 in PL vs. ML) and 844 differentially expressed lncRNAs (DELs) (427 in PF vs. MF and 417 in PL vs. ML) were obtained from the polytocous-monotocous comparison groups in the two phases. Functional enrichment analysis showed that the DEGs in the two phases were enriched in signaling pathways known to play an important role in sheep fecundity, such as calcium ion binding and cAMP signaling pathways. A total of 1322 target relationship pairs (551 pairs in PF vs. MF and 771 pairs in PL vs. ML) were obtained for the target genes prediction of DELs, of which 29 DEL-DEG target relationship pairs (nine pairs in PF vs. MF and twenty pairs in PL vs. ML). In addition, the competing endogenous RNA (ceRNA) networks were constructed to explore the regulatory relationships of DEGs, and some important regulatory relationship pairs were obtained.ConclusionAccording to the analysis results, we hypothesized that the pituitary first receives steroid hormone signals from the ovary and uterus and that VAV3 (Vav Guanine Nucleotide Exchange Factor 3), GABRG1 (Gamma-Aminobutyric Acid A Receptor, Gamma 1), and FNDC1 (Fibronectin Type III Domain Containing 1) played an important role in this process. Subsequently, the reproductive process was regulated by gonadotropins, and IGFBP1 (Insulin-like Growth Factor Binding Protein 1) was directly involved in this process, ultimately affecting litter size. In addition, TGIF1 (Transforming Growth Factor-Beta-Induced Factor 1) and TMEFF2 (Transmembrane Protein With EGF Like And Two Follistatin Like Domains 2) compensated for the effect of the FecB mutation and function by acting on TGF-β/SMAD signaling pathway, an important pathway for sheep reproduction. These results provided a reference for understanding the mechanism of multiple births in Small Tail Han Sheep without FecB mutation.

Multiple transcriptome analyses reveal mouse testis developmental dynamics

The testes are the organs of gamete production and testosterone synthesis. Up to date, no model system is available for mammalian testicular development, and only few studies have characterized the mouse testis transcriptome from no more than three postnatal ages. To describe the transcriptome landscape of the developing mouse testis and identify the potential molecular mechanisms underlying testis maturation, we examined multiple RNA-seq data of mouse testes from 3-week-old (puberty) to 11-week-old (adult). Sperm cells appeared as expected in 5-week-old mouse testis, suggesting the proper sample collection. The principal components analysis revealed the genes from 3w to 4w clustered away from other timepoints, indicating they may be the important nodes for testicular development. The pairwise comparisons at two adjacent timepoints identified 7,612 differentially expressed genes (DEGs), resulting in 58 unique mRNA expression patterns. Enrichment analysis identified functions in tissue morphogenesis (3-4w), regulation of peptidase activity (4-5w), spermatogenesis (7-8w), and antigen processing (10-11w), suggesting distinct functions in different developmental periods. 50 hub genes and 10 gene cluster modules were identified in the testis maturation process by protein-protein interaction (PPI) network analysis, and the miRNA-lncRNA-mRNA, miRNA-circRNA-mRNA and miRNA-circRNA-lncRNA-mRNA competing endogenous RNA (ceRNA) networks were constructed. The results suggest that testis maturation is a complex developmental process modulated by various molecules, and that some potential RNA-RNA interactions may be involved in specific developmental stages. In summary, this study provides an update on the molecular basis of testis development, which may help to understand the molecular mechanisms of mouse testis development and provide guidance for mouse reproduction.

Genetic markers associated with ferroptosis in Alzheimer's disease.

Ferroptosis is implicated in the pathogenesis of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and vascular dementia, implying that it may have a regulatory effect on the progression of these diseases. However, the specific role of ferroptosis-related genes (FRGs) in Alzheimer's disease (AD) is not yet fully understood. The aim of the study was to detect ferroptosis related genes with regulatory functions in the disease and explore potential mechanisms in AD. Hub FRGs were obtained through multiple algorithms based on the GSE5281 dataset. The screening process was implemented by R packages including limma, WGCNA, glm and SVM-RFE. Gene Ontology classification and pathway enrichment analysis were performed based on FRGs. Biological processes involved with hub FRGs were investigated through GSVA and GSEA methods. Immune infiltration analysis was performed by the R package CIBERSORT. Receiver operating characteristic curve (ROC) was utilized to validate the accuracy of hub FRGs. The CeRNA network attempted to find non-coding RNA transcripts which may play a role in disease progression. DDIT4, MUC1, KLHL24, CD44, and RB1 were identified as hub FRGs. As later revealed by enrichment analysis, the hub FRGs had important effects on AD through involvement in diverse AD pathogenesis-related pathways such as autophagy and glutathione metabolism. The immune microenvironment in AD shows increased numbers of resting NK cells, macrophages, and mast cells, with decreased levels of CD8 T cells when compared to healthy samples. Regulatory T cells were positively correlated with MUC1, KLHL24, and DDIT4 expression, while RB1 showed negative correlations with eosinophils and CD8 T cells, suggesting potential roles in modulating the immune environment in AD. Our research has identified five hub FRGs in AD. We concluded that ferroptosis may be involved in the disease.

Comprehensive analysis of lncRNA-miRNA-mRNA ceRNA network in ischemic stroke

ObjectiveCompetitive endogenous RNA (ceRNA) networks have uncovered a novel mode of RNA interaction, and are implicated in various biological processes and the pathogenesis of IS. This study aimed to explore the potential mechanisms underlying the ceRNA network in IS. MethodsFour public datasets containing lncRNA and mRNA (GSE22255 and GSE16561) and miRNA (GSE55937 and GSE43618) expression profiles from the GEO database were systematically analyzed to explore the role of RNAs in ischemic stroke (IS). Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) between IS and normal control samples were identified. LncRNA-miRNA and miRNA-mRNA interactions were predicted, and the competing endogenous RNA (ceRNA) regulatory network was constructed using the Cytoscape software. The correlation between the RNAs in the ceRNA network and the clinical features of the samples was evaluated. Finally, principal component analysis was performed on the RNAs that constitute the ceRNA regulatory network, and their differential expression and principal component relationships among different types of samples were observed. ResultsA total of 224 DEmRNAs, 7 DEmiRNAs, and four DElncRNAs related to IS in four datasets were identified. Then, through target gene prediction, a lncRNA–miRNA–mRNA ceRNA network that contained 3 DElncRNAs, 2 DEmiRNAs, and 24 DEmRNAs was constructed. Correlations of the clinical characteristics showed that PART1 and SERPINH1 were related to clinical diseases, WNK1 was related to lifestyle, and seven RNAs were related to age. PCA results indicate that three principal components of PC1, PC2, and PC3 can clearly distinguish between control and IS samples. ConclusionOverall, we constructed a ceRNA network in IS, which could offer insights into the molecular mechanism and potential prognostic biomarkers for further research.

Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients.

Stroke is a disease with high morbidity, disability, and mortality. Immune factors play a crucial role in the occurrence of ischemic stroke (IS), but their exact mechanism is not clear. This study aims to identify possible immunological mechanisms by recognizing immune-related biomarkers and evaluating the infiltration pattern of immune cells. We downloaded datasets of IS patients from GEO, applied R language to discover differentially expressed genes, and elucidated their biological functions using GO, KEGG analysis, and GSEA analysis. The hub genes were then obtained using two machine learning algorithms (least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE)) and the immune cell infiltration pattern was revealed by CIBERSORT. Gene-drug target networks and mRNA-miRNA-lncRNA regulatory networks were constructed using Cytoscape. Finally, we used RT-qPCR to validate the hub genes and applied logistic regression methods to build diagnostic models validated with ROC curves. We screened 188 differentially expressed genes whose functional analysis was enriched to multiple immune-related pathways. Six hub genes (ANTXR2, BAZ2B, C5AR1, PDK4, PPIH, and STK3) were identified using LASSO and SVM-RFE. ANTXR2, BAZ2B, C5AR1, PDK4, and STK3 were positively correlated with neutrophils and gamma delta T cells, and negatively correlated with T follicular helper cells and CD8, while PPIH showed the exact opposite trend. Immune infiltration indicated increased activity of monocytes, macrophages M0, neutrophils, and mast cells, and decreased infiltration of T follicular helper cells and CD8 in the IS group. The ceRNA network consisted of 306 miRNA-mRNA interacting pairs and 285 miRNA-lncRNA interacting pairs. RT-qPCR results indicated that the expression levels of BAZ2B, C5AR1, PDK4, and STK3 were significantly increased in patients with IS. Finally, we developed a diagnostic model based on these four genes. The AUC value of the model was verified to be 0.999 in the training set and 0.940 in the validation set. Our research explored the immune-related gene expression modules and provided a specific basis for further study of immunomodulatory therapy of IS.

Decoding dynamic miRNA:ceRNA interactions unveils therapeutic insights and targets across predominant cancer landscapes.

Competing endogenous RNAs play key roles in cellular molecular mechanisms through cross-talk in post-transcriptional interactions. Studies on ceRNA cross-talk, which is particularly dependent on the abundance of free transcripts, generally involve large- and small-scale studies involving the integration of transcriptomic data from tissues and correlation analyses. This abundance-dependent nature of ceRNA interactions suggests that tissue- and condition-specific ceRNA dynamics may fluctuate. However, there are no comprehensive studies investigating the ceRNA interactions in normal tissue, ceRNAs that are lost and/or appear in cancerous tissues or their interactions. In this study, we comprehensively analyzed the tumor-specific ceRNA fluctuations observed in the three highest-incidence cancers, LUAD, PRAD, and BRCA, compared to healthy lung, prostate, and breast tissues, respectively. Our observations pertaining to tumor-specific competing endogenous RNA (ceRNA) interactions revealed that, in the cases of lung adenocarcinoma (LUAD), prostate adenocarcinoma (PRAD), and breast invasive carcinoma (BRCA), 3,204, 1,233, and 406 ceRNAs, respectively, engage in post-transcriptional intercommunication within tumor tissues, in contrast to their absence in corresponding healthy samples. We also found that 90 ceRNAs are shared by the three cancer types and that these ceRNAs participate in ceRNA interactions in tumor tissues compared to those in normal tissues. Among the 90 ceRNAs that directly interact with miRNAs, we uncovered a core network of 165 miRNAs and 63 ceRNAs that should be considered in RNA-targeted and RNA-mediated approaches in future studies and could be used in these three aggressive cancer types. More specifically, in this core interaction network, ceRNAs such as GALNT7, KLF9, and DAB2 and miRNAs like miR-106a/b-5p, miR-20a-5p, and miR-519d-3p may have potential as common targets in the three critical cancers. In contrast to conventional methods that construct ceRNA networks using differentially expressed genes compared to normal tissues, our proposed approach identifies ceRNA players by considering their context within the ceRNA:miRNA interactions. Our results have the potential to reveal distinct and common ceRNA interactions in cancer types and to pinpoint critical RNAs, thereby paving the way for RNA-based strategies in the battle against cancer.

Identification and analysis of MSC-Exo-derived LncRNAs related to the regulation of EMT in hypospadias

ObjectiveThis study aims to screen the differentially expressed long non-coding RNAs (DELncRNAs) related to the regulation of epithelial-mesenchymal transition (EMT) in hypospadias in mesenchymal stem cell-derived exosomes (MSC-Exons) and explore the potential mechanism of these lncRNAs for the EMT in hypospadias.MethodsIn this study, the microarray data related to MSC-Exos and hypospadias were downloaded from Gene Expression Omnibus (GEO). Besides, the lncRNAs highly expressed in MSC-Exos and the differentially expressed mRNAs and lncRNAs in children with hypospadias were screened, respectively. In addition, the lncRNAs enriched in MSC-Exos and differentially expressed lncRNAs in hypospadias were intersected to obtain the final DElncRNAs. Moreover, the co-expression interaction pairs of differentially expressed lncRNAs and mRNAs were analyzed to construct a Competing Endogenous RNA (ceRNA) network. Finally, the candidate lncRNAs in exosomes were subjected to in vitro cell function verification.ResultsIn this study, a total of 4 lncRNAs were obtained from the microarray data analysis. Further, a ceRNA regulatory network of MSC-Exo-derived lncRNAs related to the regulation of EMT in hypospadias was constructed, including 4 lncRNAs, 2 mRNAs, and 6 miRNAs. The cell function verification results indicated that the exosomes secreted by MSCs may transport HLA complex group 18 (HCG18) into target cells, which promoted the proliferation, migration, and EMT of these cells.ConclusionMSC-Exo-derived lncRNA HCG18 can enter target cells, and it may be involved in the regulation of EMT in hypospadias through the ceRNA network.

Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning.

Cuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusion injury (HIRI). The datasets related to HIRI were sourced from the Gene Expression Omnibus database. The comparative analysis of differential gene expression involving CRGs was performed between HIRI and normal liver samples. Correlation analysis, function enrichment analyses, and protein-protein interactions were employed to understand the interactions and roles of these genes. Machine learning techniques were used to identify hub genes. Additionally, differences in immune cell infiltration between HIRI patients and controls were analyzed. Quantitative real-time PCR and western blotting were used to verify the expression of the hub genes. Seventy-five HIRI and 80 control samples from three databases were included in the bioinformatics analysis. Three hub CRGs (NLRP3, ATP7B and NFE2L2) were identified using three machine learning models. Diagnostic accuracy was assessed using a receiver operating characteristic (ROC) curve for the hub genes, which yielded an area under the ROC curve (AUC) of 0.832. Remarkably, in the validation datasets GSE15480 and GSE228782, the three hub genes had AUC reached 0.904. Additional analyses, including nomograms, decision curves, and calibration curves, supported their predictive power for diagnosis. Enrichment analyses indicated the involvement of these genes in multiple pathways associated with HIRI progression. Comparative assessments using CIBERSORT and gene set enrichment analysis suggested elevated expression of these hub genes in activated dendritic cells, neutrophils, activated CD4 memory T cells, and activated mast cells in HIRI samples versus controls. A ceRNA network underscored a complex regulatory interplay among genes. The genes mRNA and protein levels were also verified in HIRI-affected mouse liver tissues. Our findings have provided a comprehensive understanding of the association between cuproptosis and HIRI, establishing a promising diagnostic pattern and identifying latent therapeutic targets for HIRI treatment. Additionally, our study offers novel insights to delve deeper into the underlying mechanisms of HIRI.

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma.

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal. To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC. The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators. CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained. This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

Identification of potential biomarkers of gout through weighted gene correlation network analysis.

Although hyperuricemia is not always associated with acute gouty arthritis, uric acid is a significant risk factor for gout. Therefore, we investigated the specific mechanism of uric acid activity. Using the gout-associated transcriptome dataset GSE160170, we conducted differential expression analysis to identify differentially expressed genes (DEGs). Moreover, we discovered highly linked gene modules using weighted gene coexpression network analysis (WGCNA) and evaluated their intersection. Subsequently, we screened for relevant biomarkers using the cytoHubba and Mcode algorithms in the STRING database, investigated their connection to immune cells and constructed a competitive endogenous RNA (ceRNA) network to identify upstream miRNAs and lncRNAs. We also collected PBMCs from acute gouty arthritis patients and healthy individuals and constructed a THP-1 cell gout inflammatory model, RT-qPCR and western blotting (WB) were used to detect the expression of C-X-C motif ligand 8 (CXCL8), C-X-C motif ligand 2 (CXCL2), and C-X-C motif ligand 1 (CXCL1). Finally, we predicted relevant drug targets through hub genes, hoping to find better treatments. According to differential expression analysis, there were 76 upregulated and 28 downregulated mRNAs in GSE160170. Additionally, WGCNA showed that the turquoise module was most strongly correlated with primary gout; 86 hub genes were eventually obtained upon intersection. IL1β, IL6, CXCL8, CXCL1, and CXCL2 are the principal hub genes of the protein-protein interaction (PPI) network. Using RT-qPCR and WB, we found that there were significant differences in the expression levels of CXCL8, CXCL1, and CXCL2 between the gouty group and the healthy group, and we also predicted 10 chemicals related to these proteins. In this study, we screened and validated essential genes using a variety of bioinformatics tools to generate novel ideas for the diagnosis and treatment of gout.

Construction of ceRNA network mediated by circRNAs screening from microarray and identification of novel biomarkers for myasthenia gravis

BackgroundRecent studies have revealed that circRNA can serve as ceRNA to participate in multiple autoimmune diseases. Our study aims to explore the key circRNA as ceRNA and biomarker for MG. Methods: We used circRNA microarray to explore differentially expressed circRNAs (DECs) from MG and compare with control. Then, we predicted the target miRNA associated with DECs and screened miRNAs by the algorithm of random walk with restart (RWR). Next, we constructed the circRNA-miRNA-mRNA ceRNA regulated network (CMMC) to identify the hub objects. Following, we detected the expression of hub-circRNAs by RT-PCR. We verify has_circ_0004183 (circFRMD4) sponging miR-145-5p regulate cells proliferation using luciferase assay and CCK-8. Results: We found that the expression level of circFRMD4 and has_circ_0035381 (circPIGB) were upregulated and has_circ_0089153(circ NUP214) had the lowest expression level in MG. Finally, we proved circFRMD4 sponging miR-145-5p regulate Jurkat cells proliferation. CircFRMD4 take part in the genesis and development of MG via circFRMD4/miR145-5p axis. Conclusions: We found that circFRMD4, circPIGB and circNUP214 can be considered as valuable potential novel biomarkers for AchR + MG. CircFRMD4 participate in the development of AchR + MG via targeting binding with miR-145-5p.

Study on analgesic effect of Shentong Zhuyu Decoction in neuropathic pain rats by network pharmacology and RNA-Seq

Ethnopharmacological relevanceShentong Zhuyu Decoction (STZYD) is a traditional prescription for promoting the flow of Qi and Blood which is often used in the treatment of low back and leg pain clinicall with unclear mechanism. Neuropathic pain (NP) is caused by disease or injury affecting the somatosensory system. LncRNAs may play a key role in NP by regulating the expression of pain-related genes through binding mRNAs or miRNAs sponge mechanisms. Aim of the studyTo investigate the effect and potential mechanism of STZYD on neuropathic pain. MethodsChronic constriction injury (CCI) rats, a commonly used animal model, were used in this study. The target of STZYD in NP was analyzed by network pharmacology, and the analgesic effect of STZYD in different doses (H-STZYD, M-STZYD, L-STZYD) on CCI rats was evaluated by Mechanical withdrawal thresholds (MWT) and thermal withdrawal latency (TWL). Meanwhile, RNA-seq assay was used to detect the changed mRNAs and lncRNAs in CCI rats after STZYD intervention. GO analysis, KEGG pathway analysis, and IPA analysis were used to find key target genes and pathways, verified by qPCR and Western Blot. The regulatory effect of lncRNAs on target genes was predicted by co-expression analysis and ceRNA network construction. ResultsWe found that STZYD can improve hyperalgesia in CCI rats, and H-STZYD has the best analgesic effect. The results of network pharmacological analysis showed that STZYD could play an analgesic role in CCI rats through the MAPK/ERK/c-FOS pathway. By mRNA-seq and lncRNA-seq, we found that STZYD could regulate the expression of Cnr1, Cacng5, Gucy1a3, Kitlg, Npy2r, and Grm8, and inhibited the phosphorylation level of ERK in the spinal cord of CCI rats. A total of 27 lncRNAs were associated with the target genes and 30 lncRNAs, 83 miRNAs and 5 mRNAs participated in the ceRNA network. ConclusionSTZYD has the effect of improving hyperalgesia in CCI rats through the MAPK/ERK/c-FOS pathway, which is related to the regulation of lncRNAs to Cnr1 and other key targets.