Endogenous RNA Regulatory Network Research Articles

Advanced Insights into Competitive Endogenous RNAs (ceRNAs) Regulated Pathogenic Mechanisms in Metastatic Triple-Negative Breast Cancer (mTNBC)

Triple-negative breast cancer is aggressive and challenging to treat because of a lack of targets and heterogeneity among tumors. A paramount factor in the mortality from breast cancer is metastasis, which is driven by genetic and phenotypic alterations that drive epithelial–mesenchymal transition, stemness, survival, migration and invasion. Many genetic and epigenetic mechanisms have been identified in triple-negative breast cancer that drive these metastatic phenotypes; however, this knowledge has not yet led to the development of effective drugs for metastatic triple-negative breast cancer (mTNBC). One that may not have received enough attention in the literature is post-translational regulation of broad sets of cancer-related genes through inhibitory microRNAs and the complex competitive endogenous RNA (ceRNA) regulatory networks they are influenced by. This field of study and the resulting knowledge regarding alterations in these networks is coming of age, enabling translation into clinical benefit for patients. Herein, we review metastatic triple-negative breast cancer (mTNBC), the role of ceRNA network regulation in metastasis (and therefore clinical outcomes), potential approaches for therapeutic exploitation of these alterations, knowledge gaps and future directions in the field.

The potential regulatory role of the non-coding RNAs in regulating the exogenous estrogen-induced feminization in Takifugu rubripes gonad

Estrogen plays a pivotal role in the early stage of sex differentiation in teleost. However, the underlying mechanisms of estrogen-induced feminization process are still needed for further clarification. Here, the comparative analysis of whole-transcriptome RNA sequencing was conducted between 17beta-Estradiol induced feminized XY (E-XY) gonads and control gonads (C) in Takifugu rubripes. A total of 57 miRNAs, 65 lncRNAs, and 4 circRNAs were found to be expressed at lower levels in control-XY (C-XY) than that in control-XX (C-XX), and were up-regulated in XY during E2-induced feminization process. The expression levels of 24 miRNAs, and 55 lncRNAs were higher in C-XY than that in C-XX, and were down-regulated in E2-treated XY. Furthermore, a correlation analysis was performed between miRNA-seq and mRNA-seq data. In C-XX/C-XY, 114 differential expression (DE) miRNAs were predicted to target to 904 differential expression genes (DEGs), while in C-XY/E-XY, 226 DEmiRNAs were predicted to target to 2,048 DEGs. In C-XX/C-XY, and C-XY/E-XY, KEGG pathway enrichment analysis showed that those targeted genes were mainly enriched in MAPK signaling, calcium signaling, steroid hormone biosynthesis and ovarian steroidogenesis pathway. Additionally, the competitive endogenous RNA (ceRNA) regulatory network was constructed by 24 miRNAs, 21 lncRNAs, 4 circRNAs and 5 key sex-related genes. These findings suggested that the expression of critical genes in sex differentiation were altered in E2-treated XY T. rubripes may via the lncRNA-miRNA-mRNA regulation network to facilitate the differentiation and maintenance of ovaries. Our results provide a new insight into the comprehensive understanding of the effects of estrogen signaling pathways on sex differentiation in teleost gonads.

Integrating molecular pathway with genome-wide association data for causality identification in breast cancer

ObjectiveThe study purpose was to explore the causal association between pyruvate metabolism and breast cancer (BC), as well as the molecular role of key metabolic genes, by using bioinformatics and Mendelian randomization (MR) analysis.MethodsWe retrieved and examined diverse datasets from the GEO database to ascertain differentially acting genes (DAGs) in BC via differential expression analysis. Following this, we performed functional and pathway enrichment analyses to ascertain noteworthy molecular functions and metabolic pathways in BC. Employing MR analysis, we established a causal association between pyruvate metabolism and the susceptibility to BC. Additionally, utilizing the DGIdb database, we identified potential targeted medications that act on genes implicated in the pyruvate metabolic pathway and formulated a competing endogenous RNA (ceRNA) regulatory network in BC.ResultsWe collected the datasets GSE54002, GSE70947, and GSE22820, and identified a total of 1127 DEGs between the BC and NC groups. GO and KEGG enrichment analysis showed that the molecular functions of these DEGs mainly included mitotic nuclear division, extracellular matrix, signaling receptor activator activity, etc. Metabolic pathways were mainly concentrated in PI3K−Akt signaling pathway, Cytokine−cytokine receptor binding and Pyruvate, Tyrosine, Propanoate and Phenylalanine metabolism, etc. In addition, MR analysis demonstrated a causal relationship between pyruvate metabolism and BC risk. Finally, we constructed a regulatory network between pathway genes (ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C) and targeted drugs, as well as a ceRNA (lncRNA-miRNA-mRNA) regulatory network for BC, further revealing their interactions.ConclusionsOur research revealed a causal association between pyruvate metabolism and BC risk, found that ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C takes place an important part in the development of BC in the molecular mechanisms related to pyruvate metabolism, and identified some potential targeted small molecule drugs.

Integrated Analysis of Transcriptome Profiles and lncRNA-miRNA-mRNA Competing Endogenous RNA Regulatory Network to Identify Biological Functional Effects of Genes and Pathways Associated with Johne's Disease in Dairy Cattle.

Paratuberculosis or Johne's disease (JD), a chronic granulomatous gastroenteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP), causes huge economic losses and reduces animal welfare in dairy cattle herds worldwide. At present, molecular mechanisms and biological functions involved in immune responses to MAP infection of dairy cattle are not clearly understood. Our purpose was to integrate transcriptomic profiles and competing endogenous RNA (ceRNA) network analyses to identify key messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of peripheral blood mononuclear cells (PBMCs) for MAP infection in dairy cattle. In total, 28 lncRNAs, 42 miRNAs, and 370 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In this regard, we identified 21 hub genes (CCL20, CCL5, CD40, CSF2, CXCL8, EIF2AK2, FOS, IL10, IL17A, IL1A, IL1B, IRF1, MX2, NFKB1, NFKBIA, PTGS2, SOCS3, TLR4, TNF, TNFAIP3, and VCAM1) involved in MAP infection. Furthermore, eight candidate subnets with eight lncRNAs, 29 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 510, 22, and 11 significantly enriched GO terms related to MAP infection in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways related to MAP infection that were enriched included the immune system process, defense response, response to cytokine, leukocyte migration, regulation of T cell activation, defense response to bacterium, NOD-like receptor, B cell receptor, TNF, NF-kappa B, IL-17, and T cell receptor signaling pathways. Contributions of transcriptome profiles from MAP-positive and MAP-negative sample groups plus a ceRNA regulatory network underlying phenotypic differences in the intensity of pathogenicity of JD provided novel insights into molecular mechanisms associated with immune system responses to MAP infection in dairy cattle.

Construction and Bioinformatics Analysis of ceRNA Regulatory Networks in Idiopathic Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive form of pulmonary fibrosis of unknown etiology. Despite ongoing research, there is currently no cure for this disease. Recent studies have highlighted the significance of competitive endogenous RNA (ceRNA) regulatory networks in IPF development. Therefore, this study investigated the ceRNA network associated with IPF pathogenesis. We obtained gene expression datasets (GSE32538, GSE32537, GSE47460, and GSE24206) from the Gene Expression Omnibus (GEO) database and analyzed them using bioinformatics tools to identify differentially expressed messenger RNAs (DEmRNAs), microRNAs (DEmiRNAs), and long non-coding RNAs (DElncRNA). For DEmRNAs, we conducted an enrichment analysis, constructed protein-protein interaction networks, and identified hub genes. Additionally, we predicted the target genes of differentially expressed mRNAs and their interacting long non-coding RNAs using various databases. Subsequently, we screened RNA molecules with ceRNA regulatory relations in the lncACTdb database based on the screening results. Furthermore, we performed disease and functional enrichment analyses and pathway prediction for miRNAs in the ceRNA network. We also validated the expression levels of candidate DEmRNAs through quantitative real-time reverse transcriptase polymerase chain reaction and analyzed the correlation between the expression of these candidate DEmRNAs and the percent predicted pre-bronchodilator forced vital capacity [%predicted FVC (pre-bd)]. We found that three ceRNA regulatory axes, specifically KCNQ1OT1/XIST/NEAT1-miR-20a-5p-ITGB8, XIST-miR-146b-5p/miR-31-5p- MMP16, and NEAT1-miR-31-5p-MMP16, have the potential to significantly affect IPF progression. Further examination of the underlying regulatory mechanisms within this network enhances our understanding of IPF pathogenesis and may aid in the identification of diagnostic biomarkers and therapeutic targets.

Construction of a ceRNA network and screening of potential biomarkers and molecular targets in male smokers with chronic obstructive pulmonary disease.

Circular RNAs (circRNAs) play an important role in the occurrence and development of diseases. However, the role of circRNAs in male smokers with chronic obstructive pulmonary disease (COPD) remains unclear. Stable COPD patients and healthy controls were recruited. Peripheral blood mononuclear cells (PBMCs) were extracted. After high-throughput RNA sequencing (RNA-Seq) of PBMCs, a bioinformatics method was used to analyse differentially expressed (DE) circRNAs (DEcircRNAs) and mRNAs (DEmRNAs). Total of 114 DEcircRNAs and 58 DEmRNAs were identified. Functional enrichment analysis showed that processes related to COPD include the regulation of interleukin (IL)-18, IL-5 and the NLRP3 inflammasome; differentiation of T helper type 1 (Th1), Th2, and Th17 cells, and the AMPK, Wnt, JAK-STAT, and PI3K-Akt signalling pathways. In the protein-protein interaction (PPI) network, the core genes were MYO16, MYL4, SCN4A, NRCAM, HMCN1, MYOM2, and IQSEC3. Small-molecule prediction results revealed potential drugs for the COPD treatment. Additionally, the circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory network was constructed. This study identified a set of dysregulated circRNAs and mRNAs and revealed potentially important genes, pathways, new small-molecule drugs and ceRNA regulatory networks in male smokers with COPD. These circRNAs might be prospective biomarkers or potential molecular targets of the ceRNA mechanism for COPD.

Dynamic whole-transcriptome landscape of acute bilirubin encephalopathy in newborns

Hyperbilirubinemia in newborns may progress to acute bilirubin encephalopathy (ABE), posing short- and long-term health risks. Despite extensive research identifying numerous mRNAs, lncRNAs, circRNAs, and miRNAs associated with brain injury, their roles in neonatal bilirubin-induced brain injury remain elusive. This study employed whole-transcriptome sequencing to ascertain the differentially expressed (DE) RNA profiles in a newborn ABE rat model, followed by bioinformatic analysis. A time-series competing endogenous RNA (ceRNA) regulatory network was established, and the expression trends of 9 arbitrarily chosen RNAs were verified through quantitative real-time polymerase chain reaction(qRT-PCR). In comparison with the control group, we identified 595, 888, and 1448 DE mRNAs; 22, 37, and 37 DE miRNAs; 1945, 1869, and 1997 DE lncRNAs; and 31, 28, and 36 DE circRNAs at 6 h, 12 h, and 24 h, respectively. Predominantly, these DERNAs contribute to biological functions and pathways associated with inflammation, immunity, metabolism, cell death, and neurodevelopmental regulation. Moreover, we constructed ceRNA networks of DE lncRNA/circRNA-DE miRNA-DE mRNA based on time series. The qRT-PCR expression trends for the selected 9 RNAs were generally similar to the RNA-seq outcomes. This investigation uniquely delineated the temporal expression patterns of mRNA and non-coding RNA in ABE, establishing ceRNA networks and identifying potential molecular mechanisms underlying bilirubin-induced hippocampal damage. Nonetheless, further studies are warranted to corroborate these findings in humans.

Identifying competing endogenous RNA regulatory networks and hub genes in alcoholic liver disease for early diagnosis and potential therapeutic target insights.

Alcoholic liver disease (ALD) has a complex pathogenesis. Although early-stage ALD can be reversed by ceasing alcohol consumption, early symptoms are difficult to detect, and several factors contribute to making alcohol difficult to quit. Continued alcohol abuse worsens the condition, meaning it may gradually progress into alcoholic hepatitis and cirrhosis, ultimately, resulting in irreversible consequences. Therefore, effective treatments are urgently needed for early-stage ALD. Current research mainly focuses on preventing the progression of alcoholic fatty liver to alcoholic hepatitis and cirrhosis. However, challenges remain in identifying key therapeutic targets and understanding the molecular mechanisms that underlie the treatment of alcoholic hepatitis and cirrhosis, such as the limited discovery of effective therapeutic targets and treatments. Here, we downloaded ALD microarray data from Gene Expression Omnibus and used bioinformatics to compare and identify the hub genes involved in the progression of alcoholic fatty liver to alcoholic hepatitis and cirrhosis. We also predicted target miRNAs and long non-coding RNAs (lncRNAs) to elucidate the regulatory mechanisms (the mRNA-miRNA-lncRNA axis) underlying this progression, thereby building a competitive endogenous RNA (ceRNA) mechanism for lncRNA, miRNA, and mRNA. This study provides a theoretical basis for the early treatment of alcoholic hepatitis and cirrhosis and identifies potential therapeutic targets.

Spatial transcriptomics reveals gene interactions and signaling pathway dynamics in rat embryos with anorectal malformation

Anorectal malformation (ARM) is a prevalent early pregnancy digestive tract anomaly. The intricate anatomy of the embryonic cloaca region makes it challenging for traditional high-throughput sequencing methods to capture location-specific information. Spatial transcriptomics was used to sequence libraries of frozen sections from embryonic rats at gestational days (GD) 14 to 16, covering both normal and ARM cases. Bioinformatics analyses and predictions were performed using methods such as WGCNA, GSEA, and PROGENy. Immunofluorescence staining was used to verify gene expression levels. Gene expression data was obtained with anatomical annotations of clusters, focusing on the cloaca region's location-specific traits. WGCNA revealed gene modules linked to normal and ARM cloacal anatomy development, with cooperation between modules on GD14 and GD15. Differential gene expression profiles and functional enrichment were presented. Notably, protein levels of Pcsk9, Hmgb2, and Sod1 were found to be downregulated in the GD15 ARM hindgut. The PROGENy algorithm predicted the activity and interplay of common signaling pathways in embryonic sections, highlighting their synergistic and complementary effects. A competing endogenous RNA (ceRNA) regulatory network was constructed from whole transcriptome data. Spatial transcriptomics provided location-specific cloaca region gene expression. Diverse bioinformatics analyses deepened our understanding of ARM's molecular interactions, guiding future research and providing insights into gene regulation in ARM development.

Whole-Transcriptome Analysis Sheds Light on the Biological Contexts of Intramuscular Fat Deposition in Ningxiang Pigs.

The quality of pork is significantly impacted by intramuscular fat (IMF). However, the regulatory mechanism of IMF depositions remains unclear. We performed whole-transcriptome sequencing of the longissimus dorsi muscle (IMF) from the high (5.1 ± 0.08) and low (2.9 ± 0.51) IMF groups (%) to elucidate potential mechanisms. In summary, 285 differentially expressed genes (DEGs), 14 differentially expressed miRNAs (DEMIs), 83 differentially expressed lncRNAs (DELs), and 79 differentially expressed circRNAs (DECs) were identified. DEGs were widely associated with IMF deposition and liposome differentiation. Furthermore, competing endogenous RNA (ceRNA) regulatory networks were constructed through co-differential expression analyses, which included circRNA-miRNA-mRNA (containing 6 DEMIs, 6 DEGs, 47 DECs) and lncRNA-miRNA-mRNA (containing 6 DEMIs, 6 DEGs, 36 DELs) regulatory networks. The circRNAs sus-TRPM7_0005, sus-MTUS1_0004, the lncRNAs SMSTRG.4269.1, and MSTRG.7983.2 regulate the expression of six lipid metabolism-related target genes, including PLCB1, BAD, and GADD45G, through the binding sites of 2-4068, miR-7134-3p, and miR-190a. For instance, MSTRG.4269.1 regulates its targets PLCB1 and BAD via miRNA 2_4068. Meanwhile, sus-TRPM7_0005 controls its target LRP5 through ssc-miR-7134-3P. These findings indicate molecular regulatory networks that could potentially be applied for the marker-assisted selection of IMF to enhance pork quality.

Bioinformatics analysis and validation of mesenchymal stem cells related gene MT1G in osteosarcoma.

Osteosarcoma (OS) is a primary malignant bone tumor arising from mesenchymal cells. The standard clinical treatment for OS involves extensive tumor resection combined with neoadjuvant chemotherapy or radiotherapy. OS's invasiveness, lung metastasis, and drug resistance contribute to a low cure rate and poor prognosis with this treatment. Metallothionein 1G (MT1G), observed in various cancers, may serve as a potential therapeutic target for OS. OS samples in GSE33382 and TARGET datasets were selected as the test cohorts. As the external validation cohort, 13 OS tissues and 13 adjacent cancerous tissues from The Second Affiliated Hospital of Nanchang University were collected. Patients with OS were divided into high and low MT1G mRNA-expression groups; differentially expressed genes (DEGs) were identified as MT1G-related genes. The biological function of MT1G was annotated using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and gene set enrichment analysis (GSEA). Gene expression correlation analysis and competing endogenous RNA (ceRNA) regulatory network construction were used to determine potential biological regulatory relationships of DEGs. Survival analysis assessed the prognostic value of MT1G. MT1G expression increased in OS samples and presented higher in metastatic OS compared with non-metastatic OS. Functional analyses indicated that MT1G was mainly associated with spliceosome. A ceRNA network with DEGs was constructed. MT1G is an effective biomarker predicting survival and correlated with increased recurrence rates and poorer survival. This research identified MT1G as a potential biomarker for OS prognosis, highlighting its potential as a therapy target.

Integrative analysis of plasma and substantia nigra in Parkinson's disease: unraveling biomarkers and insights from the lncRNA-miRNA-mRNA ceRNA network.

Parkinson's disease (PD) is a rapidly growing neurological disorder characterized by diverse movement symptoms. However, the underlying causes have not been clearly identified, and accurate diagnosis is challenging. This study aimed to identify potential biomarkers suitable for PD diagnosis and present an integrative perspective on the disease. We screened the GSE7621, GSE8397-GPL96, GSE8397-GPL97, GSE20163, and GSE20164 datasets in the NCBI GEO database to identify differentially expressed (DE) mRNAs in the substantia nigra (SN). We also screened the GSE160299 dataset from the NCBI GEO database to identify DE lncRNAs and miRNAs in plasma. We then constructed 2 lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory networks based on the ceRNA hypothesis. To understand the biological function, we performed Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses for each ceRNA network. The receiver operating characteristic analyses (ROC) was used to assess ceRNA results. We identified 7 upregulated and 29 downregulated mRNAs as common DE mRNAs in the 5 SN datasets. In the blood dataset, we identified 31 DE miRNAs (9 upregulated and 22 downregulated) and 332 DE lncRNAs (69 upregulated and 263 downregulated). Based on the determined interactions, 5 genes (P2RX7, HSPA1, SLCO4A1, RAD52, and SIRT4) appeared to be upregulated as a result of 10 lncRNAs sponging 4 miRNAs (miR-411, miR-1193, miR-301b, and miR-514a-2/3). Competing with 9 genes (ANK1, CBLN1, RGS4, SLC6A3, SYNGR3, VSNL1, DDC, KCNJ6, and SV2C) for miR-671, a total of 26 lncRNAs seemed to function as ceRNAs, influencing genes to be downregulated. In this study, we successfully constructed 2 novel ceRNA regulatory networks in patients with PD, including 36 lncRNAs, 5 miRNAs, and 14 mRNAs. Our results suggest that these plasma lncRNAs are involved in the pathogenesis of PD by sponging miRNAs and regulating gene expression in the SN of the brain. We propose that the upregulated and downregulated lncRNA-mediated ceRNA networks represent mechanisms of neuroinflammation and dopamine neurotransmission, respectively. Our ceRNA network, which was associated with PD, suggests the potential use of DE miRNAs and lncRNAs as body fluid diagnostic biomarkers. These findings provide an integrated view of the mechanisms underlying gene regulation and interactions in PD.

Integrated Analysis of CD1A Immune Infiltration and Competing Endogenous RNA Networks in COAD.

The CD1A gene, a key component of the human immune system and part of the CD1 family, plays a crucial role in presenting lipid antigens to T cells. Abnormal CD1A expression is associated with various immune-related diseases and tumors. However, the biological function of CD1A in COAD is unclear. Multiple databases were systematically employed to conduct an analysis of CD1A expression in pan-cancer and COAD, along with its clinical-pathological features. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of CD1A were performed using the 'clusterProfiler' package. The Protein-protein interaction (PPI) analysis of CD1A was used the STRING database. Additionally, TIMER and ssGSEA tools were used to explore the relationship between CD1A expression in COAD and immune cell infiltration. The study also investigated the association between CD1A expression and N6-methyladenosine (m6A) modification genes in the TCGA COAD cohort and constructed a CD1A-centric competing endogenous RNA (ceRNA) regulatory network. CD1A displays varying expression levels in various tumors, including COAD, and is closely linked to clinical-pathological characteristics. GO analysis suggests that CD1A plays a role in important processes like antigen processing and presentation, leukocyte-mediated immunity, and lymphocyte-mediated immunity. KEGG analysis identifies CD1A's involvement in key pathways such as the Chemokine signaling pathway and Cytokine-cytokine receptor interaction. PPI analysis highlights CD1A's interactions with CD207, CD1C, CD1E, FOXP3, and ITGB2. ssGSEA analysis indicates a significant relationship between CD1A expression and the infiltration of various immune cells in COAD. Significant associations were found between CD1A and m6A modification genes in COAD. Furthermore, a CD1A-centered ceRNA regulatory network has been constructed. CD1A emerges as a potential biomarker for the diagnosis and treatment of COAD, showing a strong association with tumor immune infiltration, m6A modification, and the ceRNA network.

Exploration of lncRNA/circRNA-miRNA-mRNA network in patients with chronic atrophic gastritis in Tibetan plateau areas based on DNBSEQ-G99 RNA sequencing

A higher incidence of chronic atrophic gastritis (CAG) is generally considered as a precancerous lesion in gastric cancer (GC). The aim of this study was to identify potential molecules involved in the pathogenesis of CAG in the Tibetan plateau, hoping to help the diagnosis and management of the disease. Atrophic and non-atrophic gastric mucosal tissue samples were collected from seven patients with chronic gastritis (CG). Differentially expressed lncRNAs, circRNAs, miRNAs, and mRNAs between CAG and chronic non-atrophic gastritis (CNAG) groups were identified based on DNBSEQ-G99 RNA sequencing. Subsequently, competitive endogenous RNA (ceRNA) regulatory networks (lncRNA/circRNA-miRNA-mRNA networks) were constructed. Two datasets (GSE153224 and GSE163416), involving data from non-Tibetan plateau areas, were used to further screen out Tibetan plateau key mRNAs, followed by the common genes of Tibetan plateau key and ferroptosis-related mRNAs were also identified. Functional enrichment analyses were performed to investigate the biological functions of Tibetan plateau mRNAs in the CAG. A total of seven lncRNA-miRNA-mRNA relationship pairs and 424 circRNA-miRNA-mRNA relationship pairs were identified in this study. The relationship pairs of hsa_circ_0082984-hsa-miR-204-5p-CACNG8, lncRNA DRAIC/has_circ_0008561-hsa-miR-34a-5p-AR/GXYLT2, lncRNA GAS1RR/RGMB-AS1/hsa_circ_0008561-hsa-miR-3614-5p-TMEM216/SUSD5, and LINC00941/hsa_circ_0082984-hsa-miR-873-3p-TMC5 can be involved in the pathogenesis of CAG. Additionally, eight common genes of Tibetan plateau key and ferroptosis-related differentially expressed mRNAs (DEmRNAs) (CBS, SLC2A4, STAT3, ALOX15B, ATF3, IDO1, NOX4, and SOCS1) were identified in CAG. The common genes of Tibetan plateau key and ferroptosis-related DEmRNAs can play a role in the JAK-STAT signaling pathway. This study identified important molecular biomarkers that may be involved in regulating the pathological mechanisms of CAG in the Tibetan plateau, which provides potential research directions for future research.

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.

Analysis of the expression level and predictive value of CLEC16A|miR-654-5p|RARA regulatory axis in the peripheral blood of patients with ischemic stroke based on biosignature analysis.

Ischemic stroke (IS) is a cerebrovascular disease that can be disabling and fatal, and there are limitations in the clinical treatment and prognosis of IS. It has been reported that changes in the expression profile of circRNAs have been found during injury in ischemic stroke, and circRNAs play an important role in the IS cascade response. However, the specific mechanisms involved in the pathogenesis of IS are not yet fully understood, and thus in-depth studies are needed. In this study, one circRNA dataset (GSE161913), one miRNA dataset (GSE60319) and one mRNA dataset (GSE180470) were retrieved from the Gene Expression Omnibus (GEO) database and included, and the datasets were differentially expressed analyzed by GEO2R and easyGEO to get the DEcircRNA, DEmiRNA and DEmRNA, and DEmRNA was enriched using ImageGP, binding sites were predicted in the ENCORI database, respectively, and the competitive endogenous RNA (ceRNA) regulatory network was visualized by the cytoscape software, and then selected by MCC scoring in the cytoHubba plugin Hub genes. In addition, this study conducted a case-control study in which blood samples were collected from stroke patients and healthy medical examiners to validate the core network of ceRNAs constructed by biosignature analysis by real-time fluorescence quantitative qRT-PCR experiments. A total of 233 DEcircRNAs, 132 DEmiRNAs and 72 DEmRNAs were screened by bioinformatics analysis. circRNA-mediated ceRNA regulatory network was constructed, including 148 circRNAs, 43 miRNAs and 44 mRNAs. Finally, CLEC16A|miR-654-5p|RARA competitive endogenous regulatory axis was selected for validation by qRT-PCR, and the validation results were consistent with the bioinformatics analysis. In conclusion, the present study establishes a new axis of regulation associated with IS, providing new insights into the pathogenesis of IS.

Construction and analysis of competitive endogenous RNA networks and prognostic models associated with ovarian cancer based on the exoRBase database.

To construct a competitive endogenous RNA (ceRNA) regulatory network in blood exosomes of patients with ovarian cancer (OC) using bioinformatics and explore its pathogenesis. The exoRbase2.0 database was used to download blood exosome gene sequencing data from patients OC and normal controls and the expression profiles of exosomal mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) were detected independently using R language for differential expression analysis. TargetScan and miRanda databases were combined for the prediction and differential expression of mRNA-binding microRNAs (miRNA). The miRcode and starBase databases were used to predict miRNAs that bind to differentially expressed lncRNAs and circRNAs repectively. The relevant mRNA, circRNA, lncRNA and their corresponding miRNA prediction data were imported into Cytoscape software for visualization of the ceRNA network. The R language and KEGG Orthology-based Annotation System (KOBAS) were used to execute and illustrate the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Hub genes were identified using The CytoHubba plugin. Thirty-one differentially expressed mRNAs, 17 differentially expressed lncRNAs, and 24 differentially expressed circRNAs were screened. Cytoscape software was used to construct the ceRNA network with nine mRNA nodes, two lncRNA nodes, eight circRNA nodes, and 51 miRNA nodes. Both GO and KEGG were focused on the Spliceosome pathway, indicating that spliceosomes are closely linked with the development of OC, while heterogenous nuclear ribonucleoprotein K and RNA binding motif protein X-linked genes were the top 10 score Hub genes screened by Cytoscape software, including two lncRNAs, four mRNAs, and four circRNAs. In patients with OC, the expression of eukaryotic translation initiation factor 4 gamma 2 (EIF4G2), SERPINE 1 mRNA binding protein 1 (SERBP1), ribosomal protein L15 (RPL15) and human leukocyte antigen complex P5 (HCP5) was significantly higher whereas that of testis expressed transcript, Y-linked 15 and DEAD-box helicase 3 Y-linked genes was lower compared to normal controls Immunocorrelation scores revealed that SERBP1 was significantly and negatively correlated with endothelial cells and CD4+ T cells and positively correlated with natural killer (NK) cells and macrophages, respectively; RPL15 was significantly positively correlated with macrophages and endothelial cells and negatively correlated with CD8+ T cells and uncharacterized cells, respectively. EIF4G2 was significantly and negatively correlated with endothelial cells and CD4+ T cells, and positively correlated with uncharacterized cells, respectively. Based on the survival data and the significant correlation characteristics derived from the multifactorial Cox analysis (P < 0.05), the survival prediction curves demonstrated that the prognostic factors associated with 3-year survival in patients with OC were The prognostic factors associated with survival were Macrophage, RPL15. This study successfully constructs a ceRNA regulatory network in blood exosomes of OV patients, which provides the specific targets for diagnosis and treatment of OC.

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas.

Gliomas are the most prevalent primary malignant tumors affecting the brain, with high recurrence and mortality rates. Accurate diagnoses and effective treatment challenges persist, emphasizing the need for identifying new biomarkers to guide clinical decisions. Long noncoding RNAs (lncRNAs) hold potential as diagnostic and therapeutic biomarkers in cancer. However, only a limited subset of lncRNAs in gliomas have been explored. Therefore, this study aims to identify lncRNA signatures applicable to patients with gliomas across all grades and explore their clinical significance and potential biological mechanisms. Data used in this study were obtained from TCGA, CGGA, and GEO datasets to identify key lncRNA signatures in gliomas through differential and survival analyses and machine learning algorithms. We examined their associations with the clinical characteristics, gene mutations, diagnosis, and prognosis of gliomas. Functional enrichment analysis was employed to elucidate the potential biological mechanisms associated with these significant lncRNA signatures. We explored competing endogenous RNA (ceRNA) regulatory networks. We found that NDUFA6-DT emerged as a significant lncRNA signature in gliomas, with reduced NDUFA6-DT expression associated with a worse prognosis in gliomas. Nomogram analysis incorporating NDUFA6-DT expression levels exhibited excellent prognostic and predictive capabilities. Functional annotation suggested that NDUFA6-DT might influence immunological responses and synaptic transmission, potentially modifying glioma initiation and progression. The associated ceRNA network revealed the possible presence of the NDUFA6-DT-miR-455-3p-YWHAH/YWHAG axis in low-grade glioma (LGG) and glioblastoma multiforme (GBM), regulating the PI3K-AKT signaling pathway and influencing glioma cell survival and apoptosis. We believe that NDUFA6-DT is a novel lncRNA linked to glioma diagnosis and prognosis, potentially becoming a pivotal biomarker for glioma.

High expression of NXPH4 correlates with poor prognosis, metabolic reprogramming, and immune infiltration in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a prevalent gastrointestinal malignant disease with high mortality rate, and identification of novel prognostic biomarkers and therapeutic targets is urgently needed. Although neurexophilin 4 (NXPH4) has been investigated in several tumors, its role in COAD remains unclear. The aim of this study was to explore the prognostic value and potential functions of NXPH4 in COAD. The expression of NXPH4 in COAD were analyzed using The Cancer Genome Atlas (TCGA) and datasets from the Gene Expression Omnibus (GEO) database. The prognostic value of NXPH4 was determined using Kaplan-Meier analysis and Cox regression analysis. To investigate the possible mechanism underlying the role of NXPH4 in COAD, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were employed. The correlation between NXPH4 expression and immune cell infiltration levels was examined thorough single-sample gene set enrichment analysis (ssGSEA). Furthermore, the competing endogenous RNA (ceRNA) regulatory network that may be involved in NXPH4 in COAD was predicted and constructed through a variety of databases. NXPH4 expression was significantly higher in COAD tissue compared with normal colon tissues. Meanwhile, high expression of NXPH4 was associated with poor prognosis in COAD patients. GO-KEGG and GSEA analyses indicated that NXPH4 was associated with glycolysis and hypoxia pathway, and may promote COAD progression and metastasis by modulating metabolic reprogramming. ssGSEA analysis demonstrated that NXPH4 expression also associated with immune infiltration. Furthermore, we identified various microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) as upstream regulators of NXPH4 in COAD. The present study revealed that high expression of NXPH4 is associated with tumor progression, metabolic reprogramming, and immune infiltration. These findings suggest that NXPH4 could serve as a reliable prognostic biomarker and a promising therapeutic target in COAD.

Machine learning to establish three sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with gastric cancer

BackgroundGastric cancer (GC) is one of the most common malignant tumors worldwide. Nevertheless, GC still lacks effective diagnosed and monitoring method and treating targets. This study used multi omics data to explore novel biomarkers and immune therapy targets around sphingolipids metabolism genes (SMGs).MethodLASSO regression analysis was performed to filter prognostic and differently expression SMGs among TCGA and GTEx data. Risk score model and Kaplan-Meier were built to validate the prognostic SMG signature and prognostic nomogram was further constructed. The biological functions of SMG signature were annotated via multi omics. The heterogeneity landscape of immune microenvironment in GC was explored. qRT-PCR was performed to validate the expression level of SMG signature. Competing endogenous RNA regulatory network was established to explore the molecular regulatory mechanisms.Result3-SMGs prognostic signature (GLA, LAMC1, TRAF2) and related nomogram were constructed combing several clinical characterizes. The expression difference and diagnostic value were validated by PCR data. Multi omics data reveals 3-SMG signature affects cell cycle and death via several signaling pathways to regulate GC progression. Overexpression of 3-SMG signature influenced various immune cell infiltration in GC microenvironment. RBP-SMGs-miRNA-mRNAs/lncRNAs regulatory network was built to annotate regulatory system.ConclusionUpregulated 3-SMGs signature are excellent predictive diagnosed and prognostic biomarkers, providing a new perspective for future GC immunotherapy.