RNA Network Research Articles

Construction of circRNA-mediated ceRNA network and immunoassay for investigating pathogenesis of COPD.

The chronic respiratory condition known as chronic obstructive pulmonary disease (COPD) was one of the main causes of death and disability worldwide. This study aimed to explore and elucidate new targets and molecular mechanisms of COPD by constructing competitive endogenous RNA (ceRNA) networks. GSE38974 and GSE106986 were used to select DEGs in COPD samples and normal samples. Cytoscape software was used to construct and present protein-protein interaction (PPI) network, mRNA-miRNA co-expression network and ceRNA network. The CIBERSORT algorithm and the Lasso model were used to screen the immune infiltrating cells and hub genes associated with COPD, and the correlation between them was analyzed. COPD cell models were constructed in vitro and the expression level of ceRNA network factors mediated by hub gene was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). In this study, 852 differentially expressed genes were screened in the GSE38974 dataset, including 439 upregulated genes and 413 downregulated genes. Gene clustering analysis of PPI network results was performed using the Minimum Common Tumor Data Element (MCODE) in Cytoscape, and seven hub genes were screened using five algorithms in cytoHubba. CCL20 was verified as an important hub gene based on mRNA-miRNA co-expression network, GSE106986 database validation and the analysis of ROC curve results. Finally, we successfully constructed the circDTL-hsa-miR-330-3p-CCL20 network by Cytoscape. Immune infiltration analysis suggested that CCL20 can co-regulate immune cell migration and infiltration through chemokines CCL7 and CXCL3. In vitro experiments, the expression of circDTL and CCL20 was increased, while the expression of hsa-miR-330-3p was decreased in the COPD cell model. By constructing the circDTL-hsa-miR-330-3p-CCL20 network, this study contributes to a better understanding of the molecular mechanism of COPD development, which also provides important clues for the development of new therapeutic strategies and drug targets.

Comprehensive analysis of an mRNA co-expression network and a ceRNA network reveals potential prognostic biomarkers in oral squamous cell carcinoma

BackgroundOral squamous cell carcinoma (OSCC) is a prevalent and aggressive oral cancer with a poor prognosis. Its polygenic risk is likely influenced by complex transcriptional disorders involving networks of co-expressed and functionally related genes, though such investigations are limited in OSCC.MethodsWe analyzed the GSE37991 dataset, comprising 40 OSCC and 40 normal oral tissue samples from the Gene Expression Omnibus. Tumor-specific modules were identified using weighted correlation network analysis (WGCNA), leading to the selection of hub mRNAs and lncRNAs. These lncRNAs were used to construct lncRNA–mRNA and competing endogenous RNA networks. We further examined the expression profiles and survival data of these genes from the Cancer Genome Atlas. Prognostic markers were identified and validated through 5-year survival analysis and Cox proportional hazards modeling. RT-qPCR was used to validate the expression levels in clinical OSCC tissues.ResultsWe identified 1847 differentially expressed genes in OSCC tissues. WGCNA revealed four OSCC-specific modules, screening 120 hub mRNAs and five hub lncRNAs. Two prognostic markers (AQP5, IL-26) from hub mRNAs and three (FRMD5, INHBB, GUCY1A3) from the lncRNA–mRNA network were associated with survival. Validation showed lower expression of AQP5 and GUCY1A3, and higher expression of FRMD5 and INHBB in OSCC compared to normal tissues.ConclusionThis study enhances our understanding of transcriptional dysregulation in OSCC and may highlights AQP5, IL-26, FRMD5, INHBB, and GUCY1A3 as promising prognostic biomarkers.

Long Non-coding RNAs Influence Aging Process of Sciatic Nerves in SD Rats.

To investigate the long non-coding RNAs (lncRNAs) changes in the sciatic nerve (SN) in Sprague Dawley (SD) rats during aging. Eighteen healthy SD rats were selected at the age of 1 month (1M) and 24 months (24M) and SNs were collected. High-throughput transcriptome sequencing and bioinformatics analysis were performed. Protein-protein interaction (PPI) networks and competing endogenous RNA (ceRNA) networks were established according to differentially expressed genes (DEGs). As the length of lncRNAs increased, its proportion to the total number of lncRNAs decreased. A total of 4079 DElncRNAs were identified in Con vs. 24M. GO analysis was primarily clustered in nerve and lipid metabolism, extracellular matrix, and vascularization-related fields. There were 17 nodes in the PPI network of the target genes of up-regulating genes including Itgb2, Lox, Col11a1, Wnt5a, Kras, etc. Using quantitative RT-PCR, microarray sequencing accuracy was validated. There were 169 nodes constructing the PPI network of down-regulated target genes, mainly including Col1a1, Hmgcs1, Hmgcr. CeRNA interaction networks were constructed. Lipid metabolism, angiogenesis, and ECM fields might play an important role in the senescence process in SNs. Col3a1, Serpinh1, Hmgcr, and Fdps could be candidates for nerve aging research.

The construction and experimental verification of a 6-LncRNA model based on Lactic acid metabolism in the tumor microenvironment of Wilms tumor

BackgroundLactic acid (LA) can promote the malignant progression of tumors through the crosstalk with the tumor microenvironment (TME). However, the function of long non-coding RNAs (lncRNAs) related to LA metabolism in Wilms tumor (WT) remains unclear. MethodsGene expression data and clinical data of WT patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Through the ESTIMATE algorithm and Pearson correlation analysis, lncRNAs related to tumor immunity and LA metabolism were screened. Subsequently, Cox regression analysis and Lasso Cox regression analysis were used to construct a model. Furthermore, candidate genes were identified and a competitive endogenous RNA (ceRNA) network was conducted to explore the specific mechanism of characteristic genes. Finally, based on the strong clinical relevance of UNC5B-AS1, its expression and function were experimentally verified. ResultsThe immune score and stromal score were found to be closely related to the prognosis of WT. Eventually, a prognostic model (TME-LA-LM) consisting of 6 lncRNAs was successfully identified. The model demonstrated favorable predictive ability and accuracy, with significant variation in immune infiltration and drug susceptibility observed between risk groups. Additionally, the study revealed the involvement of 2 candidate genes and 5 microRNAs (miRNAs) in the tumor’s development. Notably, UNC5B-AS1 was highly expressed and found to promote the proliferation and migration of tumor cells. ConclusionThis study, for the first time, elucidated the prognostic signatures of WT using lncRNAs related to TME and LA metabolism. The fundings of this research offer valuable insights for future studies on immunotherapy, personalized chemotherapy and mechanism research.

Identification of the molecular link: STAT3 is a shared key gene linking postmenopausal osteoporosis and sarcopenia.

This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms. We analyzed microarray data from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA), machine learning, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify common genetic factors between POMP and sarcopenia. Further validation was done via differential gene expression in a new cohort. Single-cell analysis identified high expression cell subsets, with mononuclear macrophages in osteoporosis and muscle stem cells in sarcopenia, among others. A competitive endogenous RNA network suggested regulatory elements for these genes. Signal transducer and activator of transcription 3 (STAT3) was notably expressed in both conditions. Single-cell analysis pinpointed specific cells with high STAT3 expression, and microRNA (miRNA)-125a-5p emerged as a potential regulator. Experiments confirmed the crucial role of STAT3 in osteoclast differentiation and muscle proliferation. STAT3 has emerged as a key gene in both POMP and sarcopenia. This insight positions STAT3 as a potential common therapeutic target, possibly improving management strategies for these age-related diseases.

Unveiling circRNA-mediated ceRNA networks in ischemic stroke by integrative analysis of multi-source gene expression profiling

BackgroundCircular RNAs (circRNAs) are emerging as potential therapeutic targets for ischemic stroke (IS) due to their regulatory roles in inflammation and apoptosis. This study aimed to develop a comprehensive and robust IS-specific competing endogenous RNA (ceRNA) network to facilitate the identification of novel diagnostic and therapeutic targets. MethodsWe integrated expression data from 15 IS studies using the Rank-In algorithm to minimize batch effects. Differentially expressed circRNAs, miRNAs, and mRNAs were identified by comparing IS and control samples. Functional enrichment analysis of differentially expressed circRNA host genes revealed significantly enriched pathways and Gene Ontology (GO) terms relevant to IS pathogenesis. We further predicted miRNA-circRNA and mRNA-miRNA interactions, enabling the construction of a comprehensive ceRNA network to identify circRNA-related genes with diagnostic potential for IS. ResultsIntegrated analysis revealed 199 differentially expressed circRNAs, 103 miRNAs, and 1736 mRNAs in IS patients. Functional enrichment analysis implicated these molecules in relevant pathways like the neurotrophin signaling pathway and p53 signaling pathway. The constructed circRNA-miRNA-mRNA regulatory network provided insights into potential mechanisms underlying IS. Three circRNA-related genes (RGS2, CDK5R1, and NSF) displayed promising diagnostic potential for IS when combined. ConclusionsWe successfully constructed a robust and informative IS-specific ceRNA network by integrating data from diverse sources. This network identified differentially expressed RNAs and revealed enriched pathways potentially involved in IS pathogenesis. Notably, our analysis identified CDK5R1, RGS2, and NSF as potential diagnostic biomarkers for IS. This study sheds light on a circRNA-mediated regulatory network with potential diagnostic and therapeutic implications for ischemic stroke.

Exploring the Biomarkers and Potential Mechanisms of Botulinum Toxin Type A in the Treatment of Microglial Inflammatory Activation through P2X7 Receptors based on Transcriptome Sequencing.

This study aims to explore the potential mechanism by which Botulinum toxin type A (BoNT/ A) inhibits microglial inflammatory activation through P2X7 receptors (P2X7R). BoNT/A is a promising analgesic drug, and previous studies have established that it alleviates Neuropathic Pain (NP) by inhibiting microglial inflammatory activation. This study examined the biomarkers and potential mechanisms by which BoNT/A relieves neuropathic pain by mediating microglial P2X7R and analyzing transcriptome sequencing data from mouse BV-2 microglial cells. The P2X7R agonist Bz-ATP was used to induce microglial inflammatory activation, whilst RNAseq technology was used to explore the biomarkers and potential mechanisms through which BoNT/A suppresses microglial inflammation. RNA sequencing was performed on three BV-2 cell samples treated with a P2X7R specific activator (Bz-ATP) and three BV-2 cell samples pre-treated with BoNT/A. Only data that successfully passed quality control measures were included in subsequent analysis. Initially, Differentially Expressed Genes (DEGs) were identified from BoNT/A and control samples, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Biomarkers were then identified by constructing a Protein- Protein Interaction (PPI) network and utilizing the CytoHubba plug-in in Cytoscape software. Lastly, enrichment analysis and regulatory network analysis were performed to elucidate the potential mechanism of BoNT/A in the treatment of NP. 93 DEGs related to the "cell component size regulation" GO term and enriched in the "axon guidance" KEGG pathway were identified. Subsequently, 6 biomarkers were identified, namely PTPRF, CHDH, CKM, Ky, Sema3b, and Sema3f, which were enriched in pathways related to biosynthesis and metabolism, disease progression, signal transduction, and organelle function, including the "ribosome" and "Wnt signaling pathway." Finally, a competing endogenous RNA (ceRNAs) network was constructed from 6 mRNAs, 66 miRNAs, and 31 lncRNAs, forming a complex relationship network. Six genes (PTPRF, Sema3b, Sema3f, CHDH, CKM, and Ky) were identified as biomarkers of microglial inflammatory activation following BoNT/A treatment. This finding may provide a valuable reference for the relief and treatment of neuropathic pain.

SexAnnoDB, a knowledgebase of sex-specific regulations from multi-omics data of human cancers

BackgroundSexual differences across molecular levels profoundly impact cancer biology and outcomes. Patient gender significantly influences drug responses, with divergent reactions between men and women to the same drugs. Despite databases on sex differences in human tissues, understanding regulations of sex disparities in cancer is limited. These resources lack detailed mechanistic studies on sex-biased molecules.MethodsIn this study, we conducted a comprehensive examination of molecular distinctions and regulatory networks across 27 cancer types, delving into sex-biased effects. Our analyses encompassed sex-biased competitive endogenous RNA networks, regulatory networks involving sex-biased RNA binding protein-exon skipping events, sex-biased transcription factor-gene regulatory networks, as well as sex-biased expression quantitative trait loci, sex-biased expression quantitative trait methylation, sex-biased splicing quantitative trait loci, and the identification of sex-biased cancer therapeutic drug target genes. All findings from these analyses are accessible on SexAnnoDB (https://ccsm.uth.edu/SexAnnoDB/).ResultsFrom these analyses, we defined 126 cancer therapeutic target sex-associated genes. Among them, 9 genes showed sex-biased at both the mRNA and protein levels. Specifically, S100A9 was the target of five drugs, of which calcium has been approved by the FDA for the treatment of colon and rectal cancers. Transcription factor (TF)-gene regulatory network analysis suggested that four TFs in the SARC male group targeted S100A9 and upregulated the expression of S100A9 in these patients. Promoter region methylation status was only associated with S100A9 expression in KIRP female patients. Hypermethylation inhibited S100A9 expression and was responsible for the downregulation of S100A9 in these female patients.ConclusionsComprehensive network and association analyses indicated that the sex differences at the transcriptome level were partially the result of corresponding sex-biased epigenetic and genetic molecules. Overall, SexAnnoDB offers a discipline-specific search platform that could potentially assist basic experimental researchers or physicians in developing personalized treatment plans.

Core competing endogenous RNA network based on mRNA and non-coding RNA expression profiles in chicken fatty liver.

Fatty liver disease is a common metabolic disease in chickens. This disease can lead to a decrease in egg production and increase the risk of death in chickens. Long non-coding RNAs (lncRNAs) are involved in fatty liver formation by directly targeting genes or regulating gene expression by competitively binding microRNAs. However, a large proportion of competing endogenous RNA (ceRNA) networks in fatty liver diseases are still unclear. The total of 300 Jingxing-Huang chickens were used for fatty liver model construction. Then, differentially expressed (DE) genes (DEGs) identified through whole-transcriptome sequencing from four chickens with fatty liver and four chickens without fatty liver were chosen from the F1 generation. A total of 953 DEGs were identified between the fatty liver group and the control group, including 26 DE micro (mi)RNAs and 56 DE lncRNAs. Differential expression heatmaps and volcano plots were obtained after clustering expression analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that these DEGs were involved in many biological processes and signaling pathways related to fatty acid metabolism and lipid synthesis. Furthermore, cytoscape was used to construct a ceRNA network of the DE miRNAs, DE mRNAs, and DE lncRNAs. Eleven DE lncRNAs, seven DE miRNAs, and 13 DE mRNAs were found to be associated with the pathogenesis of fatty liver disease. An lncRNA-miRNA-mRNA ceRNA network was constructed to elucidate the mechanisms of fatty liver diseases, and the ENSGALT00000079786-miR-140/miR-143/miR-1a/miR-22/miR-375 network was identified. These results provide a valuable resource for further elucidating the posttranscriptional regulatory mechanisms of chicken liver and adipose fat development or deposition.

Identification and Validation of Aging- and Endoplasmic Reticulum Stress-Related Genes in Periodontitis Using a Competing Endogenous RNA Network.

Periodontitis is a multifactorial chronic inflammatory disease that destroy periodontium. Apart from microbial infection and host immune responses, emerging evidence shows aging and endoplasmic reticulum stress (ER stress) play a key role in periodontitis pathogenesis. The aim of this study is to identify aging-related genes (ARGs) and endoplasmic reticulum stress-related genes (ERGs) in periodontitis. Data were obtained from the Gene Expression Omnibus (GEO), Human Ageing Genomic Resources (HAGR) and GeneCards databases to identify differentially expressed mRNAs/miRNAs/lncRNAs (DEmRNAs/DEmiRNAs/DElncRNAs), ARGs and ERGs, respectively. We used the MultiMiR database for the reverse prediction of miRNAs and predicted miRNA-lncRNA interactions using the STARBase database. Afterwards, we constructed a mRNA-miRNA-lncRNA ceRNA network. A total of 10 hub genes, namely LCK, LYN, CXCL8, IL6, HCK, IL1B, BTK, CXCL12, GNAI1 and FCER1G, and 5 DEmRNAs-ARGs-ERGs were then discovered. Further, weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore co-expression modules and immune infiltration respectively. Finally, we used transmission electron microscope (TEM), inverted fluorescence microscopy, quantitative real-time polymerase chain reaction (qRT-PCR) and Western Blot to verify the bioinformatic results in periodontal ligament stem cells (PDLSCs) infected with Porphyromonas gingivalis (P. gingivalis). The experimental results broadly confirmed the accuracy of bioinformatic analysis. The present study established an aging- and ER stress-related ceRNA network in periodontitis, contributing to a deeper understanding of the pathogenesis of periodontitis.

Analysis of the miR482 Gene Family in Plants.

MicroRNA482 (miR482) is a conserved microRNA family in plants, playing critical regulatory roles in different biological activities. Though the members of the miR482 gene family have been identified in plants, a systematic study has not been reported yet. In the present research, 140 mature sequences generated by 106 precursors were used for molecular characterization, phylogenetic analysis, and target gene prediction, and the competing endogenous RNA (ceRNA) network mediated by miR482 was summarized. The length of mature sequences ranged from 17 nt to 25 nt, with 22 nt being the most abundant, and the start and end of the mature sequences had a preference for uracil (U). By sequence multiplex comparison, it was found that the mature sequences of 5p were clustered into one group, and others were clustered into the other group. Phylogenetic analysis revealed that the 140 mature sequences were categorized into six groups. Meanwhile, all the precursor sequences formed a stable hairpin structure, and the 106 precursors were divided into five groups. However, the expression of miR482 varied significantly between different species and tissues. In total, 149 target genes were predicted and their functions focused on single-organism process, cellular process, and cell and cell part. The ceRNA network of miR482 in tomato, cotton, and peanut was summarized based on related publications. In conclusion, this research will provide a foundation for further understanding of the miR482 gene family.

LncRNA PCIF1 promotes aerobic glycolysis in A549/DDP cells by competitively binding miR-326 to regulate PKM expression

ObjectiveUtilizing transcriptome analysis to investigate the mechanisms and therapeutic approaches for cisplatin resistance in non-small cell lung cancer (NSCLC). MethodsFirstly, the biological characters of A549 cells and A549/DDP cells were detected by RNA sequencing, CCK-8 and hippocampal energy analyzer. Then, the differential Genes were functionally enriched by GO and KEGG and the competitive endogenous RNA network map was constructed. Finally, the effects of the predicted biogenesis pathway on the biological functions of A549/DDP cells were verified by in vitro and in vivo experiments. ResultThe differentially transcribed genes of A549 and A549/DDP cells were analyzed by enrichment analysis and cell biological characteristics detection. The results showed that A549/DDP cells showed significantly increased resistance to cisplatin, glucose metabolism signaling pathway and glycolysis levels compared with A549 cells. Among glycolysis-related transcription genes, PKM had the most significant difference Fold Change is 8. LncRNA PCIF1 is a new marker of A549/DDP cells and can be used as a molecular sponge to regulate the expression of PKM. LncRNA PCIF1 targets miR-326 to induce PKM expression, promote glycolysis level, and enhance the resistance of A549/DDP cells to cisplatin. ConclusionLncRNA PCIF1 as biomarkers of A549/DDP cells, higher expression can induce the PKM, promote cell glycolysis, lead to the occurrence of cisplatin resistance. LncRNA PCIF1 can be considered as a potential target for treating cisplatin-resistant NSCLC.

Identification of Key Genes and Signaling Pathways in Entrectinibresistant Non-small Cell Lung Cancer Using Bioinformatic Analysis and Experimental Verification.

Entrectinib, a ROS1 inhibitor, is effective in patients with ROS1-positive non-small-cell lung cancer (NSCLC). However, entrectinib resistance remains a challenge worldwide. The biomarkers of entrectinib resistance and molecular mechanisms have not been clarified based on the Gene Expression Omnibus (GEO) database. The aim of this study is to identify key genes and signaling pathways involved in the development of entrectinib-resistant NSCLC through bioinformatics analysis and experimental validation. Differentially expressed genes (DEGs) were screened between entrectinib resistant and parental human NSCLC cell lines of the GSE214715 dataset, lung adenocarcinoma (LUAD) and non-tumor adjacent tissues of the GSE75037 dataset, and NSCLC and non-tumor adjacent tissues of the GSE18842 dataset. Functional enrichment analyses were performed, including Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Overlapped DEGs among those three datasets were identified using the Venn diagram package. The transcriptional levels of key genes were investigated using the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). The association between transcriptional levels of key genes and survival was analyzed using Kaplan-Meier Plotter (https://www.kmplot.com/analysis/). The correlations between hub genes and immune cell infiltration were investigated using the Tumor Immune Estimation Resource (TIMER) database. Specific signaling pathway enrichment analysis was performed using Gene Set Enrichment Analysis (GSEA) of LinkedOmics. Competitive endogenous RNA (ceRNA) networks, genome-wide association studies (GWAS), and drug sensitivity analyses of key genes were further investigated. The expression of ZEB2 was subsequently confirmed in both parental HCC78 cells and entrectinib-resistant HCC78 cells using real-time quantitative polymerase chain reaction (qRT-PCR). 708 DEGs were identified between entrectinib-resistant CUTO28 (CUTO28-ER) and parental CUTO28 cell lines in the GSE214715 dataset. One thousand three hundred and ninety-five DEGs were identified between entrectinib resistant (CUTO37-ER) and parental CUTO37 cell lines in the GSE214715 dataset. Eight hundred and forty-nine DEGs were identified between LUAD and non-tumor adjacent tissues in the GSE75037 dataset. Seven hundred and sevety-three DEGs were identified between NSCLC and non-tumor adjacent tissues in the GSE18842 dataset. Among these three datasets, seven overlapped DEGs were identified, including ZBED2, CHI3L2, CELF2, SEMA5A, ZEB2, S100A12, and PDK4. Among these seven overlapped DEGs, the expression levels of CHI3L2, ZEB2, and S100A12 were downregulated in those three datasets. The results of analysis using the UALCAN database showed that these three genes were significantly downregulated in LUAD and LUSC patients compared with the normal population. However, only the lower transcriptional level of ZEB2 was linked to worse survival in patients with lung cancer. GSEA analysis revealed that ZEB2 was significantly negatively correlated with nucleotide excision repair (NER) in LUAD, and homologous recombination (HR) and NER in LUSC, which were linked to drug resistance. A ceRNA network of THRB-AS1/ has-miR-1293/ ZEB2 in LUAD was established. We have identified core genes associated with non-small cell resistance to entrectinib, including CHI3L2, ZEB2, and S100A12. ZEB2 is a core gene associated with acquired resistance to entetinib in NSCLC.

Dynamic landscape of a competing endogenous RNA (ceRNA) network in Early-Onset Preeclampsia under hypoxia conditions

Objective: Early-onset preeclampsia (EOPE) manifests as elevated blood pressure and indications of organ damage, predominantly in the kidneys, in women before 34 weeks of gestation. A growing body of evidence suggests that hypoxia triggers a series of maladaptive responses culminating in the progression of EOPE. However, the precise mechanisms underlying these processes remain largely undefined. This study aimed to map the dynamic interplay within the competing endogenous RNA (ceRNA) network in EOPE under hypoxic conditions to provide insights into its molecular etiology. Methods: To investigate the oxidative stress response in EOPE, RNA sequencing data (ID: GSE119265) were retrieved from the Gene Expression Omnibus (GEO) database for exhaustive analysis. Oxygen-sensitive differential expressed genes (DEGs) were identified by comparing EOPE samples to controls at 5% and 20% O2 concentrations, respectively. Furthermore, the STRING database facilitated the construction of a protein-protein interaction network, highlighting critical hub genes among the identified DEGs. Results: An intricate ceRNA network encompassing four representative DEGs (AOC1, DCN, TGFB1, and SYNE3) and seven differentially expressed long non-coding RNAs (HCG27, MEG3, XIST, LINC01119, LINC00964, LINC01118, and LINC01588) was established. Conclusions: Our analysis revealed a set of long non-coding RNA that respond to hypoxic stress, shedding light on their possible roles in the oxygen-dependent pathophysiology of EOPE. These insights offer new avenues for targeted EOPE diagnosis and treatment. Further studies are required to elucidate their precise functions.

A comparative cross-platform analysis of cuproptosis-related genes in human nonobstructive azoospermia: An observational study.

This study aimed to identify novel biomarkers associated with cuproptosis in human nonobstructive azoospermia (NOA). We obtained 4 NOA microarray datasets (GSE145467, GSE9210, GSE108886, and GSE45885) from the NCBI Gene Expression Omnibus database and merged them into training set. Another NOA dataset (GSE45887) was used as validation set. Differentially expressed cuproptosis-related genes were identified from training set. Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted. Least absolute shrinkage and selection operator regression and support vector machine-recursive feature elimination were used to identify hub cuproptosis-related genes. We calculated the expression of the hub cuproptosis-related genes in both validation set and patients with NOA. Gene set variation analysis was used to explore their potential biological functions. The risk prediction model was built by logistic regression analysis and was evaluated in the validation set. Finally, we constructed a competing endogenous RNA network. The training set included 29 patents in the control group and 92 in the NOA group, and 10 cuproptosis-related differentially expressed genes were identified. Subsequently, we screened 6 hub cuproptosis-related genes (DBT, GCSH, NFE2L2, NLRP3, PDHA1, and SLC31A1) by least absolute shrinkage and selection operator regression and support vector machine-recursive feature elimination. GCSH, NFE2L2, NLRP3, and SLC31A1 expressed higher in NOA group than in control group (P < .05) in the validation set (4 patients in control and 16 in NOA groups), while the expression levels of GCSH, NFE2L2, NLRP3, PDHA1, and SLC31A1 were higher in NOA group than in control group (P < .05) in our patients (3 patients in control and 4 in NOA groups). The model based on the 6-gene signature showed superior performance with an AUC value of 0.970 in training set, while 1.0 in validation set. Gene set variation analysis revealed a higher enrichment score of "homologous recombination" in the high expression groups of the 6 hub genes. Finally, we constructed a competing endogenous RNA network and found hsa-miR-335-3p and hsa-miR-1-3p were the most frequently related to the 6 hub genes. DBT, GCSH, NFE2L2, NLRP3, PDHA1, and SLC31A1 may serve as predictors of cuproptosis and play important roles in the NOA pathogenesis.

Identification of an Exosome-relevant SNHG6-hsa-miR-429- CHRDL1/CCNA2 Axis for Lung Adenocarcinoma Prognosis Evaluation.

To explore an exosome-relevant molecular classification in lung adenocarcinoma (LUAD). Exosome genes or relevant non-coding RNAs are regulators of cancer treatment and prognosis, but their function in LUAD has not yet been determined. Unraveling a molecular classification applying exosome-related RNA networks for LUAD prognosis evaluation. MicroRNA sequencing data (miRNAs-seq) and RNA sequencing data (RNA- seq) were derived from The Cancer Genome Atlas (TCGA). The ConsensusCluster- Plus package was used for molecular typing in LUAD based on 121 Exosome-related genes. Then, a limma package was conducted to explore differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs) and differentially expressed lncRNAs (DElncRNAs) in molecular typing for constructing an Exosome-driven competing endogenous RNA network (ceRNA). Dominant miRNAs, as well as target mRNAs, were identified by COX modeling and Kaplan-Meier survival analysis. Two Exosome-associated molecular clusters classified in LUAD. The C2 cluster favored high clinicopathology and showed a trend toward poor prognosis. 29 lncRNA- miRNA and 12 miRNA-mRNA interaction pairs were identified. The hsa-miR-429 was the pivotal miRNA in the network that affected the prognosis of LUAD. According to the interaction relationship and LUAD prognostic role, SNHG6-hsa- miR-429-CHRDL1/CCNA2 was identified. SNHG6-hsa-miR-429-CHRDL1 exerts oncogenic effects, and SNHG6-hsa-miR-429- CCNA2 exerts pro-oncogenic effects. Overall, our study identified an Exosome-driven ceRNA network in LUAD, and the SNHG6-hsa-miR-429-CHRDL1/CCNA2 axis could be a new therapeutic target for LUAD and our study provides new insights into the molecular mechanisms of LUAD.

Genetic Analysis of Potential Biomarkers and Therapeutic Targets in Ferroptosis from Steroid-Induced Osteonecrosis of the Femoral Head Based on Machine Learning.

To locate the candidate therapeutic target genes involved in ferroptosis in steroid-induced osteonecrosis of the femoral head (SONFH). Bioinformatics analysis study. Place and Duration of the Study: Department of Orthopaedic Surgery, Zhuhai Hospital of Integrated Traditional Chinese and Western Medicine, Guangdong, China, from March to July 2023. After processing the gene expression omnibus (GEO) data with the R programming language, differentially expressed ferroptosis-related genes in SONFH were identified. To pinpoint the genes most strongly linked to SONFH in association with ferroptosis, least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) were employed. Subsequently, the screened essential genes were analysed to investigate immune cell infiltration, and competing endogenous RNA (ceRNA) networks involving these marker genes were constructed. The machine learning algorithms identified three genes i.e., SOCS1 (suppressor of cytokine signalling1), MYCN (N-myc proto-oncogene protein), and KLF2 (Kruppel-like factor 2) as diagnostic feature biomarkers associated with ferroptosis. Additionally, CIBERSORT analysis revealed that alterations in the immune microenvironment, such as Macrophages M1, Monocytes, and T cells CD4 naive, could be linked to SOCS1, MYCN, and KLF2. Moreover, the competing endogenous RNA (ceRNA) network exposed a complex regulatory relationship based on marker genes. SOCS1, MYCN, and KLF2 are potential biomarkers associated with ferroptosis in SONFH, pending confirmation in future studies. Steroid-induced osteonecrosis of the femoral head, Ferroptosis, Machine learning, Genetic analysis.

Identification and Validation of IFI44 as a Novel Biomarker for Primary Sjögren's Syndrome.

Primary Sjögren's syndrome (pSS) is an autoimmune condition marked by lymphocyte infiltration in the exocrine glands. Our study aimed to identify a novel biomarker for pSS to improve its diagnosis and treatment. The gene expression profiles of pSS were obtained from the Gene Expression Omnibus (GEO) database. The specific differentially expressed genes (DEGs) were screened by the Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Recursive Feature Elimination with Support Vector Machines (SVM-RFE). A biomarker was picked out based on correlation and diagnostic performance, the connection between the biomarker and clinical traits and immune infiltrating cells was explored, and the biomarker's protein expression level in the serum of pSS patients was detected by enzyme-linked immunosorbent assay (ELISA). The competitive endogenous RNA (ceRNA) network regulated by the biomarker was predicted to verify the reliability of the biomarker in diagnosing pSS. IFI44, XAF1, GBP1, EIF2AK2, IFI27, and IFI6 showed prominent diagnostic ability, with the high accuracy (AUC = 0.859) and significance (R ≥ 0.8) of IFI44 within the training dataset. IFI44 strongly exhibited a negative correlation with resting NK cells, macrophages M0, and eosinophils, and a positive correlation with activated dendritic cells, naive B cells, and activated CD4 memory T cells. Furthermore, IFI44 was significantly positively correlated with clinical traits such as IgG, SSA, SSB, ANA, and ESSDAI, with its protein expression level in the serum of pSS patients being notably elevated compared to controls (p < 0.001). Finally, the ceRNA regulatory network showed that hsa-miR-944, hsa-miR-9-5p, hsa-miR-126-5p, and hsa-miR-335-3p were significantly targeted IFI44, suggesting that IFI44 may serve as a dependable biomarker for pSS. In this study, we dug out IFI44 as a biomarker for pSS, systematically studied the potential regulatory mechanism of IFI44, and verified its reliability as a biomarker for pSS.

Expression profile of circular RNAs in blood samples of Northern Chinese males with intracerebral hemorrhage shows downregulation of hsa-circ-0090829

Circular RNAs (circRNAs) are involved in several neurological disorders; however, the mechanisms underlying their involvement remain to be clarified. We attempted to explore the expression profiles of circRNAs and their potential functions and mechanisms in the pathogenesis of intracerebral hemorrhage (ICH) in Northern Chinese males. The microarray results showed that 50 circRNAs were significantly upregulated, while 194 circRNAs were significantly downregulated in ICH patients compared with healthy controls (p < 0.05). After bioinformatics analysis, a circRNA–microRNA–messenger RNA network and a protein–protein interaction network were constructed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the neurotrophin signaling pathway, long-term potentiation, and the mitogen-activated protein kinase pathway are potentially implicated in ICH pathophysiology. The quantitative real-time polymerase chain reaction results revealed that hsa-circ-0090829 was significantly downregulated in ICH. The receiver operating characteristic curve analysis showed that the area under the curve of hsa-circ-0090829 between ICH and healthy controls was 0.807. Furthermore, the dual-luciferase assay showed that hsa-circ-0090829 sponged miR-526b-5p. This study reports the altered expression of circRNAs and identifies the potential functions of these circRNAs in ICH. Our results may facilitate further mechanistic research on circRNAs in ICH and provide probable novel diagnostic biomarkers and therapeutic targets for ICH.

LncRNA ZFHX4-AS1 as a novel biomarker in adrenocortical carcinoma.

Adrenocortical carcinoma (ACC) is a rare and highly aggressive malignant tumor. Currently, there is a lack of reliable prognostic markers in clinical practice. Extensive research has shown that long non-coding RNA (lncRNA) are critical factors in the initiation and progression of cancer, closely associated with early diagnosis and prognosis. Previous studies have identified that ZFHX4 antisense RNA 1 (ZFHX4-AS1) is aberrantly expressed in various cancers and is associated with poor outcomes. This study investigates whether ZFHX4-AS1 affects the prognosis of ACC patients and, if so, the potential mechanisms involved. In this study, utilizing four multi-center cohorts from The Cancer Genome Atlas (TCGA) program and Gene Expression Omnibus (GEO), we validated the prognostic capability of ZFHX4-AS1 in ACC patients through Kaplan-Meier survival analysis, cox regression models, and nomograms. Then, we explored the biological functions of ZFHX4-AS1 using gene set enrichment analysis (GSEA), competing endogenous RNA (ceRNA) networks, and analyses of somatic mutations and copy number variation (CNV). Finally, in vitro experiments were conducted to further validate the impact of ZFHX4-AS1 on proliferation and migration capabilities of ACC cell lines. Survival analysis indicated that patients in the high ZFHX4-AS1 expression group of ACC had worse prognosis. Cox regression analyses suggested that ZFHX4-AS1 levels were independent risk factors for prognosis. Subsequently, we constructed nomograms based on clinical features and ZFHX4-AS1 levels, demonstrating good predictive performance under the time-dependent receiver operating characteristic (ROC) curve. Analysis based on somatic mutations and CNV revealed that CTNNB1 and 9p21.3-Del drove the expression of ZFHX4-AS1. Cell Counting Kit-8 (CCK-8), colony formation, and Transwell assays confirmed that knockdown of ZFHX4-AS1 inhibited proliferation and migration of ACC cells. This study demonstrates that ZFHX4-AS1 has a reliable predictive value for the prognosis of ACC patients and is a promising biomarker.