Explore the vast range of titles available.

BackgroundRheumatoid arthritis (RA) is a chronic autoimmune and inflammatory disease, and circular RNAs (circRNAs) are widely involved in its progression. Baicalin, a naturally derived small molecule, has been shown to improve inflammatory responses in RA by regulating circRNAs; however, the underlying regulatory mechanism remains unclear.ObjectiveThis study aimed to investigate how circ₀000734 participates in the inflammatory response of RA-FLS through the miR-197-5p/IKBKB axis and to clarify the intervention effect of baicalin.MethodsThe expression level of circ₀000734 in peripheral blood mononuclear cells (PBMCs) from RA patients was detected by qRT-PCR. Correlation analysis was performed to evaluate the associations between circ₀000734 expression and clinical indicators, including rheumatoid factor (RF), anti-cyclic citrullinated peptide antibody (anti-CCP), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and DAS28 scores. The downstream targets miR-197-5p and IKBKB were predicted using bioinformatics databases. Dual-luciferase reporter assays were performed to verify the targeting relationship between circ₀000734 and miR-197-5p, as well as the binding relationship between miR-197-5p and IKBKB. Subsequently, circ₀000734 and miR-197-5p were silenced or overexpressed in a TNF-α-stimulated RA fibroblast-like synoviocyte (RA-FLS) model to validate their regulatory relationship. Flow cytometry (FCM), Cell Counting Kit-8 (CCK-8), reverse transcription quantitative polymerase chain reaction (RT-qPCR), Western blot (WB), and enzyme-linked immunosorbent assay (ELISA) were used to determine the effects of circ₀000734 and miR-197-5p silencing/overexpression, as well as baicalin treatment, on RA-FLS cell viability, cell cycle progression, the NF-κB signaling pathway, and the expression of inflammatory factors, including IL-17, IL-23, IL-4, and IL-10.Resultscirc₀000734 was highly expressed in PBMCs from RA patients and was positively correlated with disease activity indicators, including RF, CCP, CRP, ESR, and DAS28 scores. In the TNF-α-stimulated RA-FLS cell model, overexpression of circ₀000734 promoted RA-FLS cell proliferation, activated the NF-κB pathway, and disrupted the balance between pro-inflammatory and anti-inflammatory factors, whereas circ₀000734 silencing exerted the opposite effects. Dual-uciferase reporter assays confirmed the targeting relationship between circ₀000734 and miR-197-5p. Overexpression of miR-197-5p reversed the effects of circ₀000734 overexpression on RA-FLS cell viability, the downstream target gene IKBKB, the NF-κB pathway, and inflammatory factors. In addition, baicalin treatment downregulated circ₀000734 expression, thereby inhibiting the activation of the NF-κB pathway, improving the inflammatory cytokine profile, and reversing the adverse phenotype induced by circ₀000734 overexpression.ConclusionHighly expressed circ₀000734 in RA promotes NF-κB pathway activation by inhibiting miR-197-5p expression, thereby enhancing RA-FLS cell viability and promoting inflammatory cytokine secretion. Baicalin may inhibit the high expression of circ₀000734 and activation of the NF-κB signaling pathway, ultimately alleviating the inflammatory response in RA-FLS.

Noncoding RNAs (ncRNAs) constitute the majority of the human transcribed genome. This largest class of RNA transcripts plays diverse roles in a multitude of cellular processes, and has been implicated in many pathological conditions, especially cancer. The different subclasses of ncRNAs include microRNAs, a class of short ncRNAs; and a variety of long ncRNAs (lncRNAs), such as lincRNAs, antisense RNAs, pseudogenes, and circular RNAs. Many studies have demonstrated the involvement of these ncRNAs in competitive regulatory interactions, known as competing endogenous RNA (ceRNA) networks, whereby lncRNAs can act as microRNA decoys to modulate gene expression. These interactions are often interconnected, thus aberrant expression of any network component could derail the complex regulatory circuitry, culminating in cancer development and progression. Recent integrative analyses have provided evidence that new computational platforms and experimental approaches can be harnessed together to distinguish key ceRNA interactions in specific cancers, which could facilitate the identification of robust biomarkers and therapeutic targets, and hence, more effective cancer therapies and better patient outcome and survival.

β-Thalassemia is a chronic hemolytic anemia caused by mutations in the β-globin gene. Increasing studies have shown that circular RNA (circRNA) plays a key role in abnormal hematopoiesis. Circ₀001428 is formed by circularization of the beta-mannosidase gene. However, little is known about the biological function of circ₀001428 in β-thalassemia. Circ₀001428 was selected from two circRNA microarrays (GSE241141 and GSE196682) of β-thalassemia, and expression levels of circ₀001428, miR-32-3p, miR-325-3p, γ-globin, activating transcription factor 4 (ATF4) and B-cell lymphoma/leukemia 11 A (BCL11A) were validated in 30 patients with β-thalassemia and 30 healthy controls. Cell proliferation, apoptosis, cell cycle, and erythroid differentiation were evaluated using stable knockdown or overexpression of circ₀001428. Fluorescence in situ hybridization, dual-luciferase reporter, and Western blots were performed to confirm interactions between circ₀001428, miR-32-3p/miR-325-3p, and ATF4. Circ₀001428 was downregulated in β-thalassemia patients compared to controls, promoted cell proliferation, decreased cell apoptosis, and inhibited terminal erythroid differentiation and γ-globin production. Mechanistically, circ₀001428 functions as a sponge for miR-32-3p and miR-325-3p to promote ATF4 expression, thereby activating BCL11A expression. Additionally, rescue experiments confirmed that circ₀001428 regulated erythropoiesis and γ-globin expression via promoting the ATF4-BCL11A axis by binding with miR-32-3p/miR-325-3p. Our findings reveal, for the first time, the important role of circ₀001428 in regulating erythropoiesis and γ-globin expression in β-thalassemia. The circ₀001428/miR-32-3p and miR-325-3p/ATF4/BCL11A/γ-globin signaling pathway may be a potential therapeutic target in β-thalassemia, especially for fetal hemoglobin modulation.

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).BACKGROUNDTumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).\"GEO2R,\" \"limma\" R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. \"Survival,\" \"survminer,\" \"rms\" R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.METHODS\"GEO2R,\" \"limma\" R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. \"Survival,\" \"survminer,\" \"rms\" R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = -0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By \"survival ROC\" R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.RESULTSA total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = -0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By \"survival ROC\" R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.CONCLUSIONIn conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.

Protein aggregation is classically considered the main cause of neuronal death in neurodegenerative diseases (NDDs). However, increasing evidence suggests that alteration of RNA metabolism is a key factor in the etiopathogenesis of these complex disorders. Non-coding RNAs are the major contributor to the human transcriptome and are particularly abundant in the central nervous system, where they have been proposed to be involved in the onset and development of NDDs. Interestingly, some ncRNAs (such as lncRNAs, circRNAs and pseudogenes) share a common functionality in their ability to regulate gene expression by modulating miRNAs in a phenomenon known as the competing endogenous RNA mechanism. Moreover, ncRNAs are found in body fluids where their presence and concentration could serve as potential non-invasive biomarkers of NDDs. In this review, we summarize the ceRNA networks described in Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, amyotrophic lateral sclerosis and spinocerebellar ataxia type 7, and discuss their potential as biomarkers of these NDDs. Although numerous studies have been carried out, further research is needed to validate these complex interactions between RNAs and the alterations in RNA editing that could provide specific ceRNET profiles for neurodegenerative disorders, paving the way to a better understanding of these diseases.

Pseudogenes are now known to regulate their protein-coding counterparts. Additionally, disturbances of 3′UTRs could increase the risk of cancer susceptibility by acting as modulators of gene expression. The aim of this study was to investigate the roles of the pseudogene CYP4Z2P-3′UTR and functional gene CYP4Z1-3′UTR in breast cancer angiogenesis process. The levels of CYP4Z2P- and CYP4Z1-3′UTR and miRNA of interests were measured in 22 cancerous tissues paired with non-cancerous samples by qRT-PCR. The effects of CYP4Z2P- and CYP4Z1-3′UTR were studied by overexpression and RNA interference approaches in vitro and ex vivo . Insights of the mechanism of competitive endogenous RNAs were gained from bioinformatic analysis, luciferase assays, and western blot. The positive CYP4Z2P/CYP4Z1 interaction and negative interaction between predicted miRNAs and CYP4Z2P or CYP4Z1 were identified via qRT-PCR assay and bivariate correlation analysis. CYP4Z2P- and CYP4Z1-3′UTR share several miRNA-binding sites, including miR-211, miR-125a-3p, miR-197, miR-1226, and miR-204. The CYP4Z2P- and CYP4Z1-3′UTRs arrest the interference caused by of these miRNAs, resulting in increased translation of CYP4Z1. Moreover, ectopic expression of the CYP4Z2P- and CYP4Z1-3′UTRs exhibit tumor angiogenesis-promoting properties in breast cancer collectively by inducing the phosphorylation of ERK1/2 and PI3K/Akt. Co-transfection with Dicer siRNA reversed the CYP4Z2P 3′UTR-mediated changes. Additionally, PI3K or ERK inhibitors reversed CYP4Z2P- and CYP4Z1-3′UTR-mediated changes in VEGF-A expression. Increased CYP4Z2P- and CYP4Z1-3′UTR expression promotes tumor angiogenesis in breast cancer partly via miRNA-dependent activation of PI3K/Akt and ERK1/2. The CYP4Z2P- and CYP4Z1-3′UTRs could thus be used as combinatorial miRNA inhibitors.

A recently discovered dimension of post-transcriptional gene regulation involves co-regulatory crosstalk between RNA transcripts, which compete for common pools of microRNA (miRNA) molecules. These competing endogenous RNAs (ceRNAs), or natural miRNA sponges, have an active role in regulating miRNA availability within the cell and form intertwined regulatory networks. Recent reports have implicated diverse RNA species including protein-coding messenger RNAs and non-coding RNAs as ceRNAs in human development and diseases including human cancer. In this review, we discuss the most recent discoveries that implicate natural miRNA decoys in human cancer biology, as well as exciting advances in the study of ceRNA networks and dynamics. The structure and topology of intricate genome-scale ceRNA networks can be predicted computationally, and their dynamic response to fluctuations in ceRNA and miRNA levels can be studied via mathematical modeling. Additionally, the development of new methods to quantitatively determine absolute expression levels of miRNA and ceRNA molecules have expanded the capacity to accurately study the efficiency of ceRNA crosstalk in diverse biological models. These major milestones are of critical importance to identify key components of ceRNA regulatory networks that could aid the development of new approaches to cancer diagnostics and oligonucleotide-based therapeutics.

Background/Aims: Long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) play significant roles in the development of tumors, but the functions of specific lncRNAs and lncRNA-related ceRNA networks have not been fully elucidated for colon adenocarcinoma (COAD). In this study, we aimed to clarify the lncRNA-microRNA (miRNA)-mRNA ceRNA network and potential lncRNA biomarkers in COAD. Methods: We extracted data from The Cancer Genome Atlas (TCGA) and identified COAD-specific mRNAs, miRNAs, and lncRNAs. The biological processes in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed for COAD-specific mRNAs. We then constructed a ceRNA network of COAD-specific mRNAs, miRNAs and lncRNAs and analyzed the correlation between expression patterns and clinical features of the lncRNAs involved. After identifying potential mRNA targets of 4 lncRNAs related to overall survival (OS), we conducted stepwise analysis of these targets through GO and KEGG. Using tissue samples from our own patients, we also verified certain analytical results using quantitative real-time PCR (qRT-PCR). Results: Data from 521 samples (480 tumor tissue and 41 adjacent non-tumor tissue samples) were extracted from TCGA. A total of 258 specific lncRNAs, 206 specific miRNAs, and 1467 specific mRNAs were identified (absolute log 2 [fold change] > 2, false discovery rate < 0.01). Analysis of KEGG revealed that specific mRNAs were enriched in cancer-related pathways. The ceRNA network was constructed with 64 lncRNAs, 18 miRNAs, and 42 mRNAs. Among these lncRNAs involved in the network, 3 lncRNAs (LINC00355, HULC, and IGF2-AS) were confirmed to be associated with certain clinical features and 4 lncRNAs (HOTAIR, LINC00355, KCNQ1OT1, and TSSC1-IT1) were found to be negatively linked to OS (log-rank p < 0.05). KEGG showed that the potential mRNA targets of these 4 lncRNAs may be concentrated in the MAPK pathway. Certain results were validated by qRT-PCR. Conclusion: This study providing novel insights into the lncRNA-miRNA-mRNA ceRNA network and reveals potential lncRNA biomarkers in COAD.

Circular RNAs (circRNAs) are connected at the 3′ and 5′ ends by exon or intron cyclization, forming a complete ring structure. circRNA is more stable and conservative than linear RNA and abounds in various organisms. In recent years, increasing numbers of reports have found that circRNA plays a major role in the biological functions of a network of competing endogenous RNA (ceRNA). circRNAs can compete together with microRNAs (miRNAs) to influence the stability of target RNAs or their translation, thus, regulating gene expression at the transcriptional level. circRNAs are involved in biological processes such as tumor cell proliferation, apoptosis, invasion, and migration as ceRNAs. circRNAs, therefore, represent promising candidates for clinical diagnosis and treatment. Here, we review the progress in studying the role of circRNAs as ceRNAs in tumors and highlight the participation of circRNAs in signal transduction pathways to regulate cellular functions.