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Results for “Long non-coding RNAs”

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PubMed2026

Micropeptides encoded by lncRNAs associated with cancer progression reveal novel immunogenic epitopes.

MOTIVATION: Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin organization, and cellular signaling. Recent studies indicate that ∼20% of the ∼36 000 human lncRNA genes harbor small open reading frames (sORFs) capable of producing micropeptides (MPs), whose functions remain largely unknown. Whether these peptides contribute to the cancer immunopeptidome is largely unexplored. RESULTS: We systematically analyzed lncRNAs with strong experimental and computational evidence of MP-encoding potential (∼13% of the initial MP collection). Using The Cancer Genome Atlas (TCGA), we identified 2606 high-confidence lncRNA-derived MPs encoded by 647 genes across 16 cancer types. We then focused on 501 MPs from 124 lncRNA genes whose expression changes significantly across tumor stages and metastatic transitions, representing cancer transitional lncRNAs (Tr-lncRNAs). Dipeptide composition and conservation analyses showed that these MPs differ from a size-matched human coding proteome, supporting their potential as neoantigens. All possible 9-mer peptides were evaluated for predicted binding to prevalent European HLA class I alleles. Approximately 60% of Tr-lncRNA genes and 184 (37%) of derived peptides exhibited strong predicted HLA binding. Peptides from XIST, PCAT7, PVT1, HAND2-AS1 showed broad HLA coverage. Notably, TTN-AS1, encoded an MP (79 aa) generated 33 predicted distinct epitopes spanning all 27 HLA alleles. Our analysis identifies lncRNA-derived MPs as a previously underexplored source of potential cancer neoantigens, highlighting their promise as biomarkers and targets for immunotherapy. AVAILABILITY: Data, code and supplementary materials are available in https://doi.org/10.5281/zenodo.20167452 and GitHub: https://github.com/stavzok1/lncrna_peptide_analysis.

Humans↗

PubMed2026

Making multi-axis Gaussian graphical models scalable to millions of cells.

MOTIVATION: Networks underlie the generation and interpretation of many biological datasets: gene networks shed light on the regulatory structure of the genome, and cell networks can capture structure of the tumor micro-environment. However, most methods that learn such networks make the faulty "independence assumption"; to learn the gene network, they assume that no cell network exists. "Multi-axis" methods, which do not make this assumption, fail to scale beyond a few thousand cells or genes. This limits their applicability to only the smallest datasets. RESULTS: We develop a multi-axis method, which learns conditional dependency networks, capable of processing million-cell datasets within minutes. This was previously impossible, and unlocks the use of such methods on modern scRNA-seq datasets, as well as more complex datasets. We apply the method to a new scRNA-seq dataset for neuronal cell development, and compare the result to an existing state of the art method, hdWGCNA. We demonstrate that the new method yields gene networks that have a more focused biological interpretation and that the simultaneously learned cell network has advantages over a conventional kNN-based clustering. Further, our method yields novel biological insights by identifying long non-coding RNAs that potentially have a role in neuronal development. AVAILABILITY AND IMPLEMENTATION: Our methodology is available as a Python package GmGM on PyPI (https://pypi.org/project/GmGM/0.5.3/). The code for all experiments performed in this article is available on GitHub (https://github.com/BaileyAndrew/GmGM-Bioinformatics) and Zenodo (10.5281/zenodo.20384566).

Gene Regulatory Networks↗

PubMed2025

Constructing epigenetic regulatory landscapes of plant lncRNAs-an exploration utilizing the novel specialized platform PERlncDB.

Long non-coding RNAs (lncRNAs), once overlooked as transcriptional byproducts, are now recognized for their crucial roles in plant growth, development, and stress responses, with increasing focus on their epigenetic regulation. However, studies investigating epigenomic signals to explore the functions of lncRNAs in plants remain relatively limited. This study collected a comprehensive dataset of over 160 000 high-quality lncRNAs from 19 representative plant species and integrated 6715 ChIP-seq, BS-seq, and RNA-seq datasets to analyze epigenomic patterns at lncRNA loci. Results showed elevated DNA methylation in lncRNA regions. The highest levels occurred in transposable element-associated lncRNAs. Additionally, activating histone modifications at lncRNA loci showed tissue specificity, with epigenetic preferences differed from those at protein-coding gene (PCG) loci. Differential site analysis in epigenetic mutants further highlighted the selective regulation of lncRNA loci by specific epigenetic factors. To facilitate research, we developed PERlncDB, a platform that provides species-specific lncRNA browsing, epigenetic annotation, cross-species conservation analysis, and visualization of epigenomic landscapes. Case studies on MARS and LINC-AP2 emphasized the platform's utility. Conserved epigenetic mechanisms regulating lncRNAs across species, exemplified by a syntenic conserved MET1-regulated lncRNA pair in Arabidopsis and tomato, suggested the stability of regulatory mechanisms underlying lncRNA functions. This work provides critical insights and resources for understanding plant lncRNA epigenetic regulation.

RNA, Long Noncoding↗

PubMed2026

Transcriptome changes in circulating immune cells of critical COVID-19 patients predict a specific metabolic and epigenetic imprint.

BACKGROUND: The progression to critical COVID-19 arises predominantly from a dysregulated host immune response although the underlying regulatory mechanisms still remain partially elusive. This limits a prompt prediction of the disease progression, reduces the therapeutic options and restrains our understanding of “long COVID”. METHODS: Here, we analyzed the transcriptome of peripheral blood mononuclear cells (PBMCs) collected from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients enrolled in the clinical trial COntAGIouS as well as independent bulk RNA-seq, single-cell RNA-seq and proteomic datasets. RESULTS: In critical COVID-19 patients, the integrative analysis of transcriptomic data revealed an altered regulatory network involving microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and coding genes that control mRNA translation-related genes, epigenetics, and metabolism. In parallel, we observed an upregulation of tRNA aminoacylation genes in critical COVID-19 patients by the analysis of either bulk or single-cell RNA-seq data from publicly available independent cohorts. Additionally, we found increased expression of coding genes enriched for the cognate amino acids (glycine, alanine, isoleucine and tyrosine), all related to protein localization, post-translational modifications, and cell metabolism in our cohort. Similar alterations in amino acid frequency were found in an independent proteomic dataset. CONCLUSIONS: Collectively, our findings indicate a broad perturbation of the gene expression landscape that characterizes the aberrant host immune response in critical COVID-19 patients and is potentially coordinated by miRNA and tRNA metabolism alterations. TRIAL REGISTRATION: COntAGIouS, NCT04327570. Registered 26 March 2020, https://clinicaltrials.gov/ct2/show/NCT04327570 .

Female↗

PubMed2024

Inhibiting the expression of spindle appendix cooled coil protein 1 can suppress tumor cell growth and metastasis and is associated with cancer immune cells in esophageal squamous cell carcinoma.

Inhibiting the expression of spindle appendix cooled coil protein 1 (SPDL1) can slow down disease progression and is related to poor prognosis in patients with esophageal cancer. However, the specific roles and molecular mechanisms of SPDL1 in esophageal squamous cell carcinoma (ESCC) have not been explored yet. The current study aimed to investigate the expression levels of SPDL1 in ESCC via transcriptome analysis using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Moreover, the biological roles, molecular mechanisms, and protein networks involved in SPDL1 were identified using machine learning and bioinformatics. The cell counting kit-8 assay, EdU staining, and transwell assay were used to investigate the effects of inhibiting SPDL1 expression on ESCC cell proliferation, migration, and invasion. Finally, the correlation between the SPDL1 expression and cancer immune infiltrating cells was evaluated by analyzing data from the TCGA database. Results showed that SPDL1 was overexpressed in the ESCC tissues. The SPDL1 expression was related to age in patients with ESCC. The SPDL1 co-expressed genes included those involved in cell division, cell cycle, DNA repair and replication, cell aging, and other processes. The high-risk scores of SPDL1-related long non-coding RNAs were significantly correlated with overall survival and cancer progression in patients with ESCC (P < 0.05). Inhibiting the SPDL1 expression was effective in suppressing the proliferation, migration, and invasion of ESCC TE-1 cells (P < 0.05). The overexpression of SPDL1 was positively correlated with the levels of Th2 and T-helper cells, and was negatively correlated with the levels of plasmacytoid dendritic cells and mast cells. In conclusion, SPDL1 was overexpressed in ESCC and was associated with immune cells. Further, inhibiting the SPDL1 expression could effectively slow down cancer cell growth and migration. SPDL1 is a promising biomarker for treating patients with ESCC.

Humans↗

PubMed2026

Integrative analysis identifies a glycosylation-related lncRNA signature associated with prognosis in kidney renal clear cell carcinoma.

BACKGROUND: Glycosylation and long non-coding RNAs (lncRNAs) play critical roles in tumor progression. However, the prognostic significance of glycosylation-related lncRNAs (GRLncs) in kidney renal clear cell carcinoma (KIRC) remains largely unclear. This study aimed to identify prognostic GRLncs and construct a predictive model for KIRC prognosis. METHODS: Transcriptomic and clinical data of KIRC patients were analyzed to identify GRLncs associated with overall survival (OS). A prognostic model was constructed based on selected GRLncs, and its predictive performance was evaluated using Kaplan-Meier (KM) survival analysis, receiver operating characteristic (ROC) curves, and univariate and multivariate Cox regression analyses. Patients were stratified into high- and low-risk groups according to the median risk score, and internal validation was performed using training and testing cohorts to assess the stability of the model. Tumor microenvironment characteristics, immune checkpoint expression, immunotherapy response, and drug sensitivity were further analyzed. In addition, the expression of three signature lncRNAs was validated by real-time quantitative polymerase chain reaction (RT-qPCR) in 10 paired KIRC tumor and adjacent normal tissues. Functional roles of selected lncRNAs were investigated using antisense oligonucleotides (ASOs)-mediated knockdown in KIRC cell lines, followed by Cell Counting Kit 8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU) incorporation, colony formation, and migration assays. RESULTS: Five GRLncs (AC093278.2, EPB41L4A-DT, DLGAP1-AS2, AC084876.1, and AC005261.3) were identified and used to construct a prognostic model. AC093278.2 and EPB41L4A-DT were protective factors, whereas DLGAP1-AS2, AC084876.1, and AC005261.3 were risk factors. KM analysis on GRLncs-based risk score stratification revealed patients in the high-risk group had significantly poorer OS than those in the low-risk group. ROC analysis and Cox regression demonstrated that the GRLnc-based risk score served as an independent predictor of KIRC prognosis and exhibited favorable predictive performance compared with conventional clinical variables. High- and low-risk groups also exhibited distinct immune microenvironment characteristics, immune checkpoint expression patterns, and predicted drug sensitivities. RT-qPCR detected significant downregulation of protective factor-EPB41L4A-DT in KIRC tissues, while risk factors-DLGAP1-AS2 and AC084876.1 showed expression trends consistent with their predicted risk attributes. Functional experiments further revealed that knockdown of DLGAP1-AS2 and AC084876.1 suppressed proliferation and migration of KIRC cells, whereas knockdown of EPB41L4A-DT promoted these processes, supporting the biological relevance of these three signature lncRNAs. CONCLUSIONS: This study establishes a novel prognostic model based on five GRLncs that showed promising performance in The Cancer Genome Atlas (TCGA)-based analyses of KIRC. The combined clinical expression analysis and functional validation of three constituent GRLncs (DLGAP1-AS2, EPB41L4A-DT, and AC084876.1) supports the biological plausibility of the model and suggest that GRLncs may serve as potential prognostic biomarkers and therapeutic targets for KIRC.

Kidney renal clear cell carcinoma (KIRC)↗

PubMed2026

Teleost lincRNAs: Functional roles, regulatory mechanisms, and future applications in aquaculture.

Long intergenic non-coding RNAs (lincRNAs) regulate gene expression across vertebrate physiological systems, yet their functional roles in teleost fish remain incompletely synthesized. This review systematically integrates current evidence through PRISMA-guided searches across PubMed, Web of Science, and Scopus, identifying ten lincRNA-focused functional studies with genetic, mechanistic, or developmental validation, complemented by twenty two supplementary contextual references. Findings span development, immunity, environmental adaptation, reproduction, regeneration, and toxicology, with each association graded as experimentally validated, bioinformatically predicted, correlational, or speculative. This synthesis offers three core contributions. First, it shows that cis-acting regulation on neighboring genes, mediated through Wnt, NF-κB, and AHR signaling, is the dominant validated lincRNA mechanism across teleost physiological domains. Second, it demonstrates that direct experimental validation, primarily via CRISPR-Cas9 and chromatin-capture assays, remains concentrated in zebrafish, whereas aquaculture-species associations remain largely correlational. Third, it identifies two findings that challenge current lincRNA classification: unexpected regulatory directionality at the slincR-sox9b locus, and micropeptide-encoding potential within annotated lincRNAs. Together, these contributions establish an evidence-graded foundation for future mechanistic studies and translational aquaculture applications.

Aquaculture↗

PubMed2020

LINC00922 regulates epithelial-mesenchymal transition, invasive and migratory capacities in breast cancer through promoting NKD2 methylation.

Breast cancer ranks as the major reason for mortality in women populations, accounting for 23% of all cancer deaths. One in every three Asian women encounters the risk of this cancer in their lifetime. Long intergenic non-coding RNAs (lincRNAs) have emerged as tumor promoters and suppressors. The molecular mechanism of breast cancer remains elusive. Therefore, the current study aimed to explore the role lincRNA LINC00922 plays in the development of breast cancer. Breast cancer tissues and adjacent tissues were obtained from 109 patients with breast cancer. The RNA extraction and quantification and immunohistochemical staining characterized the high expression of LINC00922 and low expression of NKD2 in breast cancer tissues in comparison to its adjacent counterparts. Furthermore, the ectopic expression and knockdown experiments were conducted to figure out the in vivo and in vitro effects of LINC00922 on breast cancer progression. The ectopically expressed LINC00922 activated the Wnt signaling pathway, promoted epithelial-mesenchymal transition, cell proliferative, invasive and migratory capacities, tumor growth and metastasis. Additionally, the RIP and ChIP assay identified that LINC00922 recruited DNMT1, DNMT3A and DNMT3B proteins in the promoter region of NKD2 to promote NKD2 promoter methylation, thus reducing the NKD2 expression. Moreover, the Wnt signaling pathway was activated subsequent to NKD2 silencing, which was reversed by LINC00922 silencing. Lastly, the anti-oncogenic effects of LINC00922 inhibition was antagonized after NKD2 knocked down. The current study provides evidence that LINC00922 acts as a tumor promoter by promoting NKD2 methylation. Hopefully, it provides a novel potential gene target for the treatment of breast cancer.

Adaptor Proteins, Signal Transducing↗

PubMed2026

Exploring the Effect of Whole-Genome Duplication on Salmonid LincRNA Repertoire.

Long intergenic non-coding RNAs (lincRNAs) are key epigenetic regulators of genome function, yet their evolutionary dynamics following whole-genome duplication (WGD) events remain poorly understood. Salmonids, which underwent a lineage-specific autotetraploidization (salmonid-specific WGD, ~88-100 million years ago), provide an excellent model to investigate the retention, divergence, and functional potential of recently duplicated non-coding elements. LincRNA repertoires were compared across five genome-annotated salmonids (Oncorhynchus tshawytscha, O. kisutch, O. mykiss, Salmo salar, and S. trutta) and their closest non-duplicated relative, northern pike (Esox lucius). LincRNAs represented ~5-7% of annotated genes in all salmonids except S. salar (18%). Sequence conservation was low relative to coding genes, with only 11-68 highly similar (e-value < 1 × 10-30; similarity > 70% and alignments > 100 nucleotides) putative orthologues shared between salmonids and northern pike, and 161-338 among salmonids alone. Synteny conservation was modest in lincRNAs, with lower conservation in putative orthologues (8-16%) compared to putative ohnologues (8-33%). Secondary structure conservation was associated with sequence similarity (ρ = -0.45; p = 2.2 × 10-16), and the association was stronger among WGD ohnologues than orthologues. In S. salar and O. mykiss, lincRNA putative ohnologues showed weaker expression correlations than coding genes, suggesting widespread regulatory divergence, possibly through neo- and subfunctionalisation. Conserved salmonid lincRNAs showed enriched predicted interactions with miRNAs involved in tumour suppression, brain, bone, and muscle development (e.g., miR-455, miR-365, miR124, miR-133a, miR-140, and miR-9), a finding supported by limited transcriptomic data. Although salmonid WGD expanded lincRNA repertoires, lincRNAs have undergone rapid sequence and transcriptional divergence, with limited conservation across species based on sequence similarity, chromosomal position, synteny, and secondary structure. A subset of conserved lincRNAs retains structural features and regulatory signatures consistent with roles as miRNA sponges in brain, skeletal, and muscle development and tumour suppression, potentially acting within conserved regulatory networks. These findings provide new insights into lincRNA evolution following genome duplication and highlight the need for experimental validation of their regulatory functions.

Animals↗

PubMed2026

Deletion of the MALAT1 RNA 3' end promotes transcript decay and inhibits proliferation in gastric and breast cancer cells.

The long non-coding RNA MALAT1 is a conserved oncogenic driver whose function relies on a 3' triple-helix motif. While its biochemistry is well-characterized in vitro, the endogenous requirement for this motif in regulating the stability of the transcript and other genes residing in its locus remains unclear. In this study, we employed a dual-sgRNA CRISPR-Cas9 approach to systematically excise triple-helix-forming sequences from the native MALAT1 locus in gastric (AGS) and breast (MCF7) cancer cells. Our findings demonstrate that the 3' end strongly contributes to MALAT1 stability. Perturbations ranging from genomic deletions to a single-base changes trigger transcript collapse and rapid exonucleolytic decay, while the biogenesis of the small RNA mascRNA (a byproduct of MALAT1, also involved in cancer) remains decoupled and unaffected. In cellulo, DMS probing reveals that edited transcripts retain structural complexity in the 3' region. Phenotypically, structural disruption of the 3' end significantly impairs proliferation of both cancer cellular models. These results identify the 3' triple-helix as a determinant of MALAT1 stability and provide endogenous validation for its role in the analyzed AGS and MCF7 cells.

Cancer↗

PubMed2026

UFold-X: an enhanced Dual & Dynamic U-Mamba model for long-range RNA secondary structure prediction.

RNA secondary structure is essential for understanding the functions of non-coding RNAs, ribosomal RNAs, and viral genomes. However, accurate prediction of long RNA structures remains challenging due to complex long-range interactions and the limited availability of long-RNA training data. We present UFold-X, a dual-branch deep learning framework that combines a convolutional encoder for local structure modeling with a Mamba-based Visual State Space Module for capturing long-range dependencies. A dynamic gating mechanism adaptively integrates the two branches according to sequence length. UFold-X was evaluated on multiple benchmark datasets containing RNAs up to 5000 nucleotides. To rigorously assess generalization, we introduced a cross-clan benchmark for long RNAs. Under this stringent setting, UFold-X achieved performance comparable to state-of-the-art classical approaches while achieving the best performance among deep learning-based methods. Additional cross-family and within-family evaluations further demonstrated robust transferability and competitive predictive performance. UFold-X also maintained excellent computational efficiency, requiring only 0.08 s per sequence on average. To assess biological consistency, we developed a SHAPE-based reactivity prediction variant (UFold-X-R) and an integrated metric, the Hybrid Reactivity-Pairing Score (HRPS). UFold-X-R showed strong agreement with experimental icSHAPE data and achieved the highest HRPS among all evaluated methods. A user-friendly web server is available at https://ufold-x.ai4bread.com.

Nucleic Acid Conformation↗

PubMed2026

Epigenetic alterations induced by ionizing radiation: pathways to cancer and prognostic strategies.

PURPOSE: Ionizing radiation (IR) is widely used not only in cancer diagnosis and therapy, but its biological effects also extend beyond radiation-induced lethal lesions, e.g., specifically DNA double-strand breaks (DNA-DSBs). This review aims to summarize current evidence on IR-induced epigenetic alterations and to integrate mechanistic insights from radiation chemistry and radiation biology that link DNA damage to long-term epigenetic dysregulation. RESULTS: Experimental and clinical studies collectively show that IR induces persistent epigenetic reprogramming, including global and gene-specific DNA methylation changes, radiation-responsive histone modifications, chromatin remodeling, and dysregulation of non-coding RNAs. Aberrant RNA methylation, including modifications like N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), N7-methylguanine (m7G), and N3-methylcytosine (m3C), is closely linked to tumorigenesis and progression. Due to its tumor-specific properties, RNA methylation markers, specifically m6A, m5C, m1A, m7G, and m3C, emerge as valuable markers in liquid biopsy. Radiation chemistry studies indicate that epigenetically modified bases, for example, m5C, are preferential targets of radiation-induced oxidative damage, thereby promoting mutational hotspots and genomic instability. By altering DNA repair, apoptosis, immune responses, and cellular differentiation, these epigenetic changes promote carcinogenesis, radioresistance, and tissue toxicity. CONCLUSION: IR-induced epigenetic alterations represent a critical interface between initial DNA damage and long-term biological outcomes. Improved understanding of radiation-associated epigenetic signatures may enhance risk assessment, inform prognostic stratification, and support the development of epigenetic-targeted strategies to optimize radiotherapy and reduce adverse effects.

Ionizing radiation↗

PubMed2026

New insights on Plasmodium gene expression from direct RNA sequencing.

Oxford Nanopore Technology (ONT) direct RNA sequencing enables the sequencing of native RNA molecules without cDNA conversion. The long-read approach captures full-length reads spanning entire genes and has transformed the study of gene expression in Plasmodium parasites by enabling analysis of untranslated regions, isoforms, and alternative splicing. In addition, ONT provides unique insights into non-coding RNAs, RNA modifications, and polyadenylated tail dynamics, which are expanding our understanding of post-transcriptional regulation in Plasmodium, including processes beyond translational repression in gametocytes and sporozoites. Here, we discuss the past and future applications of direct RNA sequencing in Plasmodium research and highlight its advantages, limitations, and future prospects.

Oxford Nanopore Technology↗

PubMed2026

Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.

Fusion transcripts are hybrid RNA molecules generated through genomic rearrangements or RNA-level fusion mechanisms. They represent important molecular features of many cancers and can function as oncogenic drivers, diagnostic biomarkers, prognostic indicators, and therapeutic targets. Since the discovery of the BCR::ABL1 fusion in chronic myeloid leukemia, numerous cancer-associated fusion transcripts have been identified across hematologic malignancies and solid tumors. These fusion events encompass diverse biological mechanisms, including constitutively active kinases, aberrant transcription factors, epigenetic regulators, and non-coding fusion RNAs. This review summarizes current knowledge of the mechanisms underlying fusion transcript formation, including genomic rearrangement-dependent and rearrangement-independent processes, as well as fusion circular RNAs. The functional roles of fusion transcripts in cancer biology and their clinical relevance as diagnostic, prognostic, and predictive biomarkers are discussed. In addition, recent advances in fusion transcript detection and characterization are reviewed, including next-generation sequencing, long-read sequencing, single-cell approaches, artificial intelligence-assisted computational methods, and CRISPR/Cas9-mediated strategies for functional modeling and functional validation of fusion transcripts. Despite the rapid expansion of fusion transcript catalogs, the biological and clinical significance of most identified fusion events remains incompletely understood. Future progress will depend on integrating advanced sequencing technologies, artificial intelligence-assisted computational prioritization, and systematic functional validation to distinguish clinically actionable fusion transcripts from biologically neutral events. Such multidisciplinary approaches will be essential for translating fusion transcript research into precision oncology and improving cancer diagnosis, patient stratification, and targeted therapy.

Humans↗

PubMed2024

Whole transcriptome sequencing analyses of islets reveal ncRNA regulatory networks underlying impaired insulin secretion and increased β-cell mass in high fat diet-induced diabetes mellitus.

AIM: Our study aims to identify novel non-coding RNA-mRNA regulatory networks associated with β-cell dysfunction and compensatory responses in obesity-related diabetes. METHODS: Glucose metabolism, islet architecture and secretion, and insulin sensitivity were characterized in C57BL/6J mice fed on a 60% high-fat diet (HFD) or control for 24 weeks. Islets were isolated for whole transcriptome sequencing to identify differentially expressed (DE) mRNAs, miRNAs, IncRNAs, and circRNAs. Regulatory networks involving miRNA-mRNA, lncRNA-mRNA, and lncRNA-miRNA-mRNA were constructed and functions were assessed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. RESULTS: Despite compensatory hyperinsulinemia and a significant increase in β-cell mass with a slow rate of proliferation, HFD mice exhibited impaired glucose tolerance. In isolated islets, insulin secretion in response to glucose and palmitic acid deteriorated after 24 weeks of HFD. Whole transcriptomic sequencing identified a total of 1324 DE mRNAs, 14 DE miRNAs, 179 DE lncRNAs, and 680 DE circRNAs. Our transcriptomic dataset unveiled several core regulatory axes involved in the impaired insulin secretion in HFD mice, such as miR-6948-5p/Cacna1c, miR-6964-3p/Cacna1b, miR-3572-5p/Hk2, miR-3572-5p/Cckar and miR-677-5p/Camk2d. Additionally, proliferative and apoptotic targets, including miR-216a-3p/FKBP5, miR-670-3p/Foxo3, miR-677-5p/RIPK1, miR-802-3p/Smad2 and ENSMUST00000176781/Caspase9 possibly contribute to the increased β-cell mass in HFD islets. Furthermore, competing endogenous RNAs (ceRNA) regulatory network involving 7 DE miRNAs, 15 DE lncRNAs and 38 DE mRNAs might also participate in the development of HFD-induced diabetes. CONCLUSIONS: The comprehensive whole transcriptomic sequencing revealed novel non-coding RNA-mRNA regulatory networks associated with impaired insulin secretion and increased β-cell mass in obesity-related diabetes.

Mice↗

PubMed2026

ceRNA network of lncRNAs and mRNAs in OSF-to-OSCC progression: Diagnostic biomarkers and functional pathways.

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic potentially malignant disorder that can progress to oral squamous cell carcinoma (OSCC). Although dysregulated non-coding RNAs have been implicated in oral carcinogenesis, the competing endogenous RNA (ceRNA)-mediated regulatory mechanisms underlying OSF-to-OSCC progression remain poorly understood. This study aimed to identify candidate regulatory molecules and construct a putative lncRNA-miRNA-mRNA network associated with malignant transformation. METHODS: Publicly available microarray datasets (GSE117973 and GSE125866) were analyzed to identify differentially expressed genes between OSF and OSCC. Differentially expressed transcripts were classified into mRNAs and lncRNAs based on public transcript annotations. Highly correlated lncRNA-mRNA pairs were identified using Pearson correlation analysis and integrated with multiMiR-supported miRNA-mRNA interactions obtained from public databases to construct a putative ceRNA regulatory network. Functional characterization focused on apoptosis, epithelial-mesenchymal transition (EMT), and immune checkpoint-related pathways. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic performance, and selected biomarkers were externally validated using The Cancer Genome Atlas (TCGA) OSCC cohort. RESULTS: Integrated transcriptomic analysis identified several dysregulated mRNAs and lncRNAs associated with OSF-to-OSCC progression. Network analysis highlighted TBC1D3B, RREB1, TEAD3, SREBF1, TMEM41B, FOXK2, and KIAA1958 as prominent hub genes within the putative regulatory network. Functional analyses demonstrated significant associations with apoptosis-, EMT-, and immune checkpoint-related genes, suggesting potential involvement in multiple biological processes contributing to malignant transformation. Several hub genes exhibited strong diagnostic performance, with ROC analysis yielding AUC values ranging from 0.891 to 1.000, indicating excellent discrimination between OSF and OSCC samples. External validation using TCGA further supported the relevance of the identified biomarkers in OSCC. CONCLUSIONS: This study provides a comprehensive transcriptomic framework describing putative lncRNA-miRNA-mRNA regulatory interactions associated with OSF progression to OSCC. The identified hub genes and regulatory networks represent candidate biomarkers for early detection and provide a foundation for future mechanistic and experimental validation. As the proposed ceRNA interactions are computationally inferred, further biological validation is required before clinical application.

RNA, Long Noncoding↗

PubMed2026

A Comparative Analysis of the Methylation Status of Non-Coding RNA Promoters in Fibroid and Matched Myometrium.

Uterine fibroids exhibit dysregulated expression of non-coding RNAs (ncRNAs), although the underlying mechanisms remain incompletely understood. We investigated promoter DNA methylation and its relationship with ncRNA expression in fibroids. Genomic DNA from eight paired fibroid and matched myometrial tissues was analyzed using MeDIP-chip to identify differentially methylated ncRNA promoters. Selected candidates were validated by methylation-specific PCR (MSP) in 16 paired samples, and transcript expression was assessed by qRT-PCR in 68-94 paired specimens. MeDIP-chip identified 538 lncRNAs and 61 miRNAs with differential promoter methylation, including 300 hypermethylated and 238 hypomethylated lncRNAs and 47 hypermethylated and 14 hypomethylated miRNAs. Promoter methylation was not significantly correlated with transcript expression (r = -0.1224). MSP confirmed hypermethylation of LINC-PINT and MIR9-3 and hypomethylation of WT1-AS and TTLL10-AS1. Correspondingly, LINC-PINT and MIR9-3 expression was decreased, whereas WT1-AS and TTLL10-AS1 expression was increased in fibroids. However, LINC-PINT and TTLL10-AS1 methylation did not fully correspond with MeDIP-chip findings. These results reveal widespread ncRNA promoter methylation alterations in uterine fibroids but demonstrate that genome-wide methylation does not consistently predict transcript expression, highlighting the complexity of ncRNA epigenetic regulation and the importance of locus-specific validation.

Humans↗

PubMed2025

Role of lncRNA PVT1 in the progression of urological cancers: Novel insights into signaling pathways and clinical opportunities.

Urologic malignancies, encompassing cancers of the kidney, bladder, and prostate, represent approximately 25 % of all cancer cases. Recent advances have enhanced our understanding of PVT1's crucial functions. Long noncoding RNAs influence both the onset and development of cancer, as well as epigenetic alterations. Recent findings have focused on PVT1's mechanism of action across several malignancies, particularly urologic cancers. Understanding the various functions of PVT1 linked to cancer is necessary for the development of cancer detection and treatment when PVT1 is dysregulated. Furthermore, recent advancements in genomic and epigenetic research have elucidated the complex regulatory networks that control PVT1 expression. Comprehending the intricate role of PVT1 Understanding the complex function of PVT1 in urologic cancers has substantial clinical implications. Here, we summarize some of the most recent findings about the carcinogenic effects of PVT1 signaling pathways and the possible treatment strategies for urological malignancies that target these pathways.

Humans↗