SEARCH · Search PubMed

Results for “LncRNAs”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

PubMed2024

Expression profile of long noncoding RNAs and comprehensive analysis of lncRNA-cisTF-DGE regulation in condyloma acuminatum.

OBJECTIVE: To identify differentially expressed long noncoding RNAs (lncRNAs) in condyloma acuminatum (CA) and to explore their probable regulatory mechanisms by establishing coexpression networks. METHODS: High-throughput RNA sequencing was performed to assess genome-wide lncRNA expression in CA and paired adjacent mucosal tissue. The expression of candidate lncRNAs and their target genes in larger CA specimens was validated using real-time quantitative reverse transcriptase polymerase chain reaction (RT‒qPCR). Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for the functional enrichment analysis of these candidate lncRNAs and differential mRNAs. The coexpressed mRNAs of the candidate lncRNAs, calculated by Pearson's correlation coefficient, were also analysed using GO and KEGG analysis. In addition, the interactions among differentially expressed lncRNAs (DElncRNAs)-cis-regulatory transcription factors (cisTFs)-differentially expressed genes (DEGs) were analysed and their network was constructed. RESULTS: A total of 546 lncRNAs and 2553 mRNAs were found to be differentially expressed in CA compared to the paired control. Functional enrichment analysis revealed that the DEGs coexpressed with DElncRNAs were enriched in the terms of cell adhesion and keratinocyte differentiation, and the pathways of ECM-receptor interaction, local adhesion, PI3K/AKT and TGF-ß signaling. We further constructed the network among DElncRNAs-cisTFs-DEGs and found that these 95 DEGs were mainly enriched in GO terms of epithelial development, regulation of transcription or gene expression. Furthermore, the expression of 3 pairs of DElncRNAs and cisTFs, EVX1-AS and HOXA13, HOXA11-AS and EVX1, and DLX6-AS and DLX5, was validated with a larger number of specimens using RT‒qPCR. CONCLUSION: CA has a specific lncRNA profile, and the differentially expressed lncRNAs play regulatory roles in mRNA expression through cis-acting TFs, which provides insight into their regulatory networks. It will be useful to understand the pathogenesis of CA to provide new directions for the prevention, clinical treatment and efficacy evaluation of CA.

RNA, Long Noncoding↗

PubMed2026

Long non-coding RNAs link DNA methylation to immune regulatory networks in bovine subclinical mastitis.

Long non-coding RNAs (lncRNAs) are emerging as important regulators of inflammatory and immune signaling, yet their contribution to bovine subclinical mastitis remains poorly defined. Here, we characterized the lncRNA expression landscape associated with disease in milk somatic cells of healthy and subclinical mastitic Vrindavani cattle. We identified 11,403 high-confidence lncRNAs, of which 104 were differentially expressed in subclinical mastitis (adjusted P < 0.05; |log2FC| ≥ 1), with the vast majority upregulated in mastitic samples. Predicted cis- and trans-associated target analyses identified 637 non-redundant genes, and KEGG analysis identified 8 significantly enriched cis-associated pathways and 152 significantly enriched trans-associated pathways (adjusted P < 0.05), predominantly enriched for immune and inflammation-related pathways. These findings prioritized a subset of mastitis-associated lncRNAs for subsequent methylation and interaction-network analyses. A subset of these lncRNAs further overlapped differentially methylated regions (DMRs), suggesting a potential association between lncRNA expression changes and DNA methylation alterations. Integration of lncRNA-miRNA and miRNA-mRNA interactions identified lncRNA-miRNA-mRNA interaction networks involving DMR-associated lncRNAs. Among the prioritized candidates, MSTRG.28878.1 showed overlap with a hypomethylated promoter-associated DMR, increased expression, and multiple connections within the predicted interaction network. Together, these findings identify candidate lncRNAs, methylation-associated loci, and predicted molecular interactions associated with bovine subclinical mastitis and provide a resource for future functional investigation of candidate non-coding RNA-associated mechanisms in disease.

Animals↗

PubMed2025

Expression analysis of LINC00671 and LINC01913 long non-coding RNAs in gastric cancer patients and their correlation with EMT markers.

BACKGROUND: Long-chain non-coding RNAs (lncRNAs) play various roles in the regulation of gene expression at the levels of transcription and translation, and epigenetic modification. Dysregulation of lncRNAs is associated with various malignancies, including cancer. lncRNAs have been demonstrated to regulate critical biological processes in cancer cells, such as apoptosis, proliferation, migration, and invasion. They also play essential roles in the development of gastric cancer (GC). However, the clinical significance and biological function of many lncRNAs remain unexplored in GC progression. This study aimed to evaluate the expression profiles of LINC00671 and LINC01913 in GC patients and investigate their correlation with epithelial-to-mesenchymal transition (EMT) markers. METHOD: The real-time PCR technique was applied to measure the expression levels of the selected lncRNAs (LINC01913 and LINC00671) and EMT-related mRNAs (MAMLs and MMP-13) in 83 tumor and adjacent normal tissues obtained from GC patients. RESULT: A significant reduction in LINC00671 expression was observed in 55.4% of tumor tissues, while elevated expression of LINC01913 (41%), MMP13 (56.6%), and MAML1 (44.6%) was detected, representing the proportion of samples with dysregulated expression relative to matched normal tissues. Dysregulation of these genes was significantly associated with various clinicopathological features (P < 0.05), supporting a potential link between these lncRNAs and EMT processes in GC. CONCLUSION: The observed associations between LINC00671, LINC01913, and EMT-related genes suggest their potential as prognostic biomarkers for treatment response in GC patients.

Humans↗

PubMed2024

CRISPRi screens identify the lncRNA, LOUP, as a multifunctional locus regulating macrophage differentiation and inflammatory signaling.

Long noncoding RNAs (lncRNAs) account for the largest portion of RNA from the transcriptome, yet most of their functions remain unknown. Here, we performed two independent high-throughput CRISPRi screens to understand the role of lncRNAs in monocyte function and differentiation. The first was a reporter-based screen to identify lncRNAs that regulate TLR4-NFkB signaling in human monocytes and the second screen identified lncRNAs involved in monocyte to macrophage differentiation. We successfully identified numerous noncoding and protein-coding genes that can positively or negatively regulate inflammation and differentiation. To understand the functional roles of lncRNAs in both processes, we chose to further study the lncRNA LOUP [lncRNA originating from upstream regulatory element of SPI1 (also known as PU.1)], as it emerged as a top hit in both screens. Not only does LOUP regulate its neighboring gene, the myeloid fate-determining factor SPI1, thereby affecting monocyte to macrophage differentiation, but knockdown of LOUP leads to a broad upregulation of NFkB-targeted genes at baseline and upon TLR4-NFkB activation. LOUP also harbors three small open reading frames capable of being translated and are responsible for LOUP's ability to negatively regulate TLR4/NFkB signaling. This work emphasizes the value of high-throughput screening to rapidly identify functional lncRNAs in the innate immune system.

RNA, Long Noncoding↗

PubMed2025

Genome imbalance modulates the expression of long non-coding RNAs in maize.

Genome imbalance, resulting from varying the dosage of individual chromosomes (aneuploidy), has a more detrimental effect than changes in complete sets of chromosomes (haploidy/polyploidy). This imbalance is likely due to disruptions in stoichiometry and interactions among macromolecular assemblies. Previous research has shown that aneuploidy causes global modulation of protein-coding genes (PCGs), microRNAs, and transposable elements (TEs), affecting both the varied chromosome (cis-located) and unvaried genome regions (trans-located) across various taxa. While long non-coding RNAs (lncRNAs) are important gene expression regulators, their roles in the context of genomic imbalance remain largely unexplored. In this study, we analyzed and compared the impact of aneuploidy and haploidy/polyploidy on lncRNA expression using RNA-seq data from maize mature leaf tissue. Our results indicate that cis-located lncRNAs are modulated from dosage compensation to a gene dosage effect, while trans-located lncRNAs exhibit trends ranging from an inverse effect to a positive correlation with chromosomal dosage. Remarkably, the ploidy series showed a lesser degree of lncRNA modulation. LncRNAs and TEs display a similar trend of inverse modulation but exhibit greater sensitivity to dosage changes compared to PCGs. The construction of cis-acting and trans-acting lncRNA co-expression networks indicates that lncRNAs likely function as dosage-sensitive regulators of gene expression under conditions of genomic imbalance. Overall, this study not only elucidates the dosage effect of plant lncRNAs but also serves as a valuable resource for exploring potential regulators of PCGs that play significant biological functions.

Zea mays↗

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

Overexpression of a subset of long intergenic noncoding RNAs in uterine serous carcinoma predicts poor prognosis.

The evaluation and prediction of uterine serous carcinoma (USC), a type of endometrial cancer that is more severe than endometrioid adenocarcinoma, remain challenging. Long noncoding RNAs (lncRNAs) are frequently dysregulated in human cancers. This study assessed the expression patterns and prognostic values of long intergenic noncoding RNAs (lincRNAs) in USC. RNA sequencing, copy number variation (CNV), and clinical data from The Cancer Genome Atlas were used to investigate various lncRNAs in endometrial cancer. LincRNAs, a major subclass of lncRNAs, exhibit specific expression patterns modulated by CNVs and act as predictors of poor prognosis, survival, and recurrence in USC. Functional analyses were conducted to investigate the roles of lncRNAs in USC. Finally, the expression of these lincRNAs was verified in 32 pairs of USCs collected from the hospital over 3 years. A series of lincRNAs were found to be specifically expressed in USC compared with other lncRNAs and regulated by CNV. Moreover, these specific upregulated lincRNAs, particularly ENSG00000281406, ENSG00000226791, ENSG00000269903, and ENSG00000204277, demonstrated poor prognoses for survival and recurrence in USC. Functionally, our analysis showed that ENSG00000281406 positively correlated with the Wnt signaling pathway, whereas ENSG00000226791, ENSG00000269903, and ENSG00000204277 negatively correlated with the T-cell receptor signaling pathway. Importantly, we confirmed that ENSG00000204277 negatively correlated with CD8+ T-cell immune infiltration in USC. Our results highlight that these lincRNAs can serve as new biomarkers for the prognostic prediction of USC. In particular, ENSG00000204277 may be used as a therapeutic target for USC.

Humans↗

PubMed2026

Comparative transcriptome analysis of Qinchuan and Wagyu cattle reveals lnc11599 as a negative regulator of intramuscular fat deposition.

BACKGROUND: Intramuscular fat (IMF) content is a critical factor determining beef quality, influenced by various factors including breed and age. However, the regulatory role of long non-coding RNAs (lncRNAs) in IMF deposition remains unclear. METHODS: This study investigated IMF deposition in the longissimus dorsi muscle of one- and two-year-old Qinchuan and Wagyu cattle through histological examination and fat content measurement. Based on transcriptome sequencing data of intramuscular fat tissue, differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify lncRNAs associated with IMF deposition. The effects of a key candidate lncRNA on the adipogenic differentiation of cattle intramuscular preadipocytes were further examined. RESULTS: Results showed that Wagyu cattle exhibited stronger IMF deposition capacity than Qinchuan cattle across all age groups, with IMF content increasing with age in both breeds. We identified 7,910 lncRNAs from intramuscular fat tissue transcriptome data, including 6,455 novel lncRNAs. Through integrated differential expression analysis and WGCNA, 88 lncRNAs closely associated with IMF deposition were screened from two-year-old Qinchuan and Wagyu cattle. Notably, lnc11599 was significantly upregulated in Qinchuan cattle intramuscular fat tissue, but its expression decreased during intramuscular preadipocyte differentiation. Functional experiments demonstrated that lnc11599 knockdown enhanced adipogenic differentiation capacity, manifested as a highly significant increase in lipid accumulation, upregulation of key adipogenic genes at the mRNA level, together with increases in total fatty acid content and unsaturated fatty acid proportion. CONCLUSIONS: This study established the lncRNA expression profiles in intramuscular fat tissue of Qinchuan and Wagyu cattle across different developmental stages, and demonstrated that lnc11599 acts as a negative regulator of intramuscular fat deposition. These findings provide new directions for elucidating the mechanisms of cattle IMF deposition and offer potential targets for genetic improvement of beef quality.

Animals↗

PubMed2025

LncRNA Profiling and ceRNA Network Construction of Intrauterine Exosomes in Goats During Embryo Implantation.

Exosomes have been shown to play an important role in embryo implantation, but the mechanism is still unclear. This study aimed to investigate the functional roles of lncRNAs in intrauterine exosomes in goat pregnancy. We used RNA-seq to identify the lncRNA profiles of exosomes obtained from goat uterine rinsing fluid at 5, 15, and 18 days of gestation. In addition, we performed weighted gene co-expression network analysis based on differentially expressed mRNAs (DEMs) and lncRNAs (DELs). Functional enrichment analyses of gene modules were conducted using Gene Ontology classification (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. A lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory network was constructed based on predictive interaction derived from miRTarBase, miRDB and RNAhybrid databases. Altogether, 831 DELs were identified. GO and KEGG analysis showed that the target genes were enriched in processes associated with embryo implantation, such as signaling receptor activity, binding and immune response. Nine functional co-expression modules were enriched in various biological processes, such as metabolic pathways, protein transport, cell cycle and VEGF signaling pathway. Additionally, 12 lncRNA-mediated ceRNA networks were constructed. Our results demonstrate that exosomal lncRNAs in uterine flushing fluid exhibit dynamic changes across gestational stages and play an important role in regulating the uterine microenvironment during embryo implantation. These findings provide a foundational basis for screening exosome-derived lncRNAs that influence embryo implantation and contribute to elucidating the mechanistic roles of lncRNAs in exosome-mediated processes during early pregnancy.

embryo implantation↗

PubMed2026

Whole-transcriptome RNA sequencing and ceRNA network analyses provide novel insights into the antibacterial immune response of Hippocampus abdominalis against Vibrio harveyi.

Long non-coding RNAs (lncRNAs) stand as newly-arisen molecular types that exert regulatory effects, able to operate as competitive endogenous RNAs (ceRNAs) to engage microRNAs (miRNAs) in interaction, resulting in the recovery of target mRNA expression and activity. Increasing evidences indicate that the ceRNA network affects various biological processes in mammals, including development, cellular differentiation, metabolism, immune response, and disease pathogenesis. In teleost fish, the lncRNA-miRNA-mRNA regulatory networks have been reported occasionally. However, up to now, the roles of lncRNAs in the big-belly seahorse (Hippocampus abdominalis) remains unclear. In this study, we reported for the first time, via whole-transcriptome RNA sequencing, the lncRNA mediated ceRNA regulatory network in Vibrio harveyi-infected H. abdominalis. A total of 4197 differentially expressed mRNAs (DE-mRNAs), 1317 DE-lncRNAs, and 183 DE-miRNAs were identified. Furthermore, the crosstalk between miRNAs and lncRNAs as well as between miRNAs and mRNAs was inferred based on the negative correlations between miRNAs and their target lncRNAs/mRNAs. A core immune associated lncRNA-miRNA-mRNA putative regulatory network was thus constructed, comprising 211 lncRNA-miRNA and 224 mRNA-miRNA pairs. In conclusion, our findings provide an integrative overview of the ceRNA regulatory networks on the underlying immune responses to V. harveyi infection in the big-belly seahorse, and offer a solid theoretical foundation for the comparative immunological research of teleost fish.

Animals↗

PubMed2025

In Vivo CRISPR Interference Screen Reveals Long Noncoding RNA Portfolio Crucial for Cutaneous Squamous Cell Carcinoma Tumor Growth.

Cutaneous squamous cell carcinoma (cSCC) accounts for 20% of all skin cancer mortality globally, making it the second-highest subtype of skin cancer. The high prevalence of cSCC in humans highlights the need to uncover alternative actors and mechanisms influencing skin cancer development. Significant advances have been made to better understand some key factors in cSCC growth. However, little is known about the role of noncoding RNAs, particularly of a specific subclass termed long noncoding RNA (lncRNA). By performing pseudobulk analysis of single-cell sequencing data from normal and cSCC human skin tissues, we determined a global portfolio of lncRNAs specifically expressed in keratinocyte subpopulations. Integration of CRISPR interference screens in vitro and the xenograft model identified several lncRNAs impacting the growth of cSCC cancer lines both in vitro and in vivo. Among these, we further validated LINC00704 and LINC01116 as proliferation-regulating lncRNAs in cSCC lines and potential biomarkers of cSCC growth. Taken together, our study provides a comprehensive signature of lncRNAs with roles in regulating cSCC growth.

RNA, Long Noncoding↗

PubMed2026

Differentiation-independent activation of HPV genome replication by the lncRNA DINO.

Human papillomaviruses (HPVs) rely on multiple host cell factors to replicate the viral genome, yet the contribution of host long non-coding RNAs (lncRNAs) to viral genome maintenance and amplification in the productive life cycle remains poorly understood. In this study, we show that the lncRNA damage-induced long non-coding RNA (DINO) is a driver of HPV DNA replication. DINO levels increase during keratinocyte differentiation, and ectopic expression of DINO promotes both HPV genome replication and the formation of replication foci, and this is independent of keratinocyte differentiation signals. Ectopic DINO expression increases select early viral transcript levels, including E1^E4, E1, and E2. Notably, DINO's subcellular localization is also context-dependent: during DNA damage, DINO is predominantly cytoplasmic, but during keratinocyte differentiation, nuclear retention is observed. This differential localization suggests that DINO has distinct functional roles in keratinocyte differentiation and HPV biology. Our findings highlight DINO as a lncRNA that promotes HPV genome replication and suggest that lncRNAs may play underappreciated roles in host-virus interactions. This work provides a foundation for further exploration of lncRNAs as potential therapeutic targets in HPV-associated diseases.IMPORTANCEHuman papillomaviruses (HPVs) are the causative agents of many anogenital tract and oral cancers, yet the host factors that trigger and support viral genome replication during the productive life cycle are incompletely understood. This study identifies the long non-coding RNA DINO as a host regulator that promotes HPV DNA replication, replication focus formation, and early viral gene expression independently of keratinocyte differentiation. We further show that DINO exhibits context-dependent subcellular localization, suggesting distinct functional roles in cellular stress responses and HPV biology. These findings reveal an underappreciated role for host lncRNAs in virus-host interactions and provide new insight into cellular pathways that support HPV genome replication.

Virus Replication↗

PubMed2026

Identification of a necroptosis-related lncRNA prognostic signature and the hub RBP HNRNPK in esophageal squamous cell carcinoma.

ObjectiveEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with poor prognosis. Necroptosis is important for tumor immunity, but its role in ESCC remains unclear. This retrospective bioinformatics study aimed to investigate the prognostic value of necroptosis-related long non-coding RNAs (lncRNAs) and to identify key lncRNA-binding proteins (RBPs) in ESCC patients.MethodsRNA transcriptome and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Necroptosis-related lncRNAs were identified through correlation analysis with necroptosis-related genes, subjected to consensus cluster analysis, and used to construct a prognostic risk model via least absolute shrinkage and selection operator (LASSO) regression. The hub RBP was experimentally validated by quantitative polymerase chain reaction (qPCR) using 30 pairs of ESCC and adjacent normal tissues from patients who underwent surgical resection.ResultsA total of 30 necroptosis-related lncRNAs were significantly correlated with overall survival (OS). The upregulated lncRNAs in the risk model were associated with high immune scores, innate immune cell infiltration, cluster 2 classification, and advanced T-stage disease (p < 0.05). Three hub RBPs (HNRNPA1, HNRNPC, and HNRNPK) were identified through protein-protein interaction network analysis. qPCR confirmed that HNRNPK was significantly overexpressed in ESCC tissues compared to adjacent normal tissues (p < 0.05).ConclusionsThe necroptosis-related lncRNA risk model is an independent prognostic factor for ESCC patients. HNRNPK was identified as a hub RBP significantly overexpressed in ESCC tissues. We hypothesize that HNRNPK may promote tumor progression through regulating proto-oncogene expression or modulating the immune microenvironment, though this requires further mechanistic validation.

Humans↗

PubMed2024

Transcriptome-wide N6-methyladenosine modification profiling of long non-coding RNAs in patients with recurrent implantation failure.

N6-methyladenosine (m6A) is involved in most biological processes and actively participates in the regulation of reproduction. According to recent research, long non-coding RNAs (lncRNAs) and their m6A modifications are involved in reproductive diseases. In the present study, using m6A-modified RNA immunoprecipitation sequencing (m6A-seq), we established the m6A methylation transcription profiles in patients with recurrent implantation failure (RIF) for the first time. There were 1443 significantly upregulated m6A peaks and 425 significantly downregulated m6A peaks in RIF. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that genes associated with differentially methylated lncRNAs are involved in the p53 signalling pathway and amino acid metabolism. The competing endogenous RNA network revealed a regulatory relationship between lncRNAs, microRNAs and messenger RNAs. We verified the m6A methylation abundances of lncRNAs by using m6A-RNA immunoprecipitation (MeRIP)-real-time polymerase chain reaction. This study lays a foundation for further exploration of the potential role of m6A modification in the pathogenesis of RIF.

Humans↗

PubMed2026

LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.

Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.

Humans↗

PubMed2025

Expression of long noncoding RNAs in peripheral blood mononuclear cells of patients with type 1 diabetes mellitus: potential biomarkers for disease onset.

OBJECTIVE: Long non-coding RNAs (lncRNAs) do not encode proteins and are transcripts longer than 200 nucleotides. The precise involvement of lncRNAs in type 1 diabetes mellitus (T1DM) pathogenesis remains unclear. Therefore, this study aimed to analyze the expressions of five lncRNAs in peripheral blood mononuclear cells of individuals with T1DM and without DM. MATERIALS AND METHODS: This study comprised 27 patients with T1DM (cases) and 13 individuals without DM (controls). The case group was divided into two subgroups based on T1DM duration: < 5 years of diagnosis group and long-term diabetes group (≥5 years). LncRNA expression was evaluated by qPCR. RESULTS: MALAT1 and TUG1 were upregulated in patients within the first five years of diagnosis of T1DM compared to the other groups. MEG3 was upregulated in the case group of < 5 years of diagnosis compared to controls. TUG1 and MALAT1 levels were negatively correlated with the duration of T1DM, while TUG1 and MEG3 were positively correlated with glycated hemoglobin levels. Bioinformatics analysis revealed that MALAT1, MEG3, and TUG1 regulate and interact with protein-codifying genes and microRNAs involved in T1DM-related pathways. CONCLUSION: Our study revealed MALAT1, MEG3, and TUG1 upregulation in patients within the first five years of diagnosis of T1DM.

Humans↗

PubMed2026

Comparative transcriptome analysis reveals ncRNA-mediated regulatory networks associated with muscle crispiness in grass carp.

Non-coding RNAs (ncRNAs) have been demonstrated to be involved in muscle development and to function as key regulators. However, the molecular mechanism underlying muscle crispiness in grass carp (GC) remains poorly understood, and whether these ncRNAs are involved in its regulation is still unknown. In the current investigation, differentially expressed (DE) RNAs (including lncRNAs, circRNAs, miRNAs, and mRNAs) were identified; concomitantly, target genes prediction was conducted, and functional and signaling pathway enrichment analyses were performed. Pathways related to muscle crispiness were identified, and the competitive endogenous RNA (ceRNA) (lncRNA/circRNA-miRNA-mRNA) regulatory network was further constructed. The results showed that a total of 126 DE-lncRNAs, 17 DE-circRNAs, 329 DE-miRNAs, and 442 DE-mRNAs were identified in muscle tissues of both the GC and crisp grass carp (CGC). GO and KEGG enrichment analyses revealed that target genes of DE-ncRNAs were significantly enriched in signaling pathways, including structural constituents of muscle, apoptosis, oxidative phosphorylation, and regulation of actin cytoskeleton, suggesting that these pathways may be involved in muscle texture remodeling. Subsequently, DE-RNAs enriched in related pathways were identified, and a core ceRNA regulation network comprising 3 lncRNAs, 4 circRNAs, 3 miRNAs, and 17 mRNAs was constructed. Additionally, 10 DE-RNAs from randomly selected groups were validated by qRT-PCR. Our findings not only provide scientific evidence elucidating the molecular mechanisms underlying muscle crispiness in GC but also establish a foundation for studying changes in muscle textural qualities across other fish species.

Animals↗

PubMed2026

HyLnc: a hybrid deep learning and feature-based approach for long non-coding RNA prediction.

Long non-coding RNAs (lncRNAs) play important roles in gene regulation, development and disease, yet accurate identification of lncRNAs from transcriptomic data remains a major computational challenge. Existing methods often rely either on handcrafted sequence features or deep learning approaches, each with their inherent limitations in capturing the full complexity of RNA sequences. In this study, we proposed HyLnc, a computational framework that integrates transformer-based contextual embeddings with biologically meaningful sequence features for improved lncRNA prediction. A custom BERT-based model was first pre-trained on a large corpus of metazoan RNA sequences using a masked language modelling strategy to learn contextual nucleotide dependencies. The model was subsequently fine-tuned on curated datasets of lncRNAs and protein-coding transcripts and 256-dimensional deep sequence embeddings were extracted. Parallelly, 348 handcrafted features, including ORF characteristics, untranslated region (UTR) properties, nucleotide composition and Fickett scores, were computed. A multi-stage feature selection strategy was applied to identify the most informative features, resulting in optimized hybrid feature sets. Multiple machine learning classifiers were evaluated, with the RF model achieving the best performance. The proposed framework attained an accuracy of 91.30%, F1-score of 91.23% and MCC of 82.60 on an independent validation dataset, outperforming several existing lncRNA prediction tools. Thus, HyLnc demonstrates that integrating deep contextual representations with biologically interpretable features enhances lncRNA prediction. This approach provides a robust and scalable solution for large-scale transcriptome annotation and can be extended to other sequence-based prediction.

RNA, Long Noncoding↗