Genome-wide analysis of long noncoding RNA stability

Tracing the dynamic changes in the lncRNA-mediated competing endogenous RNA network during bovine preimplantation embryo development

Long noncoding RNAs (lncRNAs) can regulate gene expression by "sponging" microRNAs (miRNAs), reducing their inhibitory effects on mRNAs. However, this mechanism has been minimally investigated in preimplantation embryo development. In this study, we revisited existing RNA sequencing and small RNA sequencing data to investigate the role of lncRNAs in in vitro-produced bovine preimplantation embryos. Our findings revealed that although lncRNAs exhibit expression patterns similar to mRNAs, maternal lncRNAs degrade earlier than mRNAs during embryonic genome activation (EGA). Weighted gene co-expression network analysis identified 27 modules of mRNA and lncRNA, with enrichment analysis showing a significant negative correlation between the polycomb repressive complex pathway and blastocyst formation (R2 = -0.98). Additionally, bioinformatics analysis was used to predict and construct lncRNA-miRNA-mRNA networks, highlighting that lncRNAs bind more to miRNAs compared with mRNAs. Moreover, lncRNA-induced lncRNA-miRNA-mRNA axes participated in mRNA degradation and biogenesis around the EGA stage. These interactions became stronger after EGA, especially after the 16-cell stage. Overall, our study provides new insights into lncRNA-mediated regulatory networks during bovine preimplantation development.

POCALI: Prediction and Insight on CAncer LncRNAs by Integrating Multi-Omics Data with Machine Learning

Long non-coding RNAs (lncRNAs) are receiving increasing attention as biomarkers for cancer diagnosis and therapy. Although there are many computational methods to identify cancer lncRNAs, they do not comprehensively integrate multi-omics features for predictions or systematically evaluate the contribution of each omics to the multifaceted landscape of cancer lncRNAs. In this study, an algorithm, POCALI, is developed to identify cancer lncRNAs by integrating 44 omics features across six categories. The contributions of different omics are explored to identifying cancer lncRNAs and, more specifically, how each feature contributes to a single prediction. The model is evaluated and benchmarked POCALI with existing methods. Finally, the cancer phenotype and genomics characteristics of the predicted novel cancer lncRNAs are validated. POCALI identifies secondary structure and gene expression-related features as strong predictors of cancer lncRNAs, and epigenomic features as moderate predictors. POCALI performed better than other methods, especially in terms of sensitivity, and predicted more candidates. Novel POCALI-predicted cancer lncRNAs have strong relationships with cancer phenotypes, similar to known cancer lncRNAs. Overall, this study facilitates the identification of previously undetected cancer lncRNAs and the comprehensive exploration of the multifaceted feature contributions to cancer lncRNA prediction.

Non-coding RNAs, a double-edged sword in breast cancer prognosis

Cancer is a rising issue worldwide, and numerous studies have focused on understanding the underlying reasons for its occurrence and finding proper ways to defeat it. By applying technological advances, researchers are continuously uncovering and updating treatments in cancer therapy. Their vast functions in the regulation of cell growth and proliferation and their significant role in the progression of diseases, including cancer. This review provides a comprehensive analysis of ncRNAs in breast cancer, focusing on long non-coding RNAs such as HOTAIR, MALAT1, and NEAT1, as well as microRNAs such as miR-21, miR-221/222, and miR-155. These ncRNAs are pivotal in regulating cell proliferation, metastasis, drug resistance, and apoptosis. Additionally, we discuss experimental approaches that are useful for studying them and highlight the advantages and challenges of each method. We then explain the results of these clinical trials and offer insights for future studies by discussing major existing gaps. On the basis of an extensive number of studies, this review provides valuable insights into the potential of ncRNAs in cancer therapy. Key findings show that even though the functions of ncRNAs are vast and undeniable in cancer, there are still complications associated with their therapeutic use. Moreover, there is an absence of sufficient experiments regarding their application in mouse models, which is an area to work on. By emphasizing the crucial role of ncRNAs, this review underscores the need for innovative approaches and further studies to explore their potential in cancer therapy.

LncRNA H19 promotes osteoclast differentiation by sponging miR-29c-3p to increase expression of cathepsin K

BACKGROUND

Osteoporosis is a prevalent metabolic bone disease. Osteoporotic fractures can lead to severe functional impairment and increased mortality. Long noncoding RNA H19 has emerged as a pivotal player in bone remodeling, serving both as a biomarker and a regulator. While previous research has elucidated H19's role in promoting osteogenic differentiation through diverse mechanisms, its involvement in osteoclast differentiation remains largely unknown.

METHODS

In this study, we used lentiviral vectors to stably overexpress or knockdown H19 in RAW264.7 cell lines. Quantitative reverse polymerase chain reaction, Western blot, tartrate resistant acid phosphatase staining and bone resorption assay were performed to assess the level of osteoclast differentiation and bone resorption capacity. And fluorescence in situ hybridization, dual-luciferase reporter and RNA immunoprecipitation were used to explore the specific mechanism of H19 regulating osteoclast differentiation in vitro. Then, ovariectomized osteoporosis models in wild type mice and H19 knockout mice were conducted. And micro-CT analysis, HE staining, and immunohistochemistry were performed to verify the mechanism of H19 regulating osteoclast differentiation in vivo. Bone marrow derived monocytes and bone mesenchymal stem cells were extracted from mice and assayed for osteoclastic and osteogenic-related assays, respectively.

RESULTS

In vitro, H19 promoted osteoclast differentiation and bone resorption of RAW264.7 cells, while miR-29c-3p inhibited them. Both H19 and cathepsin K were the target genes of miR-29c-3p. In vivo, H19 knockout mice have increased femur bone mineral density, decreased osteoclast formation, and reduced cathepsin K expression. MiR-29c-3p agomir could increase bone mineral density in osteoporotic mice on the premise of H19 knockout.

CONCLUSIONS

H19 upregulates cathepsin K expression through sponging miR-29c-3p, which promoting osteoclast differentiation and enhancing bone resorption. This underscores the potential of H19 and miR-29c-3p as promising biomarkers for osteoporosis.

Cell death-associated lncRNAs in cancer immunopathogenesis: An exploration of molecular mechanisms and signaling pathways

Cancer remains one of the foremost causes of mortality worldwide, highlighting the urgent need for novel therapeutic targets due to the insufficient efficacy and adverse side effects associated with existing cancer treatments. Long non-coding RNAs (lncRNAs), defined as RNA transcripts longer than 200 nucleotides, have emerged as pivotal regulators in the initiation and progression of various malignancies. In oncology, programmed cell death (PCD) serves as the primary mechanism for tumor cell elimination, comprising processes such as apoptosis, pyroptosis, autophagy, and ferroptosis. Recent studies have elucidated a substantial relationship between lncRNAs and these PCD pathways, indicating that lncRNAs can modulate the apoptotic and non-apoptotic death mechanisms. This regulation may influence not only the dynamics of cancer progression but also the therapeutic response to clinical interventions. This review delves into the intricate role of lncRNAs within the context of PCD in cancer, unveiling the underlying pathogenic mechanisms while proposing innovative strategies for cancer therapy. Additionally, it discusses the potential therapeutic implications of targeting lncRNAs in PCD and related signaling pathways, aiming to enhance treatment outcomes for patients facing cancer.

Construction of an lncRNA-mediated ceRNA network to investigate the inflammatory regulatory mechanisms of ischemic stroke

Long non-coding RNAs (lncRNAs) are among the most abundant types of non-coding RNAs in the genome and exhibit particularly high expression levels in the brain, where they play crucial roles in various neurophysiological and neuropathological processes. Although ischemic stroke is a complex multifactorial disease, the involvement of brain-derived lncRNAs in its intricate regulatory networks remains inadequately understood. In this study, we established a cerebral ischemia-reperfusion injury model using middle cerebral artery occlusion (MCAO) in male Sprague-Dawley rats. High-throughput sequencing was performed to profile the expression of cortical lncRNAs post-stroke, with subsequent validation using RT-PCR and qRT-PCR. Among the 31,183 lncRNAs detected in the rat cerebral cortex, 551 were differentially expressed between the MCAO and sham-operated groups in the ipsilateral cortex (fold change ≥2.0, P < 0.05). An integrated analysis of the 20 most abundant and significantly differentially expressed lncRNAs (DELs) identified 25 core cytoplasmic DELs, which were used to construct an interaction network based on their targeting relationships. This led to the establishment of a comprehensive lncRNA-miRNA-mRNA regulatory network comprising 12 lncRNAs, 16 sponge miRNAs, and 191 target mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that differentially expressed mRNAs (DEmRNAs) were significantly enriched in stroke-related pathways. Our analysis predicted four key lncRNAs, four miRNAs, and eleven crucial mRNAs involved in post-transcriptional regulation through competing endogenous RNA (ceRNA) mechanisms. These molecules were shown to participate extensively in post-stroke processes, including angiogenesis, axonal regeneration, inflammatory responses, microglial activation, blood-brain barrier (BBB) disruption, apoptosis, autophagy, ferroptosis, and thrombocytopenia. These findings highlight the role of lncRNAs as multi-level regulators in the complex network of post-stroke mechanisms, providing novel insights into the pathophysiological processes of stroke.

Dysregulated Long Non-coding RNAs in Myasthenia Gravis- A Mini-Review

Myasthenia gravis (MG) is an acquired autoimmune disease that is mediated by humoral immunity, supplemented by cellular immunity, along with participation of the complement system. The pathogenesis of MG is complex; although autoimmune dysfunction is clearly implicated, the specific mechanism remains unclear. Long non-coding RNAs (lncRNAs) are a class of non-coding RNA molecules with lengths greater than 200 nucleotides, with increasing evidence of their rich biological functions and high-level structure conservation. LncRNAs can directly interact with proteins and microRNAs to regulate the expression of target genes at the transcription and post-transcription levels. In recent years, emerging studies have suggested that lncRNAs play roles in the differentiation of immune cells, secretion of immune factors, and complement production in the human body. This suggests the involvement of lncRNAs in the occurrence and progression of MG through various mechanisms. In addition, the differentially expressed lncRNAs in peripheral biofluid may be used as a biomarker to diagnose MG and evaluate its prognosis. Moreover, with the development of lncRNA expression regulation technology, it is possible to regulate the differentiation of immune cells and influence the immune response by regulating the expression of lncRNAs, which will provide a potential therapeutic option for MG. Here, we review the research progress on the role of lncRNAs in different pathophysiological events contributing to MG, focusing on specific lncRNAs that may largely contribute to the pathophysiology of MG, which could be used as potential diagnostic biomarkers and therapeutic targets.

Localization is the key to action: regulatory peculiarities of lncRNAs

To understand the transcriptomic profile of an individual cell in a multicellular organism, we must comprehend its surrounding environment and the cellular space where distinct molecular stimuli responses are located. Contradicting the initial perception that RNAs were nonfunctional and that only a few could act in chromatin remodeling, over the last few decades, research has revealed that they are multifaceted, versatile regulators of most cellular processes. Among the various RNAs, long non-coding RNAs (LncRNAs) regulate multiple biological processes and can even impact cell fate. In this sense, the subcellular localization of lncRNAs is the primary determinant of their functions. It affects their behavior by limiting their potential molecular partner and which process it can affect. The fine-tuned activity of lncRNAs is also tissue-specific and modulated by their cis and trans regulation. Hence, the spatial context of lncRNAs is crucial for understanding the regulatory networks by which they influence and are influenced. Therefore, predicting a lncRNA's correct location is not just a technical challenge but a critical step in understanding the biological meaning of its activity. Hence, examining these peculiarities is crucial to researching and discussing lncRNAs. In this review, we debate the spatial regulation of lncRNAs and their tissue-specific roles and regulatory mechanisms. We also briefly highlight how bioinformatic tools can aid research in the area.

LncRNAs in tumor metabolic reprogramming and tumor microenvironment remodeling

The tumor microenvironment (TME) is a complex and dynamic ecosystem composed of tumor cells, immune cells, supporting cells, and the extracellular matrix. Typically, the TME is characterized by an immunosuppressive state. To meet the demands of rapid proliferation, cancer cells undergo metabolic reprogramming, which enhances their biosynthesis and bioenergy supply. Immune cells require similar nutrients for activation and proliferation, leading to competition and immunosuppression within the TME. Additionally, tumor metabolites inhibit immune cell activation and function. Consequently, an immunosuppressed and immune-tolerant TME promotes cancer cell proliferation and metastasis. Long non-coding RNAs (lncRNAs), a category of non-coding RNA longer than 200 nucleotides, regulate tumor metabolic reprogramming by interacting with key enzymes, transporters, and related signaling pathways involved in tumor metabolism. Furthermore, lncRNAs can interact with both cellular and non-cellular components in the TME, thereby facilitating tumor growth, metastasis, drug resistance, and inducing immunosuppression. Recent studies have demonstrated that lncRNAs play a crucial role in reshaping the TME by regulating tumor metabolic reprogramming. In this discussion, we explore the potential mechanisms through which lncRNAs regulate tumor metabolic reprogramming to remodel the TME. Additionally, we examine the prospects of lncRNAs as targets for anti-tumor therapy and as biomarkers for tumor prognosis.

G-quadruplexes in long non-coding RNAs and their interactions with proteins

Long non-coding RNAs (lncRNAs) have emerged as crucial regulators of cellular processes, with their dysregulation linked to various disease states. Among the structural motifs in lncRNAs, RNA G-quadruplexes (rG4s) have gained increasing attention due to their diverse roles in cellular function and disease pathogenesis. This review provides an updated and comprehensive overview of rG4s in lncRNAs, elucidating their formation, interaction with proteins, and distinctive roles in cellular processes. We discuss current methodologies for experimentally probing RNA G4s, including the use of specific small molecules, biomolecular ligands and fluorescent probes. The commonly found RNA G4-interacting protein domains are summarised along with potential strategies for disrupting lncRNA G4-protein interactions from a therapeutic perspective.

Long non‑coding RNAs as diagnostic and prognostic biomarkers for colorectal cancer (Review)

Colorectal cancer (CRC) ranks as the 3rd most common cancer globally and is the 2nd leading cause of cancer-related death. Owing to the lack of specific early symptoms and the limitations of existing early diagnostic methods, most patients with CRC are diagnosed at advanced stages. To overcome these challenges, researchers have increasingly focused on molecular biomarkers, with particular interest in long non-coding RNAs (lncRNAs). These non-protein-coding RNAs, which exceed 200 nucleotides in length, play critical roles in the development and progression of CRC. The stability and detectability of lncRNAs in the circulatory system make them promising candidate biomarkers. The analysis of circulating lncRNAs in peripheral blood represents a potential option for minimally invasive diagnostic tests based on liquid biopsy samples. The present review aimed to evaluate the efficacy of lncRNAs with altered expression levels in peripheral blood as diagnostic markers for CRC. Additionally, the clinical significance of lncRNAs as prognostic markers for this disease were summarized.

Paraspeckle-independent co-transcriptional regulation of nuclear microRNA biogenesis by SFPQ

MicroRNAs (miRNAs) play crucial roles in physiological functions and disease, but the regulation of their nuclear biogenesis remains poorly understood. Here, BioID on Drosha, the catalytic subunit of the microprocessor complex, reveals its proximity to splicing factor proline- and glutamine (Q)-rich (SFPQ), a multifunctional RNA-binding protein (RBP) involved in forming paraspeckle nuclear condensates. SFPQ depletion impacts both primary and mature miRNA expression, while other paraspeckle proteins (PSPs) or the paraspeckle scaffolding RNA NEAT1 do not, indicating a paraspeckle-independent role. Comprehensive transcriptomic analyses show that SFPQ loss broadly affects RNAs and miRNA host gene (HG) expression, influencing both their transcription and the stability of their products. Notably, SFPQ protects the oncogenic miR-17∼92 polycistron from degradation by the nuclear exosome targeting (NEXT)-exosome complex and is tightly linked with its overexpression across a broad variety of cancers. Our findings reveal a dual role for SFPQ in regulating miRNA HG transcription and stability, as well as its significance in cancers.

Long non-coding RNAs in ferroptosis, pyroptosis and necroptosis: from functions to clinical implications in cancer therapy

As global population ageing accelerates, cancer emerges as a predominant cause of mortality. Long non-coding RNAs (lncRNAs) play crucial roles in cancer cell growth and death, given their involvement in regulating downstream gene expression levels and numerous cellular processes. Cell death, especially non-apoptotic regulated cell death (RCD), such as ferroptosis, pyroptosis and necroptosis, significantly impacts cancer proliferation, invasion and metastasis. Understanding the interplay between lncRNAs and the diverse forms of cell death in cancer is imperative. Modulating lncRNA expression can regulate cancer onset and progression, offering promising therapeutic avenues. This review discusses the mechanisms by which lncRNAs modulate non-apoptotic RCDs in cancer, highlighting their potential as biomarkers for various cancer types. Elucidating the role of lncRNAs in cell death pathways provides valuable insights for personalised cancer interventions.

Mask-Guided Target Node Feature Learning and Dynamic Detailed Feature Enhancement for lncRNA-Disease Association Prediction

Identifying new relevant long noncoding RNAs (lncRNAs) for various human diseases can facilitate the exploration of the causes and progression of these diseases. Recently, several graph inference methods have been proposed to predict disease-related lncRNAs by exploiting the topological structure and node attributes within graphs. However, these methods did not prioritize the target lncRNA and disease nodes over auxiliary nodes like miRNA nodes, potentially limiting their ability to fully utilize the features of the target nodes. We propose a new method, mask-guided target node feature learning and dynamic detailed feature enhancement for lncRNA-disease association prediction (MDLD), to enhance node feature learning for improved lncRNA-disease association prediction. First, we designed a heterogeneous graph masked transformer autoencoder to guide feature learning, focusing more on the features of target lncRNA (disease) nodes. The target nodes were increasingly masked as training progressed, which helps develop a more robust prediction model. Second, we developed a graph convolutional network with dynamic residuals (GCNDR) to learn and integrate the heterogeneous topology and features of all lncRNA, disease, and miRNA nodes. GCNDR employs an interlayer residual strategy and a residual evolution strategy to mitigate oversmoothing caused by multilayer graph convolution. The interlayer residual strategy estimates the importance of node features learned in the previous GCN encoding layer for nodes in the current encoding layer. Additionally, since there are dependencies in the importance of features of individual lncRNA (disease, miRNA) nodes across multiple encoding layers, a gated recurrent unit-based strategy is proposed to encode these dependencies. Finally, we designed a perspective-level attention mechanism to obtain more informative features of lncRNA and disease node pairs from the perspectives of mask-enhanced and dynamic-enhanced node features. Cross-validation experimental results demonstrated that MDLD outperformed 10 other state-of-the-art prediction methods. Ablation experiments and case studies on candidate lncRNAs for three diseases further proved the technical contributions of MDLD and its capability to discover disease-related lncRNAs.

Identification of Two Long Noncoding RNAs, Kcnq1ot1 and Rmst, as Biomarkers in Chronic Liver Diseases in Mice

This study investigates novel short-lived long noncoding RNAs (lncRNAs) in mice with altered expression in metabolic dysfunction-associated steatotic liver (MASH) and liver fibrosis. LncRNAs share similarities with mRNAs in their transcription by RNA polymerase II, possession of a 5' cap structure, and presence of a polyA tail. We identified two lncRNAs, Kcnq1ot1 and Rmst, significantly decreased in both conditions. These lncRNAs showed dramatic expression changes in MASH livers induced by Western diets and CCl4, and in fibrotic livers induced by CCl4 alone. The decrease was more pronounced in liver fibrosis, suggesting their potential as biomarkers for disease progression. Our findings are consistent across different fibrosis models, indicating a crucial role for these lncRNAs in MASH and liver fibrosis in mice. With MASH becoming a global health issue and its progression to fibrosis associated with hepatocarcinogenesis and poor prognosis, understanding the underlying mechanisms is critical. This research contributes to elucidating lncRNA functions in murine liver diseases and provides a foundation for developing novel therapeutic strategies targeting lncRNAs in MASH and liver fibrosis, offering new avenues for potential therapeutic interventions.

Disulfidptosis-related lncRNAs signature predicting prognosis and immunotherapy effect in lung adenocarcinoma

PURPOSE

Lung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients.

METHODS

The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines.

RESULTS

A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line.

CONCLUSIONS

The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.

Long live the RNAs: The guardians of neuronal longevity?

In a recent publication in Science, Zocher et al.1 identify and characterize long-lived nuclear RNA in the mouse brain, suggesting their potential roles as guardians of neuronal longevity.

Epigenetic modulation of long noncoding RNA H19 in oral squamous cell carcinoma-A narrative review

Oral squamous cell carcinoma (OSCC) showed a seemingly increasing incidence in the last decade. In India, despite the use of tobacco decreased rapidly, in the past five years, the incidence pattern of OSCC over gender and age showed a drastic shift. About 51 % of the head and neck cancers are not associated with habits. Studies exploring various contributing factors in the incidence of this malignancy have documented. Recently, the epigenetic factors associated with the induction and progression of OSCC were explored. More than 90 % of the human genome is made up of non-coding transcriptome, which believed to be noises. However, these non-coding RNAs were identified to be the major epigenetic modulators, which raises concern over incidence of carcinoma in non-habit patients. H19 is a long non coding RNA which proved to be an effective biomarker in various carcinoma. Its role in oral squamous cell cancer was not investigated in depth. This review discusses in detail the various epigenetic role of H19 in inducing oral carcinogenesis.

MIAT LncRNA: A multifunctional key player in non-oncological pathological conditions

The discovery of non-coding RNAs (ncRNAs) has unveiled a wide range of transcripts that do not encode proteins but play key roles in several cellular and molecular processes. Long noncoding RNAs (lncRNAs) are specific class of ncRNAs that are longer than 200 nucleotides and have gained significant attention due to their diverse mechanisms of action and potential involvement in various pathological conditions. In the current review, the authors focus on the role of lncRNAs, specifically highlighting the Myocardial Infarction Associated Transcript (MIAT), in non-oncological context. MIAT is a nuclear lncRNA that has been directly linked to myocardial infarction and is reported to control post-transcriptional processes as a competitive endogenous RNA (ceRNA) molecule. It interacts with microRNAs (miRNAs), thereby limiting the translation and expression of their respective target messenger RNA (mRNA) and regulating protein expression. Yet, MIAT has been implicated in other numerous pathological conditions such as other cardiovascular diseases, autoimmune disease, neurodegenerative diseases, metabolic diseases, and many others. In this review, the authors emphasize that MIAT exhibits distinct expression patterns and functions across different pathological conditions and is emerging as potential diagnostic, prognostic, and therapeutic agent. Additionally, the authors highlight the regulatory role of MIAT and shed light on the involvement of lncRNAs and specifically MIAT in various non-oncological pathological conditions.

Long non-coding RNA MALAT1 in hematological malignancies and its clinical applications

ABSTRACT

Metastasis-associated lung adenocarcinoma transcript 1 ( MALAT1 ) is a well-established oncogenic long non-coding RNA, the higher expression of which is strongly correlated with cancer events such as tumorigenesis, progression, metastasis, drug resistance, and treatment outcome in solid cancers. Recently, a series of studies has highlighted its potential role in hematological malignancies in terms of these events. Similar to solid cancers, MALAT1 can regulate various target genes via sponging and epigenetic mechanisms, but the miRNAs sponged by MALAT1 differ from those identified in solid cancers. In this review, we systematically describe the role and underlying mechanisms of MALAT1 in multiple types of hematological malignancies, including regulation of cell proliferation, metastasis, stress response, and glycolysis. Clinically, MALAT1 expression is related to poor treatment outcome and drug resistance, therefore exhibiting potential prognostic value in multiple myeloma, lymphoma, and leukemia. Finally, we discuss the evaluation of MALAT1 as a novel therapeutic target against cancer in preclinical studies.

Annotation of nuclear lncRNAs based on chromatin interactions

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

A Bidirectional Non-Coding RNA Promoter Mediates Long-Range Gene Expression Regulation

Recent evidence suggests that human gene promoters display gene expression regulatory mechanisms beyond the typical single gene local transcription modulation. In mammalian genomes, genes with an associated bidirectional promoter are abundant; bidirectional promoter architecture serves as a regulatory hub for a gene pair expression. However, it has been suggested that its contribution to transcriptional regulation might exceed local transcription initiation modulation. Despite their abundance, the functional consequences of bidirectional promoter architecture remain largely unexplored. This work studies the long-range gene expression regulatory role of a long non-coding RNA gene promoter using chromosome conformation capture methods. We found that this particular bidirectional promoter contributes to distal gene expression regulation in a target-specific manner by establishing promoter-promoter interactions. In particular, we validated that the promoter-promoter interactions of this regulatory element with the promoter of distal gene BBX contribute to modulating the transcription rate of this gene; removing the bidirectional promoter from its genomic context leads to a rearrangement of BBX promoter-enhancer interactions and to increased gene expression. Moreover, long-range regulatory functionality is not directly dependent on its associated non-coding gene pair expression levels.

The roles of long non-coding RNAs in ovarian cancer: from functions to therapeutic implications

Long non-coding RNAs (lncRNAs) are multifunctional and participate in a variety of biological processes and gene regulatory networks. The deregulation of lncRNAs has been extensively implicated in diverse human diseases, especially in cancers. Overwhelming evidence demonstrates that lncRNAs are essential to the pathophysiological processes of ovarian cancer (OC), acting as regulators involved in metastasis, cell death, chemoresistance, and tumor immunity. In this review, we illustrate the expanded functions of lncRNAs in the initiation and progression of OC and elaborate on the signaling pathways in which they pitch. Additionally, the potential clinical applications of lncRNAs as biomarkers in the diagnosis and treatment of OC were emphasized, cementing the bridge of communication between clinical practice and basic research.

Neuroinflammation driven by human immunodeficiency virus-1 (HIV-1) directs the expression of long noncoding RNA RP11-677M14.2 resulting in dysregulation of neurogranin in vivo and in vitro

Neuroinflammation and synaptodendritic damage represent the pathological hallmarks of HIV-1 associated cognitive disorders (HAND). The post-synaptic protein neurogranin (Nrgn) is significantly reduced in the frontal cortex of postmortem brains from people with HIV (PWH) and it is associated with inflammatory factors released by infected microglia/macrophages. However, the mechanism involved in synaptic loss have yet to be elucidated. In this study, we characterized a newly identified long non-coding RNA (lncRNA) transcript (RP11-677M14.2), which is antisense to the NRGN locus and is highly expressed in the frontal cortex of HIV-1 individuals. Further analysis indicates an inverse correlation between the expression of RP11-677M14.2 RNA and Nrgn mRNA. Additionally, the Nrgn-lncRNA axis is dysregulated in neurons exposed to HIV-1 infected microglia conditioned medium enriched with IL-1β. Moreover, in vitro overexpression of this lncRNA impacts Nrgn expression at both mRNA and protein levels. Finally, we modeled the Nrgn-lncRNA dysregulation within an HIV-1-induced inflammatory environment using brain organoids, thereby corroborating our in vivo and in vitro findings. Together, our study implicates a plausible role for lncRNA RP11-677M14.2 in modulating Nrgn expression that might serve as the mechanistic link between Nrgn loss and cognitive dysfunction in HAND, thus shedding new light on the mechanisms underlying synaptodendritic damage.

Prognostic analysis of hepatocellular carcinoma based on cuproptosis -associated lncRNAs

OBJECTIVES

Cuproptosis represents an innovative type of cell death, distinct from apoptosis, driven by copper dependency, yet the involvement of copper apoptosis-associated long non-coding RNAs (CRLncRNAs) in hepatocellular carcinoma (HCC) remains unclear. This study is dedicated to unveiling the role and significance of these copper apoptosis-related lncRNAs within the context of HCC, focusing on their impact on both the development of the disease and its prognosis.

METHODS

We conducted an analysis of gene transcriptomic and clinical data for HCC cases by sourcing information from The Cancer Genome Atlas database. By incorporating cuproptosis-related genes, we established prognostic features associated with cuproptosis-related lncRNAs. Furthermore, we elucidated the mechanism of cuproptosis-related lncRNAs in the prognosis and treatment of HCC through comprehensive approaches, including Lasso and Cox regression analyses, survival analyses of samples, as well as examinations of tumor mutation burden and immune function.

RESULTS

We developed a prognostic model featuring six cuproptosis-related lncRNAs: AC026412.3, AC125437.1, AL353572.4, MKLN1-AS, TMCC1-AS1, and SLC6A1-AS1. This model demonstrated exceptional prognostic accuracy in both training and validation cohorts for patients with tumors, showing significantly longer survival times for those categorized in the low-risk group compared to the high-risk group. Additionally, our analyses, including tumor mutation burden, immune function, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and drug sensitivity, further elucidated the potential mechanisms through which cuproptosis-associated lncRNAs may influence disease outcome.

CONCLUSIONS

The model developed using cuproptosis-related long non-coding RNAs (lncRNAs) demonstrates promising predictive capabilities for both the prognosis and immunotherapy outcomes of tumor patients. This could play a crucial role in patient management and the optimization of immunotherapeutic strategies, offering valuable insights for future research.

Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs

As the long non-coding RNAs (lncRNAs) play important roles during the incurrence and development of various human diseases, identifying disease-related lncRNAs can contribute to clarifying the pathogenesis of diseases. Most of the recent lncRNA-disease association prediction methods utilized the multi-source data about the lncRNAs and diseases. A single lncRNA may participate in multiple disease processes, and multiple lncRNAs usually are involved in the same disease process synergistically. However, the previous methods did not completely exploit the biological characteristics to construct the informative prediction models. We construct a prediction model based on adaptive hypergraph and gated convolution for lncRNA-disease association prediction (AGLDA), to embed and encode the biological characteristics about lncRNA-disease associations, the topological features from the entire heterogeneous graph perspective, and the gated enhanced pairwise features. First, the strategy for constructing hyperedges is designed to reflect the biological characteristic that multiple lncRNAs are involved in multiple disease processes. Furthermore, each hyperedge has its own biological perspective, and multiple hyperedges are beneficial for revealing the diverse relationships among multiple lncRNAs and diseases. Second, we encode the biological features of each lncRNA (disease) node using a strategy based on dynamic hypergraph convolutional networks. The strategy may adaptively learn the features of the hyperedges and formulate the dynamically evolved hypergraph topological structure. Third, a group convolutional network is established to integrate the entire heterogeneous topological structure and multiple types of node attributes within an lncRNA-disease-miRNA graph. Finally, a gated convolutional strategy is proposed to enhance the informative features of the lncRNA-disease node pairs. The comparison experiments indicate that AGLDA outperforms seven advanced prediction methods. The ablation studies confirm the effectiveness of major innovations, and the case studies validate AGLDA's ability in application for discovering potential disease-related lncRNA candidates.

MALAT1: A Long Non-Coding RNA with Multiple Functions and Its Role in Processes Associated with Fat Deposition

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) belongs to the lncRNA molecules, which are involved in transcriptional and epigenetic regulation and the control of gene expression, including the mechanism of chromatin remodeling. MALAT1 was first discovered during carcinogenesis in lung adenocarcinoma, hence its name. In humans, 66 of its isoforms have been identified, and in pigs, only 2 are predicted, for which information is available in Ensembl databases (Ensembl Release 111). MALAT1 is expressed in numerous tissues, including adipose, adrenal gland, heart, kidney, liver, ovary, pancreas, sigmoid colon, small intestine, spleen, and testis. MALAT1, as an lncRNA, shows a wide range of functions. It is involved in the regulation of the cell cycle, where it has pro-proliferative effects and high cellular levels during the G1/S and mitotic (M) phases. Moreover, it is involved in invasion, metastasis, and angiogenesis, and it has a crucial function in alternative splicing during carcinogenesis. In addition, MALAT1 plays a significant role in the processes of fat deposition and adipogenesis. The human adipose tissue stem cells, during differentiation into adipocytes, secrete MALAT1 as one the most abundant lncRNAs in the exosomes. MALAT1 expression in fat tissue is positively correlated with adipogenic FABP4 and LPL. This lncRNA is involved in the regulation of PPARγ at the transcription stage, fatty acid metabolism, and insulin signaling. The wide range of MALAT1 functions makes it an interesting target in studies searching for drugs to prevent obesity development in humans. In turn, in farm animals, it can be a source of selection markers to control the fat tissue content.

Mathematical model for the role of multiple pericentromeric repeats on heterochromatin assembly

Although the length and constituting sequences for pericentromeric repeats are highly variable across eukaryotes, the presence of multiple pericentromeric repeats is one of the conserved features of the eukaryotic chromosomes. Pericentromeric heterochromatin is often misregulated in human diseases, with the expansion of pericentromeric repeats in human solid cancers. In this article, we have developed a mathematical model of the RNAi-dependent methylation of H3K9 in the pericentromeric region of fission yeast. Our model, which takes copy number as an explicit parameter, predicts that the pericentromere is silenced only if there are many copies of repeats. It becomes bistable or desilenced if the copy number of repeats is reduced. This suggests that the copy number of pericentromeric repeats alone can determine the fate of heterochromatin silencing in fission yeast. Through sensitivity analysis, we identified parameters that favor bistability and desilencing. Stochastic simulation shows that faster cell division and noise favor the desilenced state. These results show the unexpected role of pericentromeric repeat copy number in gene silencing and provide a quantitative basis for how the copy number allows or protects repetitive and unique parts of the genome from heterochromatin silencing, respectively.

The prognostic, diagnostic, and therapeutic impact of Long noncoding RNAs in gastric cancer

Gastric cancer (GC), ranking as the third deadliest cancer globally, faces challenges of late diagnosis and limited treatment efficacy. Long non-coding RNAs (lncRNAs) emerge as valuable treasured targets for cancer prognosis, diagnosis, and therapy, given their high specificity, convenient non-invasive detection in body fluids, and crucial roles in diverse physiological and pathological processes. Research indicates the significant involvement of lncRNAs in various aspects of GC pathogenesis, including initiation, metastasis, and recurrence, underscoring their potential as novel diagnostic and prognostic biomarkers, as well as therapeutic targets for GC. Despite existing challenges in the clinical application of lncRNAs in GC, the evolving landscape of lncRNA molecular biology holds promise for advancing the survival and treatment outcomes of gastric cancer patients. This review provides insights into recent studies on lncRNAs in gastric cancer, elucidating their molecular mechanisms and exploring the potential clinical applications in GC.

Harnessing the supremacy of MEG3 LncRNA to defeat gastrointestinal malignancies

Evidence suggests that long non-coding RNAs (lncRNAs) play a pivotal role in the carcinogenesis and progression of various human malignancies including gastrointestinal malignancies. This comprehensive review reports the functions and mechanisms of the lncRNA maternally expressed gene 3 (MEG3) involved in gastrointestinal malignancies. It summarizes its roles in mediating the regulation of cellular proliferation, apoptosis, migration, invasiveness, epithelial-to-mesenchymal transition, and drug resistance in several gastrointestinal cancers such as colorectal cancer, gall bladder cancer, pancreatic cancer, gastric cancer, esophageal cancer, cholangiocarcinoma, gastrointestinal stromal tumors and most importantly, hepatocellular carcinoma. In addition, the authors briefly highlight its implicated mechanistic role and interactions with different non-coding RNAs and oncogenic signaling cascades. This review presents the rationale for developing non coding RNA-based anticancer therapy via harnessing the power of MEG3 in gastrointestinal malignancies.

Inheritance of epigenetic transcriptional memory

Epigenetic memory allows organisms to stably alter their transcriptional program in response to developmental or environmental stimuli. Such transcriptional programs are mediated by heritable regulation of the function of enhancers and promoters. Memory involves read-write systems that enable self-propagation and mitotic inheritance of cis-acting epigenetic marks to induce stable changes in transcription. Also, in response to environmental cues, cells can induce epigenetic transcriptional memory to poise inducible genes for faster induction in the future. Here, we discuss modes of epigenetic inheritance and the molecular basis of epigenetic transcriptional memory.

Identifying Biomarkers and Therapeutic Targets by Multiomic Analysis for HNSCC: Precision Medicine and Healthcare Management

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the major types of cancer, with 900,000 cases and over 400,000 deaths annually. It constitutes 3-4% of all cancers in Europe and western countries. As early diagnosis is the key to treating the disease, reliable biomarkers play an important role in the precision medicine of HNSCC. Despite treatments, the survival rate of cancer patients remains unchanged, and this is mainly due to the failure to detect the disease early. Thus, the objective of this study is to identify reliable biomarkers for head and neck cancers for better healthcare management. Methods: In this study, all available, curated human genes were screened for their expression against HNSCC TCGA patient samples using genomic and proteomic data by various bioinformatic approaches and datamining. Docking studies were performed using AutoDock or online virtual screening tools for identifying potential ligands. Results: Sixty genes were short-listed, and most of them show a consistently higher expression in head and neck patient samples at both the mRNA and the protein level. Irrespective of human papillomavirus (HPV) status, all of them show a higher expression in cancer samples. The higher expression of 30 genes shows adverse effects on patient survival. Out of the 60 genes, 12 genes have crystal structures and druggable potential. We show that genes such as GTF2H4, HAUS7, MSN, and MNDA could be targets of Pembrolizumab and Nivolumab, which are approved monoclonal antibodies for HNSCC. Conclusion: Sixty genes are identified as potential biomarkers for head and neck cancers based on their consistent and statistically significantly higher expression in patient samples. Four proteins have been identified as potential drug targets based on their crystal structure. However, the utility of these candidate genes has to be further tested using patient samples.

NAP-seq reveals multiple classes of structured noncoding RNAs with regulatory functions

Up to 80% of the human genome produces "dark matter" RNAs, most of which are noncapped RNAs (napRNAs) that frequently act as noncoding RNAs (ncRNAs) to modulate gene expression. Here, by developing a method, NAP-seq, to globally profile the full-length sequences of napRNAs with various terminal modifications at single-nucleotide resolution, we reveal diverse classes of structured ncRNAs. We discover stably expressed linear intron RNAs (sliRNAs), a class of snoRNA-intron RNAs (snotrons), a class of RNAs embedded in miRNA spacers (misRNAs) and thousands of previously uncharacterized structured napRNAs in humans and mice. These napRNAs undergo dynamic changes in response to various stimuli and differentiation stages. Importantly, we show that a structured napRNA regulates myoblast differentiation and a napRNA DINAP interacts with dyskerin pseudouridine synthase 1 (DKC1) to promote cell proliferation by maintaining DKC1 protein stability. Our approach establishes a paradigm for discovering various classes of ncRNAs with regulatory functions.

The lncRNAs Gas5, MALAT1 and SNHG8 as diagnostic biomarkers for epithelial malignant pleural mesothelioma in Egyptian patients

Long noncoding RNAs have been shown to be involved in a myriad of physiological and pathological pathways. To date, malignant pleural mesothelioma (MPM) is considered an extremely aggressive cancer. One reason for this is the late diagnosis of the disease, which can occur within 30-40 years of asbestos exposure. There is an immense need for the development of new, sensitive, inexpensive and easy methods for the early detection of this disease other than invasive methods such as biopsy. The aim of this study was to determine the expression of circulating lncRNAs in mesothelioma patient plasma to identify potential biomarkers. Ten previously identified lncRNAs that were shown to be aberrantly expressed in mesothelioma tissues were selected as candidates for subsequent validation. The expression of the ten selected candidate lncRNAs was verified via quantitative PCR (qPCR) in human plasma samples from mesothelioma patients versus healthy controls. The expression levels of circulating GAS5, SNHG8 and MALAT1 were significantly greater in plasma samples from patients than in those from controls. The ROC analysis of both MALAT1 and SNHG8 revealed 88.89% sensitivity and 66.67% specificity. The sensitivity of these markers was greater than that of GAS5 (sensitivity 72.22% and specificity 66.67%). The regression model for GAS5 was statistically significant, while that for SNHG8 and MALAT1 was not significant due to the small sample size. The area under the curve (AUC) of the three ROC curves was acceptable and significant: 0.7519 for GAS5, 0.7352 for SNHG8 and 0.7185 for MALAT1. This finding confirmed their ability to be used as markers. The three lncRNAs were not affected by age, sex or smoking status. The three lncRNAs showed great potential as independent predictive diagnostic biomarkers. Although the prediction model for MALAT1 did not significantly differ, MALAT1 was significantly expressed in patients more than in controls (p = 0.0266), and the recorded sensitivity and specificity were greater than those of GAS5.

The early macrophage response to pathogens requires dynamic regulation of the nuclear paraspeckle

To ensure a robust immune response to pathogens without risking immunopathology, the kinetics and amplitude of inflammatory gene expression in macrophages need to be exquisitely well controlled. There is a growing appreciation for stress-responsive membraneless organelles (MLOs) regulating various steps of eukaryotic gene expression in response to extrinsic cues. Here, we implicate the nuclear paraspeckle, a highly ordered biomolecular condensate that nucleates on the Neat1 lncRNA, in tuning innate immune gene expression in murine macrophages. In response to a variety of innate agonists, macrophage paraspeckles rapidly aggregate (0.5 h poststimulation) and disaggregate (2 h poststimulation). Paraspeckle maintenance and aggregation require active transcription and MAPK signaling, whereas paraspeckle disaggregation requires degradation of Neat1 via the nuclear RNA exosome. In response to lipopolysaccharide treatment, Neat1 KO macrophages fail to properly express a large cohort of proinflammatory cytokines, chemokines, and antimicrobial mediators. Consequently, Neat1 KO macrophages cannot control replication of Salmonella enterica serovar Typhimurium or vesicular stomatitis virus. These findings highlight a prominent role for MLOs in orchestrating the macrophage response to pathogens and support a model whereby dynamic assembly and disassembly of paraspeckles reorganizes the nuclear landscape to enable inflammatory gene expression following innate stimuli.

Neuroinflammation driven by Human Immunodeficiency Virus-1 (HIV-1) directs the expression of long noncoding RNA RP11-677M14.2 resulting in dysregulation of Neurogranin in vivo and in vitro

Neuroinflammation and synaptodendritic damage represent the pathological hallmarks of HIV-1 associated cognitive disorders (HAND). The post-synaptic protein neurogranin (Nrgn) is significantly reduced in the frontal cortex of postmortem brains from people with HIV (PWH) and it is associated with inflammatory factors released by infected microglia/macrophages. However, the mechanism involved in synaptic loss have yet to be elucidated. In this study, we characterized a newly identified long non-coding RNA (lncRNA) transcript (RP11-677M14.2), which is antisense to the NRGN locus and is highly expressed in the frontal cortex of HIV-1 individuals. Further analysis indicates an inverse correlation between the expression of RP11-677M14.2 RNA and Nrgn mRNA. Additionally, the Nrgn-lncRNA axis is dysregulated in neurons exposed to HIV-1 infected microglia conditioned medium enriched with IL-1b. Moreover, in vitro overexpression of this lncRNA impact Nrgn expression at both mRNA and protein levels. Finally, we modeled the Nrgn-lncRNA dysregulation within an HIV-1-induced neuroinflammatory environment using brain organoids, thereby corroborating our in vivo and in vitro findings. Together, our study implicates a plausible role for lncRNA RP11-677M14.2 in modulating Nrgn expression that might serve as the mechanistic link between Nrgn loss and cognitive dysfunction in HAND, thus shedding new light on the mechanisms underlying synaptodendritic damage.

GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations

BACKGROUND

A growing body of researches indicate that the disrupted expression of long non-coding RNA (lncRNA) is linked to a range of human disorders. Therefore, the effective prediction of lncRNA-disease association (LDA) can not only suggest solutions to diagnose a condition but also save significant time and labor costs.

METHOD

In this work, we proposed a novel LDA predicting algorithm based on graph convolutional network and transformer, named GCNFORMER. Firstly, we integrated the intraclass similarity and interclass connections between miRNAs, lncRNAs and diseases, and built a graph adjacency matrix. Secondly, to completely obtain the features between various nodes, we employed a graph convolutional network for feature extraction. Finally, to obtain the global dependencies between inputs and outputs, we used a transformer encoder with a multiheaded attention mechanism to forecast lncRNA-disease associations.

RESULTS

The results of fivefold cross-validation experiment on the public dataset revealed that the AUC and AUPR of GCNFORMER achieved 0.9739 and 0.9812, respectively. We compared GCNFORMER with six advanced LDA prediction models, and the results indicated its superiority over the other six models. Furthermore, GCNFORMER's effectiveness in predicting potential LDAs is underscored by case studies on breast cancer, colon cancer and lung cancer.

CONCLUSIONS

The combination of graph convolutional network and transformer can effectively improve the performance of LDA prediction model and promote the in-depth development of this research filed.

Exploring IDI2-AS1, OIP5-AS1, and LITATS1: Changes in Long Non-coding RNAs Induced by the Poly I:C Stimulation

Long non-coding RNAs (lncRNAs) are sequences longer than 200 nucleotides, but they do not encode proteins. Nevertheless, they have significant roles in diverse biological functions. It remains unclear how viral infections trigger the expression of lncRNAs. In our previous research, we revealed a distinct type of lncRNAs with a lifespan under 4 h in human HeLa cells. These short-lived lncRNAs might be associated with numerous regulatory roles. Given their potential impact on human physiology, these short-lived lncRNAs could be key indicators to measure polyinosinic:polycytidylic acid (poly I:C) stimulation. In our recent work, we discovered three lncRNAs: IDI2-AS1, OIP5-AS1, and LITATS1. After exposure to poly I:C, imitating viral assault in human A549 cells, IDI2-AS1 levels dropped significantly while OIP5-AS1 and LITATS1 levels rose markedly. Our results indicate that short-lived lncRNAs respond to poly I:C stimulation, exhibiting substantial changes in expression. This indicates that the understanding the role of lncRNAs in the host response to viral infection and the potential for these molecules to serve as novel therapeutic targets.

Strategic and Innovative Roles of lncRNAs Regulated by Naturally-derived Small Molecules in Cancer Therapy

In the field of precision and personalized medicine, the next generation sequencing method has begun to take an active place as genome-wide screening applications in the diagnosis and treatment of diseases. Studies based on the determination of the therapeutic efficacy of personalized drug use in cancer treatment in the size of the transcriptome and its extension, lncRNA, have been increasing rapidly in recent years. Targeting and/or regulating noncoding RNAs (ncRNAs) consisting of long noncoding RNAs (lncRNAs) are promising strategies for cancer treatment. Within the scope of rapidly increasing studies in recent years, it has been shown that many natural agents obtained from biological organisms can potentially alter the expression of many lncRNAs associated with oncogenic functions. Natural agents include effective small molecules that provide anti-cancer effects and have been used as chemotherapy drugs or in combination with standard anti-cancer drugs used in routine treatment. In this review, it was aimed to provide detailed information about the potential of natural agents to regulate and/or target non-coding RNAs and their mechanisms of action to provide an approach for cancer therapy. The discovery of novel anti-cancer targets and subsequent development of effective drugs or combination strategies that are still needed for most cancers will be promising for cancer treatment.

The complex nature of lncRNA-mediated chromatin dynamics in multiple myeloma

Extensive genome-wide sequencing efforts have unveiled the intricate regulatory potential of long non-protein coding RNAs (lncRNAs) within the domain of haematological malignancies. Notably, lncRNAs have been found to directly modulate chromatin architecture, thereby impacting gene expression and disease progression by interacting with DNA, RNA, and proteins in a tissue- or condition-specific manner. Furthermore, recent studies have highlighted the intricate epigenetic control of lncRNAs in cancer. Consequently, this provides a rationale to explore the possibility of therapeutically targeting lncRNAs themselves or the epigenetic mechanisms that govern their activity. Within the scope of this review, we will assess the current state of knowledge regarding the epigenetic regulation of lncRNAs and how, in turn, lncRNAs contribute to chromatin remodelling in the context of multiple myeloma.

Comprehensive landscape and future perspective of long noncoding RNAs in non-small cell lung cancer: it takes a village

Long noncoding RNAs (lncRNAs) are a distinct subtype of RNA that lack protein-coding capacity but exert significant influence on various cellular processes. In non-small cell lung cancer (NSCLC), dysregulated lncRNAs act as either oncogenes or tumor suppressors, contributing to tumorigenesis and tumor progression. LncRNAs directly modulate gene expression, act as competitive endogenous RNAs by interacting with microRNAs or proteins, and associate with RNA binding proteins. Moreover, lncRNAs can reshape the tumor immune microenvironment and influence cellular metabolism, cancer cell stemness, and angiogenesis by engaging various signaling pathways. Notably, lncRNAs have shown great potential as diagnostic or prognostic biomarkers in liquid biopsies and therapeutic strategies for NSCLC. This comprehensive review elucidates the significant roles and diverse mechanisms of lncRNAs in NSCLC. Furthermore, we provide insights into the clinical relevance, current research progress, limitations, innovative research approaches, and future perspectives for targeting lncRNAs in NSCLC. By summarizing the existing knowledge and advancements, we aim to enhance the understanding of the pivotal roles played by lncRNAs in NSCLC and stimulate further research in this field. Ultimately, unraveling the complex network of lncRNA-mediated regulatory mechanisms in NSCLC could potentially lead to the development of novel diagnostic tools and therapeutic strategies.

The Role of ncRNAs in the Immune Dysregulation of Preeclampsia

The main complications causing practically 75% of all maternal deaths are severe bleeding, infections, and high blood pressure during pregnancy (preeclampsia (PE) and eclampsia). The usefulness of ncRNAs as clinical biomarkers has been explored in an extensive range of human diseases including pregnancy-related diseases such as PE. Immunological dysregulation show that the Th1/17:Th2/Treg ratio is "central and causal" to PE. However, there is evidence of the involvement of placenta-expressed miRNAs and lncRNAs in the immunological regulation of crucial processes of placenta development and function during pregnancy. Abnormal expression of these molecules is related to immune physiopathological processes that occur in PE. Therefore, this work aims to describe the importance of miRNAs and lncRNAs in immune dysregulation in PE. Interestingly, multiple ncRNAS are involved in the immune dysregulation of PE participating in type 1 immune response regulation, immune microenvironment regulation in placenta promoting inflammatory factors, trophoblast cell invasion in women with Early-Onset PE (EOPE), placental development, and angiogenesis, promotion of population of M1 and M2, proliferation, invasion, and migration of placental trophoblast cells, and promotion of invasion and autophagy through vias such as PI3K/AKT/mTOR, VEGF/VEGFR1, and TLR9/STAT3.

Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Long noncoding RNAs (lncRNA) play an important role in gene regulation and contribute to tumorigenesis. While pan-cancer studies of lncRNA expression have been performed for adult malignancies, the lncRNA landscape across pediatric cancers remains largely uncharted. Here, we curated RNA sequencing data for 1,044 pediatric leukemia and extracranial solid tumors and integrated paired tumor whole genome sequencing and epigenetic data in relevant cell line models to explore lncRNA expression, regulation, and association with cancer. A total of 2,657 lncRNAs were robustly expressed across six pediatric cancers, including 1,142 exhibiting histotype-elevated expression. DNA copy number alterations contributed to lncRNA dysregulation at a proportion comparable to protein coding genes. Application of a multidimensional framework to identify and prioritize lncRNAs impacting gene networks revealed that lncRNAs dysregulated in pediatric cancer are associated with proliferation, metabolism, and DNA damage hallmarks. Analysis of upstream regulation via cell type-specific transcription factors further implicated distinct histotype-elevated and developmental lncRNAs. Integration of these analyses prioritized lncRNAs for experimental validation, and silencing of TBX2-AS1, the top-prioritized neuroblastoma-specific lncRNA, resulted in significant growth inhibition of neuroblastoma cells, confirming the computational predictions. Taken together, these data provide a comprehensive characterization of lncRNA regulation and function in pediatric cancers and pave the way for future mechanistic studies.

SIGNIFICANCE

Comprehensive characterization of lncRNAs in pediatric cancer leads to the identification of highly expressed lncRNAs across childhood cancers, annotation of lncRNAs showing histotype-specific elevated expression, and prediction of lncRNA gene regulatory networks.

RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies

RNA localization is essential for regulating spatial translation, where RNAs are trafficked to their target locations via various biological mechanisms. In this review, we discuss RNA localization in the context of molecular mechanisms, experimental techniques and machine learning-based prediction tools. Three main types of molecular mechanisms that control the localization of RNA to distinct cellular compartments are reviewed, including directed transport, protection from mRNA degradation, as well as diffusion and local entrapment. Advances in experimental methods, both image and sequence based, provide substantial data resources, which allow for the design of powerful machine learning models to predict RNA localizations. We review the publicly available predictive tools to serve as a guide for users and inspire developers to build more effective prediction models. Finally, we provide an overview of multimodal learning, which may provide a new avenue for the prediction of RNA localization.

Comprehensive transcriptomic analysis of long non-coding RNAs in bovine ovarian follicles and early embryos

Long non-coding RNAs (lncRNAs) have been the subject of numerous studies over the past decade. First thought to come from aberrant transcriptional events, lncRNAs are now considered a crucial component of the genome with roles in multiple cellular functions. However, the functional annotation and characterization of bovine lncRNAs during early development remain limited. In this comprehensive analysis, we review lncRNAs expression in bovine ovarian follicles and early embryos, based on a unique database comprising 468 microarray hybridizations from a single platform designed to target 7,724 lncRNA transcripts, of which 5,272 are intergenic (lincRNA), 958 are intronic, and 1,524 are antisense (lncNAT). Compared to translated mRNA, lncRNAs have been shown to be more tissue-specific and expressed in low copy numbers. This analysis revealed that protein-coding genes and lncRNAs are both expressed more in oocytes. Differences between the oocyte and the 2-cell embryo are also more apparent in terms of lncRNAs than mRNAs. Co-expression network analysis using WGCNA generated 25 modules with differing proportions of lncRNAs. The modules exhibiting a higher proportion of lncRNAs were found to be associated with fewer annotated mRNAs and housekeeping functions. Functional annotation of co-expressed mRNAs allowed attribution of lncRNAs to a wide array of key cellular events such as meiosis, translation initiation, immune response, and mitochondrial related functions. We thus provide evidence that lncRNAs play diverse physiological roles that are tissue-specific and associated with key cellular functions alongside mRNAs in bovine ovarian follicles and early embryos. This contributes to add lncRNAs as active molecules in the complex regulatory networks driving folliculogenesis, oogenesis and early embryogenesis all of which are necessary for reproductive success.

Deciphering shared attributes of plant long non-coding RNAs through a comparative computational approach

Over the past decade, long non-coding RNA (lncRNA), which lacks protein-coding potential, has emerged as an essential regulator of the genome. The present study examined 13,599 lncRNAs in Arabidopsis thaliana, 11,565 in Oryza sativa, and 32,397 in Zea mays for their characteristic features and explored the associated genomic and epigenomic features. We found lncRNAs were distributed throughout the chromosomes and the Helitron family of transposable elements (TEs) enriched, while the terminal inverted repeat depleted in lncRNA transcribing regions. Our analyses determined that lncRNA transcribing regions show rare or weak signals for most epigenetic marks except for H3K9me2 and cytosine methylation in all three plant species. LncRNAs showed preferential localization in the nucleus and cytoplasm; however, the distribution ratio in the cytoplasm and nucleus varies among the studied plant species. We identified several conserved endogenous target mimic sites in the lncRNAs among the studied plants. We found 233, 301, and 273 unique miRNAs, potentially targeting the lncRNAs of A. thaliana, O. sativa, and Z. mays, respectively. Our study has revealed that miRNAs, which interact with lncRNAs, target genes that are involved in a diverse array of biological and molecular processes. The miRNA-targeted lncRNAs displayed a strong affinity for several transcription factors, including ERF and BBR-BPC, mutually present in all three plants, advocating their conserved functions. Overall, the present study showed that plant lncRNAs exhibit conserved genomic and epigenomic characteristics and potentially govern the growth and development of plants.

Imprinted Long Non-Coding RNAs in Mammalian Development and Disease

Imprinted genes play diverse roles in mammalian development, homeostasis, and disease. Most imprinted chromosomal domains express one or more long non-coding RNAs (lncRNAs). Several of these lncRNAs are strictly nuclear and their mono-allelic expression controls in cis the expression of protein-coding genes, often developmentally regulated. Some imprinted lncRNAs act in trans as well, controlling target gene expression elsewhere in the genome. The regulation of imprinted gene expression-including that of imprinted lncRNAs-is susceptible to stochastic and environmentally triggered epigenetic changes in the early embryo. These aberrant changes persist during subsequent development and have long-term phenotypic consequences. This review focuses on the expression and the cis- and trans-regulatory roles of imprinted lncRNAs and describes human disease syndromes associated with their perturbed expression.

Specific topology and topological connection sensitivity enhanced graph learning for lncRNA-disease association prediction

Predicting disease-related candidate long noncoding RNAs (lncRNAs) is beneficial for exploring disease pathogenesis due to the close relations between lncRNAs and the occurrence and development of human diseases. It is a long-term and challenging task to adequately extract specific and local topologies in individual lncRNA network and individual disease network, and integrate the information of the connection relationships. We propose a new graph learning-based prediction method to encode specific and local topologies from each individual network, neighbor topologies with different connection relationships, and pairwise attributes. We first construct a lncRNA network composed of all the lncRNA nodes and their similarities, and a single disease network that contains all the disease nodes and disease similarities. Then, a network-aware graph convolutional autoencoder is constructed to encode the specific and local topologies of each network. Secondly, a heterogeneous network is established to embed all lncRNA, disease, and miRNA nodes and their various connections. Afterwards, a connection-sensitive graph neural network is designed to deeply integrate the neighbor node attributes and connection characteristics in the heterogeneous network and learn neighbor topological representations. We also construct both connection-level and topology representation-level attention mechanisms to extract informative connections and topological representations. Finally, we build a multi-layer convolutional neural networks with weighted residuals to adaptively complement the detailed features to pairwise attribute encoding. Comprehensive experiments and comparison results demonstrated that NCPred outperforms seven state-of-the-art prediction methods. The ablation studies demonstrated the importance of local topology learning, neighbor topology learning, and pairwise attribute encoding. Case studies on prostate, lung, and breast cancers further revealed NCPred's capacity to screen potential candidate disease-related lncRNAs.

Cardiac regeneration - Past advancements, current challenges, and future directions

Cardiovascular disease is the leading cause of mortality and morbidity worldwide. Despite improvements in the standard of care for patients with heart diseases, including innovation in pharmacotherapy and surgical interventions, none have yet been proven effective to prevent the progression to heart failure. Cardiac transplantation is the last resort for patients with severe heart failure, but donor shortages remain a roadblock. Cardiac regenerative strategies include cell-based therapeutics, gene therapy, direct reprogramming of non-cardiac cells, acellular biologics, and tissue engineering methods to restore damaged hearts. Significant advancements have been made over the past several decades within each of these fields. This review focuses on the advancements of: 1) cell-based cardiac regenerative therapies, 2) the use of noncoding RNA to induce endogenous cell proliferation, and 3) application of bioengineering methods to promote retention and integration of engrafted cells. Different cell sources have been investigated, including adult stem cells derived from bone marrow and adipose cells, cardiosphere-derived cells, skeletal myoblasts, and pluripotent stem cells. In addition to cell-based transplantation approaches, there have been accumulating interest over the past decade in inducing endogenous CM proliferation for heart regeneration, particularly with the use of noncoding RNAs such as miRNAs and lncRNAs. Bioengineering applications have focused on combining cell-transplantation approaches with fabrication of a porous, vascularized scaffold using biomaterials and advanced bio-fabrication techniques that may offer enhanced retention of transplanted cells, with the hope that these cells would better engraft with host tissue to improve cardiac function. This review summarizes the present status and future challenges of cardiac regenerative therapies.

Novel insights into the role of long non-coding RNA in the human malaria parasite, Plasmodium falciparum

The complex life cycle of Plasmodium falciparum requires coordinated gene expression regulation to allow host cell invasion, transmission, and immune evasion. Increasing evidence now suggests a major role for epigenetic mechanisms in gene expression in the parasite. In eukaryotes, many lncRNAs have been identified to be pivotal regulators of genome structure and gene expression. To investigate the regulatory roles of lncRNAs in P. falciparum we explore the intergenic lncRNA distribution in nuclear and cytoplasmic subcellular locations. Using nascent RNA expression profiles, we identify a total of 1768 lncRNAs, of which 718 (~41%) are novels in P. falciparum. The subcellular localization and stage-specific expression of several putative lncRNAs are validated using RNA-FISH. Additionally, the genome-wide occupancy of several candidate nuclear lncRNAs is explored using ChIRP. The results reveal that lncRNA occupancy sites are focal and sequence-specific with a particular enrichment for several parasite-specific gene families, including those involved in pathogenesis and sexual differentiation. Genomic and phenotypic analysis of one specific lncRNA demonstrate its importance in sexual differentiation and reproduction. Our findings bring a new level of insight into the role of lncRNAs in pathogenicity, gene regulation and sexual differentiation, opening new avenues for targeted therapeutic strategies against the deadly malaria parasite.