LncATLAS database for subcellular localization of long noncoding RNAs

GP-HTNLoc: A graph prototype head-tail network-based model for multi-label subcellular localization prediction of ncRNAs

Numerous research results demonstrated that understanding the subcellular localization of non-coding RNAs (ncRNAs) is pivotal in elucidating their roles and regulatory mechanisms in cells. Despite the existence of over ten computational models dedicated to predicting the subcellular localization of ncRNAs, a majority of these models are designed solely for single-label prediction. In reality, ncRNAs often exhibit localization across multiple subcellular compartments. Furthermore, the existing multi-label localization prediction models are insufficient in addressing the challenges posed by the scarcity of training samples and class imbalance in ncRNA dataset. To address these limitations, this study proposes a novel multi-label localization prediction model for ncRNAs, named GP-HTNLoc. To mitigate class imbalance, GP-HTNLoc adopts separate training approaches for head and tail location labels. Additionally, GP-HTNLoc introduces a pioneering graph prototype module to enhance its performance in small-sample, multi-label scenarios. The experimental results based on 10-fold cross-validation on benchmark datasets demonstrate that GP-HTNLoc achieves competitive predictive performance. The average results from 10 rounds of testing on an independent dataset show that GP-HTNLoc outperforms the best existing models on the human lncRNA, human snoRNA, and human miRNA subsets, with average precision improvements of 31.5%, 14.2%, and 5.6%, respectively, reaching 0.685, 0.632, and 0.704. A user-friendly online GP-HTNLoc server is accessible at https://56s8y85390.goho.co.

An ontology-based knowledge graph for representing interactions involving RNA molecules

The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

ncStem: a comprehensive resource of curated and predicted ncRNAs in cancer stemness

Cancer stemness plays an important role in cancer initiation and progression, and is the major cause of tumor invasion, metastasis, recurrence, and poor prognosis. Non-coding RNAs (ncRNAs) are a class of RNA transcripts that generally cannot encode proteins and have been demonstrated to play a critical role in regulating cancer stemness. Here, we developed the ncStem database to record manually curated and predicted ncRNAs associated with cancer stemness. In total, ncStem contains 645 experimentally verified entries, including 159 long non-coding RNAs (lncRNAs), 254 microRNAs (miRNAs), 39 circular RNAs (circRNAs), and 5 other ncRNAs. The detailed information of each entry includes the ncRNA name, ncRNA identifier, disease, reference, expression direction, tissue, species, and so on. In addition, ncStem also provides computationally predicted cancer stemness-associated ncRNAs for 33 TCGA cancers, which were prioritized using the random walk with restart (RWR) algorithm based on regulatory and co-expression networks. The total predicted cancer stemness-associated ncRNAs included 11 132 lncRNAs and 972 miRNAs. Moreover, ncStem provides tools for functional enrichment analysis, survival analysis, and cell location interrogation for cancer stemness-associated ncRNAs. In summary, ncStem provides a platform to retrieve cancer stemness-associated ncRNAs, which may facilitate research on cancer stemness and offer potential targets for cancer treatment. Database URL: http://www.nidmarker-db.cn/ncStem/index.html.

Non-coding RNA therapeutics in the treatment of heart failure

Non-coding RNA (ncRNA) therapeutics can target either ncRNAs or conventional messenger RNA, offering both superior pharmacokinetics and selectivity to conventional therapies and addressing new, previously unexplored pathways. Although no ncRNA has yet been approved for the treatment of heart failure, in this review we present five most promising pathways and agents that either are in human clinical trials or offer great promise in the near future.

The comprehensive roles of lncRNA FAM99A/FAM99B in hepatocellular carcinoma: Expressions, regulatory mechanisms and functional pathway analysis

AIMS

The incidence and mortality of liver hepatocellular carcinoma (LIHC) were increasing year by year. The aim of this study was to investigate the comprehensive roles of lncRNA FAM99A and FAM99B in LIHC.

MAIN METHODS

According to the data of TCGA and GTEx, the expression levels of FAM99A and FAM99B in LIHC were evaluated, and the overall survival (OS), disease-free survival (DFS), immune cell infiltration and tumor stage were analyzed. The subcellular localization of FAM99A and FAM99B in various cancer cell lines was predicted by lncATLAS database. In addition, we also used ENCORI, KEGG, LinkedOmics, Metascape and other databases. It was verified by in vivo and in vitro experiments.

KEY FINDINGS

Compared with adjacent normal tissues, FAM99A and FAM99B were down-regulated in LIHC tissues, and significantly correlated with immune cell infiltration. With the progression of tumor stage and grade, the expression of FAM99A and FAM99B showed a decreasing trend, and the prognosis of patients were also poor. In addition, the biological functions, signaling pathways and protein interactions of FAM99A and FAM99B in LIHC were enriched to study the potential molecular mechanisms. The overlapping RNA binding proteins (RBP) of FAM99A and FAM99B mainly included CSTF2T, BCCIP, RBFOX2 and SF3B4. Finally, experiments showed that overexpression of FAM99A attenuated the proliferation, invasion, colony formation and tumor growth of LIHC cells.

SIGNIFICANCE

Taken together, the above studies demonstrated that FAM99A and FAM99B had an inhibitory effect on the progression of LIHC, which might be promising diagnostic biomarkers and therapeutic targets for LIHC patients.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

Revealing the molecular landscape of human placenta: a systematic review and meta-analysis of single-cell RNA sequencing studies

BACKGROUND

With increasing significance of developmental programming effects associated with placental dysfunction, more investigations are devoted to improving the characterization and understanding of placental signatures in health and disease. The placenta is a transitory but dynamic organ adapting to the shifting demands of fetal development and available resources of the maternal supply throughout pregnancy. Trophoblasts (cytotrophoblasts, syncytiotrophoblasts, and extravillous trophoblasts) are placental-specific cell types responsible for the main placental exchanges and adaptations. Transcriptomic studies with single-cell resolution have led to advances in understanding the placenta's role in health and disease. These studies, however, often show discrepancies in characterization of the different placental cell types.

OBJECTIVE AND RATIONALE

We aim to review the knowledge regarding placental structure and function gained from the use of single-cell RNA sequencing (scRNAseq), followed by comparing cell-type-specific genes, highlighting their similarities and differences. Moreover, we intend to identify consensus marker genes for the various trophoblast cell types across studies. Finally, we will discuss the contributions and potential applications of scRNAseq in studying pregnancy-related diseases.

SEARCH METHODS

We conducted a comprehensive systematic literature review to identify different cell types and their functions at the human maternal-fetal interface, focusing on all original scRNAseq studies on placentas published before March 2023 and published reviews (total of 28 studies identified) using PubMed search. Our approach involved curating cell types and subtypes that had previously been defined using scRNAseq and comparing the genes used as markers or identified as potential new markers. Next, we reanalyzed expression matrices from the six available scRNAseq raw datasets with cell annotations (four from first trimester and two at term), using Wilcoxon rank-sum tests to compare gene expression among studies and annotate trophoblast cell markers in both first trimester and term placentas. Furthermore, we integrated scRNAseq raw data available from 18 healthy first trimester and nine term placentas, and performed clustering and differential gene expression analysis. We further compared markers obtained with the analysis of annotated and raw datasets with the literature to obtain a common signature gene list for major placental cell types.

OUTCOMES

Variations in the sampling site, gestational age, fetal sex, and subsequent sequencing and analysis methods were observed between the studies. Although their proportions varied, the three trophoblast types were consistently identified across all scRNAseq studies, unlike other non-trophoblast cell types. Notably, no marker genes were shared by all studies for any of the investigated cell types. Moreover, most of the newly defined markers in one study were not observed in other studies. These discrepancies were confirmed by our analysis on trophoblast cell types, where hundreds of potential marker genes were identified in each study but with little overlap across studies. From 35 461 and 23 378 cells of high quality in the first trimester and term placentas, respectively, we obtained major placental cell types, including perivascular cells that previously had not been identified in the first trimester. Importantly, our meta-analysis provides marker genes for major placental cell types based on our extensive curation.

WIDER IMPLICATIONS

This review and meta-analysis emphasizes the need for establishing a consensus for annotating placental cell types from scRNAseq data. The marker genes identified here can be deployed for defining human placental cell types, thereby facilitating and improving the reproducibility of trophoblast cell annotation.

Cell Type- and Age-Specific Expression of lncRNAs across Kidney Cell Types

Key Points

Background

Accumulated evidence demonstrates that long noncoding RNAs (lncRNAs) regulate cell differentiation and homeostasis, influencing kidney aging and disease. Despite their versatility, the function of lncRNA remains poorly understood because of the lack of a reference map of lncRNA transcriptome in various cell types.

Methods

In this study, we used a targeted single-cell RNA sequencing method to enrich and characterize lncRNAs in individual cells. We applied this method to various mouse tissues, including normal and aged kidneys.

Results

Through tissue-specific clustering analysis, we identified cell type–specific lncRNAs that showed a high correlation with known cell-type marker genes. Furthermore, we constructed gene regulatory networks to explore the functional roles of differentially expressed lncRNAs in each cell type. In the kidney, we observed dynamic expression changes of lncRNAs during aging, with specific changes in glomerular cells. These cell type– and age-specific expression patterns of lncRNAs suggest that lncRNAs may have a potential role in regulating cellular processes, such as immune response and energy metabolism, during kidney aging.

Conclusions

Our study sheds light on the comprehensive landscape of lncRNA expression and function and provides a valuable resource for future analysis of lncRNAs (https://gist-fgl.github.io/sc-lncrna-atlas/).

Molecular insights into regulatory RNAs in the cellular machinery

It is apparent that various functional units within the cellular machinery are derived from RNAs. The evolution of sequencing techniques has resulted in significant insights into approaches for transcriptome studies. Organisms utilize RNA to govern cellular systems, and a heterogeneous class of RNAs is involved in regulatory functions. In particular, regulatory RNAs are increasingly recognized to participate in intricately functioning machinery across almost all levels of biological systems. These systems include those mediating chromatin arrangement, transcription, suborganelle stabilization, and posttranscriptional modifications. Any class of RNA exhibiting regulatory activity can be termed a class of regulatory RNA and is typically represented by noncoding RNAs, which constitute a substantial portion of the genome. These RNAs function based on the principle of structural changes through cis and/or trans regulation to facilitate mutual RNA‒RNA, RNA‒DNA, and RNA‒protein interactions. It has not been clearly elucidated whether regulatory RNAs identified through deep sequencing actually function in the anticipated mechanisms. This review addresses the dominant properties of regulatory RNAs at various layers of the cellular machinery and covers regulatory activities, structural dynamics, modifications, associated molecules, and further challenges related to therapeutics and deep learning.

Long non-coding RNAs in cardiac hypertrophy and heart failure: functions, mechanisms and clinical prospects

The surge in reports describing non-coding RNAs (ncRNAs) has focused attention on their possible biological roles and effects on development and disease. ncRNAs have been touted as previously uncharacterized regulators of gene expression and cellular processes, possibly working to fine-tune these functions. The sheer number of ncRNAs identified has outpaced the capacity to characterize each molecule thoroughly and to reliably establish its clinical relevance; it has, nonetheless, created excitement about their potential as molecular targets for novel therapeutic approaches to treat human disease. In this Review, we focus on one category of ncRNAs - long non-coding RNAs - and their expression, functions and molecular mechanisms in cardiac hypertrophy and heart failure. We further discuss the prospects for this specific class of ncRNAs as novel targets for the diagnosis and treatment of these conditions.

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma

BACKGROUND

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal.

AIM

To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC.

METHODS

The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators.

RESULTS

CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained.

CONCLUSION

This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

Functional identification of cis-regulatory long noncoding RNAs at controlled false discovery rates

A key attribute of some long noncoding RNAs (lncRNAs) is their ability to regulate expression of neighbouring genes in cis. However, such 'cis-lncRNAs' are presently defined using ad hoc criteria that, we show, are prone to false-positive predictions. The resulting lack of cis-lncRNA catalogues hinders our understanding of their extent, characteristics and mechanisms. Here, we introduce TransCistor, a framework for defining and identifying cis-lncRNAs based on enrichment of targets amongst proximal genes. TransCistor's simple and conservative statistical models are compatible with functionally defined target gene maps generated by existing and future technologies. Using transcriptome-wide perturbation experiments for 268 human and 134 mouse lncRNAs, we provide the first large-scale survey of cis-lncRNAs. Known cis-lncRNAs are correctly identified, including XIST, LINC00240 and UMLILO, and predictions are consistent across analysis methods, perturbation types and independent experiments. We detect cis-activity in a minority of lncRNAs, primarily involving activators over repressors. Cis-lncRNAs are detected by both RNA interference and antisense oligonucleotide perturbations. Mechanistically, cis-lncRNA transcripts are observed to physically associate with their target genes and are weakly enriched with enhancer elements. In summary, TransCistor establishes a quantitative foundation for cis-lncRNAs, opening a path to elucidating their molecular mechanisms and biological significance.

Cancer-derived exosomal lncRNA SNHG3 promotes the metastasis of colorectal cancer through hnRNPC-mediating RNA stability of β-catenin

Metastasis is the leading cause of death in colorectal cancer (CRC) patients. By mediating intercellular communication, exosomes exhibit considerable value in regulating tumor metastasis. Long non-coding RNAs (lncRNAs) are abundant in exosomes and participate in regulating tumor progression. However, it is poorly understood how the cancer-secreted exosomal lncRNAs affect CRC proliferation and metastasis. Here, by analyzing the public databases we identified a lncRNA SNHG3 and demonstrated that SNHG3 was delivered through CRC cells-derived exosomes to promote metastasis in CRC. Mechanistically, exosomal SNHG3 was internalized by CRC cells and afterward upregulated the expression of β-catenin by facilitating the intranuclear transport of hnRNPC. Consequently, the RNA stability of β-catenin was enhanced which led to the activation of EMT and metastasis of CRC cells. Our findings expand the oncogenic mechanisms of exosomal SNHG3 and identify it as a diagnostic marker for CRC.

Identification of m6A/m5C-related lncRNA signature for prediction of prognosis and immunotherapy efficacy in esophageal squamous cell carcinoma

N6-methyladenosine (m6A) and 5-methylcytosine (m5C) RNA modifications have garnered significant attention in the field of epigenetic research due to their close association with human cancers. This study we focus on elucidating the expression patterns of m6A/m5C-related long non-coding RNAs (lncRNAs) in esophageal squamous cell carcinoma (ESCC) and assessing their prognostic significance and therapeutic potential. Transcriptomic profiles of ESCC were derived from public resources. m6A/m5C-related lncRNAs were obtained from TCGA using Spearman's correlations analysis. The m6A/m5C-lncRNAs prognostic signature was selected to construct a RiskScore model for survival prediction, and their correlation with the immune microenvironment and immunotherapy response was analyzed. A total of 606 m6A/m5C-lncRNAs were screened, and ESCC cases in the TCGA cohort were stratified into three clusters, which showed significantly distinct in various clinical features and immune landscapes. A RiskScore model comprising ten m6A/m5C-lncRNAs prognostic signature were constructed and displayed good independent prediction ability in validation datasets. Patients in the low-RiskScore group had a better prognosis, a higher abundance of immune cells (CD4 + T cell, CD4 + naive T cell, class-switched memory B cell, and Treg), and enhanced expression of most immune checkpoint genes. Importantly, patients with low-RiskScore were more cline benefit from immune checkpoint inhibitor treatment (P < 0.05). Our findings underscore the potential of RiskScore system comprising ten m6A/m5C-related lncRNAs as effective biomarkers for predicting survival outcomes, characterizing the immune landscape, and assessing response to immunotherapy in ESCC.

Comprehensive analysis identifies long non-coding RNA RNASEH1-AS1 as a potential prognostic biomarker and oncogenic target in hepatocellular carcinoma

RNASEH1-AS1, a long non-coding RNA (lncRNA) divergently transcribed from the antisense strand of its neighboring protein-coding gene ribonuclease H1 (RNASEH1), has recently been demonstrated to be involved in tumor progression. However, the association between RNASEH1-AS1 and hepatocellular carcinoma (HCC) remains unclear. In the present study, first, the expression of RNASEH1-AS1 in HCC and its correlation with clinicopathological features, prognosis, diagnosis, immune cell infiltration of HCC patients was inspected using relevant R packages based on The Cancer Genome Atlas (TCGA) data. RNASEH1-AS1 was found to be up-regulated in most cancer types, including HCC, and its overexpression was significantly associated with histologic grade and AFP level as well as poor prognosis, and was an independent risk factor affecting overall survival with good diagnostic and prognostic values for HCC. RNASEH1-AS1 was inversely associated with the infiltration of most immune cell types, including plasmacytoid dendritic cells (pDC), B cells and neutrophils. Second, a total of 1109 positively co-expressed genes (PCEGs) of RNASEH1-AS1 were screened out in HCC by correlation analysis in batches (|Spearman's r| >0.4 and adjusted P value <0.01). GO and KEGG enrichment analysis indicated that PCEGs of RNASEH1-AS1 were mainly related to RNA processing, ribosome biogenesis, transcription and histone acetylation. The top 10 hub genes (EIF4A3, WDR43, WDR12, DKC1, NAT10, UTP18, DDX18, BYSL, DDX10, PDCD11) were identified by constructing the protein-protein interaction (PPI) network, and they were all highly expressed in HCC and positively correlated with histological grade. Third, a risk model was constructed based on four RNASEH1-AS1-related hub genes (EIF4A3, WDR12, DKC1, and NAT10) with good prognostic predictive potential via univariate Cox and the least absolute selection operator (LASSO) regression analysis. Fourth, experimental validation revealed that RNASEH1-AS1 was significantly elevated in HCC tissues and several cell lines, and its knockdown could suppress the proliferation, migration, and invasion of HCC cells. Finally, mechanistic studies demonstrated that the stability of RNASEH1-AS1 could be regulated by DKC1 via their direct interaction. Taken together, RNASEH1-AS1 may serve as a potential prognostic and diagnostic biomarker and oncogenic lncRNA for HCC.

A comprehensive database of exosome molecular biomarkers and disease-gene associations

Exosomes play a crucial role in intercellular communication and can be used as biomarkers for diagnostic and therapeutic clinical applications. However, systematic studies in cancer-associated exosomal nucleic acids remain a big challenge. Here, we developed ExMdb, a comprehensive database of exosomal nucleic acid biomarkers and disease-gene associations curated from published literature and high-throughput datasets. We performed a comprehensive curation of exosome properties including 4,586 experimentally supported gene-disease associations, 13,768 diagnostic and therapeutic biomarkers, and 312,049 nucleic acid subcellular locations. To characterize expression variation of exosomal molecules and identify causal factors of complex diseases, we have also collected 164 high-throughput datasets, including bulk and single-cell RNA sequencing (scRNA-seq) data. Based on these datasets, we performed various bioinformatics and statistical analyses to support our conclusions and advance our knowledge of exosome biology. Collectively, our dataset will serve as an essential resource for investigating the regulatory mechanisms of complex diseases and improving the development of diagnostic and therapeutic biomarkers.

Pan-cancer analyses identify MIR210HG overexpression, epigenetic regulation and oncogenic role in human tumors and its interaction with the tumor microenvironment

BACKGROUND

Molecular entities showing dysregulation in multiple cancers may hold great biomarker or therapeutic potential. There is accumulating evidence that highlights the dysregulation of a long non-coding RNA, MIR210HG, in various cancers and its oncogenic role. However, a comprehensive analysis of MIR210HG expression pattern, molecular mechanisms, diagnostic or prognostic significance or evaluation of its interaction with tumor microenvironment across various cancers remains unstudied.

METHODS

A systematic pan-cancer analysis was done using multiple public databases and bioinformatic tools to study the molecular role and clinical significance of MIR210HG. We have analyzed expression patterns, genome alteration, transcriptional and epigenetic regulation, correlation with patient survival, immune infiltrates, co-expressed genes, interacting proteins, and pathways associated with MIR210HG.

RESULTS

The Pan cancer expression analysis of MIR210HG through various tumor datasets demonstrated that MIR210HG is significantly upregulated in most cancers and increased with the tumor stage in a subset of them. Furthermore, prognostic analysis revealed high MIR210HG expression is associated with poor overall and disease-free survival in specific cancer types. Genetic alteration analysis showed minimal alterations in the MIR210HG locus, indicating that overexpression in cancers is not due to gene amplification. The exploration of SNPs on MIR210HG suggested possible structural changes that may affect its interactions with the miRNAs. The correlation of MIR210HG with promoter methylation was found to be significantly negative in nature in majority of cancers depicting the possible epigenetic regulation of expression of MIR210HG. Additionally, MIR210HG showed negative correlations with immune cells and thus may have strong impact on the tumor microenvironment. Functional analysis indicates its association with hypoxia, angiogenesis, metastasis, and DNA damage repair processes. MIR210HG was found to interact with several proteins and potentially regulate chromatin modifications and transcriptional regulation.

CONCLUSIONS

A first pan-can cancer analysis of MIR210HG highlights its transcriptional and epigenetic deregulation and oncogenic role in the majority of cancers, its correlation with tumor microenvironment factors such as hypoxia and immune infiltration, and its potential as a prognostic biomarker and therapeutic target in several cancers.

MRSLpred-a hybrid approach for predicting multi-label subcellular localization of mRNA at the genome scale

In the past, several methods have been developed for predicting the single-label subcellular localization of messenger RNA (mRNA). However, only limited methods are designed to predict the multi-label subcellular localization of mRNA. Furthermore, the existing methods are slow and cannot be implemented at a transcriptome scale. In this study, a fast and reliable method has been developed for predicting the multi-label subcellular localization of mRNA that can be implemented at a genome scale. Machine learning-based methods have been developed using mRNA sequence composition, where the XGBoost-based classifier achieved an average area under the receiver operator characteristic (AUROC) of 0.709 (0.668-0.732). In addition to alignment-free methods, we developed alignment-based methods using motif search techniques. Finally, a hybrid technique that combines the XGBoost model and the motif-based approach has been developed, achieving an average AUROC of 0.742 (0.708-0.816). Our method-MRSLpred-outperforms the existing state-of-the-art classifier in terms of performance and computation efficiency. A publicly accessible webserver and a standalone tool have been developed to facilitate researchers (webserver: https://webs.iiitd.edu.in/raghava/mrslpred/).

Role of UPF1 in lncRNA-HEIH regulation for hepatocellular carcinoma therapy

UPF1, a novel posttranscriptional regulator, regulates the abundance of transcripts, including long noncoding RNAs (lncRNAs), and thus plays an important role in cell homeostasis. In this study, we revealed that UPF1 regulates the abundance of hepatocellular carcinoma upregulated EZH2-associated lncRNA (lncRNA-HEIH) by binding the CG-rich motif, thereby regulating hepatocellular carcinoma (HCC) tumorigenesis. UPF1-bound lncRNA-HEIH was susceptible to degradation mediated by UPF1 phosphorylation via SMG1 and SMG5. According to analysis of RNA-seq and public data on patients with liver cancer, the expression of lncRNA-HEIH increased the levels of miR-194-5p targets and was inversely correlated with miR-194-5p expression in HCC patients. Furthermore, UPF1 depletion upregulated lncRNA-HEIH, which acts as a decoy of miR-194-5p that targets GNA13, thereby promoting GNA13 expression and HCC proliferation. The UPF1/lncRNA-HEIH/miR-194-5p/GNA13 regulatory axis is suggested to play a crucial role in cell progression and may be a suitable target for HCC therapy.

The long noncoding RNA HNF1A-AS1 with dual functions in the regulation of cytochrome P450 3A4

Cytochrome P450 3A4 (CYP3A4) is the most important and abundant drug-metabolizing enzyme in the human liver. Inter-individual differences in the expression and activity of CYP3A4 affect clinical and precision medicine. Increasing evidence indicates that long noncoding RNAs (lncRNAs) play crucial roles in the regulation of CYP3A4 expression. Here, we showed that lncRNA hepatocyte nuclear factor 1 alpha-antisense 1 (HNF1A-AS1) exerted dual functions in regulating CYP3A4 expression in Huh7 and HepG2 cells. Mechanistically, HNF1A-AS1 served as an RNA scaffold to interact with both protein arginine methyltransferase 1 and pregnane X receptor (PXR), thereby facilitating their protein interactions and resulting in the transactivation of PXR and transcriptional alteration of CYP3A4 via histone modifications. Furthermore, HNF1A-AS1 bound to the HNF1A protein, a liver-specific transcription factor, thereby blocking its interaction with the E3 ubiquitin ligase tripartite motif containing 25, ultimately preventing HNF1A ubiquitination and protein degradation, further regulating the expression of CYP3A4. In summary, these results reveal the novel functions of HNF1A-AS1 as the transcriptional and post-translational regulator of CYP3A4; thus, HNF1A-AS1 may serve as a new indicator for establishing or predicting individual differences in CYP3A4 expression.

Beyond ribosome biogenesis: noncoding nucleolar RNAs in physiology and tumor biology

The nucleolus, the largest subcompartment of the nucleus, stands out from the nucleoplasm due to its exceptionally high local RNA and low DNA concentrations. Within this central hub of nuclear RNA metabolism, ribosome biogenesis is the most prominent ribonucleoprotein (RNP) biogenesis process, critically determining the structure and function of the nucleolus. However, recent studies have shed light on other roles of the nucleolus, exploring the interplay with various noncoding RNAs that are not directly involved in ribosome synthesis. This review focuses on this intriguing topic and summarizes the techniques to study and the latest findings on nucleolar long noncoding RNAs (lncRNAs) as well as microRNAs (miRNAs) in the context of nucleolus biology beyond ribosome biogenesis. We particularly focus on the multifaceted roles of the nucleolus and noncoding RNAs in physiology and tumor biology.

LncRNA ABHD11-AS1 activates EGFR signaling to promote cervical cancer progression by preventing FUS-mediated degradation of ABHD11 mRNA

Cervical cancer is one of the most common gynecological cancers with high metastasis, poor prognosis and conventional chemotherapy. The long non-coding RNA (lncRNA) ABHD11 antisense RNA 1 (ABHD11-AS1) plays a vital role in tumorigenesis and is involved in cell proliferation, differentiation, and apoptosis. Especially for cervical cancer, the functions and mechanisms of ABHD11-AS1 are still undetermined. In this study, we explored the role and underlying mechanism of ABHD11-AS1 in cervical cancer. We found that ABHD11-AS1 is highly expressed in cervical cancer tissue. The roles of ABHD11-AS1 and EGFR have investigated the loss of function analysis and cell movability in SiHa and Hela cells. Knockdown of ABHD11-AS1 and EGFR significantly inhibited the proliferation, migration, and invasion and promoted apoptosis of SiHa and Hela cells by up-regulating p21 and Bax and down-regulating cyclin D1, Bcl2, MMP9, and Vimentin. ABHD11-AS1 knockdown could decrease the expression of EGFR. In addition, ABHD11-AS1 could regulate the EGFR signaling pathway, including p-EGFR, p-AKT, and p-ERK. Spearman's correlation analysis and cell experiments demonstrated that ABHD11 was highly expressed in tumor tissue and partially offset the effect of shABHD11-AS1 on the proliferation, migration, and invasion of SiHa and Hela cells. Then, RNA pulldown was used to ascertain the mechanisms of ABHD11-AS1 and FUS. ABHD11-AS1 inhibited ABHD11 mRNA degradation by bounding to FUS. A subcutaneous xenograft of SiHa cells was established to investigate the effect of ABHD11-AS1 in tumor tissue. Knockdown of ABDH11-AS1 inhibited tumor growth and decreased the tumor volume. ABHD11-AS1 knockdown inhibited the expression of Ki67 and Vimentin and up-regulated the expression of Tunel. Our data indicated that ABHD11-AS1 promoted cervical cancer progression by activating EGFR signaling, preventing FUS-mediated degradation of ABHD11 mRNA. Our findings provide novel insights into the potential role of lncRNA in cervical cancer therapy.

Exploration of the Noncoding Genome for Human-Specific Therapeutic Targets-Recent Insights at Molecular and Cellular Level

While it is well known that 98-99% of the human genome does not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs [ncRNAs] with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two topics of high current interest: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel therapeutic targets in human diseases? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the profound interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with remarkable recent progress regarding delivery, efficacy, and safety of nucleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.

DlncRNALoc: A discrete wavelet transform-based model for predicting lncRNA subcellular localization

The prediction of long non-coding RNA (lncRNA) subcellular localization is essential to the understanding of its function and involvement in cellular regulation. Traditional biological experimental methods are costly and time-consuming, making computational methods the preferred approach for predicting lncRNA subcellular localization (LSL). However, existing computational methods have limitations due to the structural characteristics of lncRNAs and the uneven distribution of data across subcellular compartments. We propose a discrete wavelet transform (DWT)-based model for predicting LSL, called DlncRNALoc. We construct a physicochemical property matrix of a 2-tuple bases based on lncRNA sequences, and we introduce a DWT lncRNA feature extraction method. We use the Synthetic Minority Over-sampling Technique (SMOTE) for oversampling and the local fisher discriminant analysis (LFDA) algorithm to optimize feature information. The optimized feature vectors are fed into support vector machine (SVM) to construct a predictive model. DlncRNALoc has been applied for a five-fold cross-validation on the three sets of benchmark datasets. Extensive experiments have demonstrated the superiority and effectiveness of the DlncRNALoc model in predicting LSL.

ncRNALocate-EL: a multi-label ncRNA subcellular locality prediction model based on ensemble learning

Subcellular localizations of ncRNAs are associated with specific functions. Currently, an increasing number of biological researchers are focusing on computational approaches to identify subcellular localizations of ncRNAs. However, the performance of the existing computational methods is low and needs to be further studied. First, most prediction models are trained with outdated databases. Second, only a few predictors can identify multiple subcellular localizations simultaneously. In this work, we establish three human ncRNA subcellular datasets based on the latest RNALocate, including lncRNA, miRNA and snoRNA, and then we propose a novel multi-label classification model based on ensemble learning called ncRNALocate-EL to identify multi-label subcellular localizations of three ncRNAs. The results show that the ncRNALocate-EL outperforms previous methods. Our method achieved an average precision of 0.709,0.977 and 0.730 on three human ncRNA datasets. The web server of ncRNALocate-EL has been established, which can be accessed at https://bliulab.net/ncRNALocate-EL.

Long noncoding RNA study: Genome-wide approaches

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.

Construction of a Novel Cuproptosis-Related ceRNA Network-SNHG3/miR-1306-5p/PDHA1 and Identification of SNHG3 as a Prognostic Biomarker in Hepatocellular Carcinoma

The crucial role of competitive endogenous RNA (ceRNA) in the malignant biological behavior of tumors has been certificated. Nevertheless, the detailed function and molecular mechanism of ceRNA associated with cuproptosis in hepatocellular carcinoma (HCC) remains dismal. In this study, we first constructed a protein-protein interaction network and identified the module with the highest degree of aggregation degree. DLAT and PDHA1 were screened out of the module after differential expression and survival analysis. Next, we reverse-predicted the upstream miRNA and lncRNA from mRNA (DLAT, PDHA1) and successfully established the ceRNA network-SNHG3/miR-1306-5p/PDHA1. SNHG3 was identified to be an independent prognostic biomarker based on the outcome of univariate and multivariate Cox analyses. Subsequently, we implemented methylation, immune infiltration, and drug sensitivity analysis to investigate the potential biological functions of SNHG3 in HCC. In addition, SNHG3 expression was upregulated in liver cancer cell lines. In vitro functional assay revealed that SNHG3 knockdown significantly attenuated proliferation, migration, and invasion of liver cancer cells. In summary, SNHG3 exhibited oncogenic characterization via sponging miR-1306-5p to regulate PDHA1, which might function as a promising prognostic indicator and a potential therapeutic target for HCC and shed new light on the molecular mechanism of HCC progression.

Analysis of shared ceRNA networks and related-hub genes in rats with primary and secondary photoreceptor degeneration

Introduction

Photoreceptor degenerative diseases are characterized by the progressive death of photoreceptor cells, resulting in irreversible visual impairment. However, the role of competing endogenous RNA (ceRNA) in photoreceptor degeneration is unclear. We aimed to explore the shared ceRNA regulation network and potential molecular mechanisms between primary and secondary photoreceptor degenerations.

Methods

We established animal models for both types of photoreceptor degenerations and conducted retina RNA sequencing to identify shared differentially expressed long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs). Using ceRNA regulatory principles, we constructed a shared ceRNA network and performed function enrichment and protein-protein interaction (PPI) analyses to identify hub genes and key pathways. Immune cell infiltration and drug-gene interaction analyses were conducted, and hub gene expression was validated by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

We identified 37 shared differentially expressed lncRNAs, 34 miRNAs, and 247 mRNAs and constructed a ceRNA network consisting of 3 lncRNAs, 5 miRNAs, and 109 mRNAs. Furthermore, we examined 109 common differentially expressed genes (DEGs) through functional annotation, PPI analysis, and regulatory network analysis. We discovered that these diseases shared the complement and coagulation cascades pathway. Eight hub genes were identified and enriched in the immune system process. Immune infiltration analysis revealed increased T cells and decreased B cells in both photoreceptor degenerations. The expression of hub genes was closely associated with the quantities of immune cell types. Additionally, we identified 7 immune therapeutical drugs that target the hub genes.

Discussion

Our findings provide new insights and directions for understanding the common mechanisms underlying the development of photoreceptor degeneration. The hub genes and related ceRNA networks we identified may offer new perspectives for elucidating the mechanisms and hold promise for the development of innovative treatment strategies.

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.

A New Understanding of Long Non-Coding RNA in Hepatocellular Carcinoma-From m6A Modification to Blood Biomarkers

With recent advancements in biological research, long non-coding RNAs (lncRNAs) with lengths exceeding 200 nucleotides have emerged as pivotal regulators of gene expression and cellular phenotypic modulation. Despite initial skepticism due to their low sequence conservation and expression levels, their significance in various biological processes has become increasingly apparent. We provided an overview of lncRNAs and discussed their defining features and modes of operation. We then explored their crucial function in the hepatocarcinogenesis process, elucidating their complex involvement in hepatocellular carcinoma (HCC). The influential role of lncRNAs within the HCC tumor microenvironment is emphasized, illustrating their potential as key modulators of disease dynamics. We also investigated the significant influence of N6-methyladenosine (m6A) modification on lncRNA function in HCC, enhancing our understanding of both their roles and their upstream regulators. Additionally, the potential of lncRNAs as promising biomarkers was discussed in liver cancer diagnosis, suggesting a novel avenue for future research and clinical application. Finally, our work underscored the dual potential of lncRNAs as both contributors to HCC pathogenesis and innovative tools for its diagnosis. Existing challenges and prospective trajectories in lncRNA research are also discussed, emphasizing their potential in advancing liver cancer research.

Systematic Analysis of Long Non-Coding RNAs in Inflammasome Activation in Monocytes/Macrophages

The NLRP3 inflammasome plays a pivotal role in regulating inflammation and immune responses. Its activation can lead to an inflammatory response and pyroptotic cell death. This is beneficial in the case of infections, but excessive activation can lead to chronic inflammation and tissue damage. Moreover, while most of the mammalian genome is transcribed as RNAs, only a small fraction codes for proteins. Among non-protein-coding RNAs, long non-coding RNAs (lncRNAs) have been shown to play key roles in regulating gene expression and cellular processes. They interact with DNA, RNAs, and proteins, and their dysregulation can provide insights into disease mechanisms, including NLRP3 inflammasome activation. Here, we systematically analyzed previously published RNA sequencing (RNA-seq) data of NLRP3 inflammasome activation in monocytes/macrophages to uncover inflammasome-regulated lncRNA genes. To uncover the functional importance of inflammasome-regulated lncRNA genes, one inflammasome-regulated lncRNA, ENSG00000273124, was knocked down in an in vitro model of macrophage polarization. The results indicate that silencing of ENSG00000273124 resulted in the up-regulation tumor necrosis factor (TNF), suggesting that this lncRNA might be involved in pro-inflammatory response in macrophages. To make our analyzed data more accessible, we developed the web database InflammasomeDB.

In Silico Identification of Potential Quadruplex Forming Sequences in LncRNAs of Cervical Cancer

Long non-coding RNAs (lncRNAs) have emerged as auxiliary regulators of gene expression influencing tumor microenvironment, metastasis and radio-resistance in cancer. The presence of lncRNA in extracellular fluids makes them promising diagnostic markers. LncRNAs deploy higher-order structures to facilitate a complex range of functions. Among such structures, G-quadruplexes (G4s) can be detected or targeted by small molecular probes to drive theranostic applications. The in vitro identification of G4 formation in lncRNAs can be a tedious and expensive proposition. Bioinformatics-driven strategies can provide comprehensive and economic alternatives in conjunction with suitable experimental validation. We propose a pipeline to identify G4-forming sequences, protein partners and biological functions associated with dysregulated lncRNAs in cervical cancer. We identified 17 lncRNA clusters which possess transcripts that can fold into a G4 structure. We confirmed in vitro G4 formation in the four biologically active isoforms of SNHG20, MEG3, CRNDE and LINP1 by Circular Dichroism spectroscopy and Thioflavin-T-assisted fluorescence spectroscopy and reverse-transcriptase stop assay. Gene expression data demonstrated that these four lncRNAs can be potential prognostic biomarkers of cervical cancer. Two approaches were employed for identifying G4 specific protein partners for these lncRNAs and FMR2 was a potential interacting partner for all four clusters. We report a detailed investigation of G4 formation in lncRNAs that are dysregulated in cervical cancer. LncRNAs MEG3, CRNDE, LINP1 and SNHG20 are shown to influence cervical cancer progression and we report G4 specific protein partners for these lncRNAs. The protein partners and G4s predicted in lncRNAs can be exploited for theranostic objectives.

A concise review on the role of MIR100HG in human disorders

MIR100HG is a long non-coding RNA (lncRNA) encoded by a locus on chr11:122,028,203-122,556,721. This gene can regulate cell proliferation, apoptosis, cell cycle transition and cell differentiation. MIR100HG was firstly identified through a transcriptome analysis and found to regulate differentiation of human neural stem cells. It is functionally related with a number of signalling pathways such as TGF-β, Wnt, Hippo and ERK/MAPK signalling pathways. Dysregulation of MIR100HG has been detected in a diversity of cancers in association with clinical outcomes. Moreover, it has a role in the pathophysiology of dilated cardiomyopathy, intervertebral disk degeneration and pulmonary fibrosis. The current study summarizes the role of these lncRNAs in human disorders.

A review from biological mapping to computation-based subcellular localization

Subcellular localization is crucial to the study of virus and diseases. Specifically, research on protein subcellular localization can help identify clues between virus and host cells that can aid in the design of targeted drugs. Research on RNA subcellular localization is significant for human diseases (such as Alzheimer's disease, colon cancer, etc.). To date, only reviews addressing subcellular localization of proteins have been published, which are outdated for reference, and reviews of RNA subcellular localization are not comprehensive. Therefore, we collated (the most up-to-date) literature on protein and RNA subcellular localization to help researchers understand changes in the field of protein and RNA subcellular localization. Extensive and complete methods for constructing subcellular localization models have also been summarized, which can help readers understand the changes in application of biotechnology and computer science in subcellular localization research and explore how to use biological data to construct improved subcellular localization models. This paper is the first review to cover both protein subcellular localization and RNA subcellular localization. We urge researchers from biology and computational biology to jointly pay attention to transformation patterns, interrelationships, differences, and causality of protein subcellular localization and RNA subcellular localization.

LncRNA AK001796 promotes cell proliferation via acting as a ceRNA of miR-150 in hepatocellular carcinoma

Long non-coding RNA AK001796 was initially identified altered in lung cancer. Recent research showed it could participate in the prognosis of hepatocellular carcinoma (HCC). However, the general biological role of AK001796 and its underlying mechanisms in HCC remain unclear. Here we demonstrated that the expression level of AK001796 in HCC tissues and cell lines was up-regulated. Silencing AK001796 suppressed the proliferation ability of HCC cells. Through dual luciferase reporter assays and loss/gain of functions studies, we identified that AK001796 could bind to miR-150, a star microRNA, promoting HCC proliferation. Furthermore, it was reported that growth factor receptor binding protein 2-associated binder 1 (GAB1) is a target gene of miR-150. Owing to AK001796 being a decoy for miR-150 and binding the same putative sites of miR-150 as GAB1, we presented that inhibition of miR-150 in AK001796 silencing cells reversed the reduction in GAB1. Subsequently, our findings demonstrated that silencing AK001796 can impair phospho-ERK1/2 and phospho-AKT. In conclusion, our investigation revealed that AK001796 promoted proliferation by enhancing phospho-ERK1/2 and phospho-AKT through AK001796/miR-150/GAB1 axis in HCC. These results provided further evidence for the critical roles of AK001796 accumulating HCC and suggested that AK001796 might act as an HCC biomarker in clinical treatment.

Long non-coding RNAs: definitions, functions, challenges and recommendations

Genes specifying long non-coding RNAs (lncRNAs) occupy a large fraction of the genomes of complex organisms. The term 'lncRNAs' encompasses RNA polymerase I (Pol I), Pol II and Pol III transcribed RNAs, and RNAs from processed introns. The various functions of lncRNAs and their many isoforms and interleaved relationships with other genes make lncRNA classification and annotation difficult. Most lncRNAs evolve more rapidly than protein-coding sequences, are cell type specific and regulate many aspects of cell differentiation and development and other physiological processes. Many lncRNAs associate with chromatin-modifying complexes, are transcribed from enhancers and nucleate phase separation of nuclear condensates and domains, indicating an intimate link between lncRNA expression and the spatial control of gene expression during development. lncRNAs also have important roles in the cytoplasm and beyond, including in the regulation of translation, metabolism and signalling. lncRNAs often have a modular structure and are rich in repeats, which are increasingly being shown to be relevant to their function. In this Consensus Statement, we address the definition and nomenclature of lncRNAs and their conservation, expression, phenotypic visibility, structure and functions. We also discuss research challenges and provide recommendations to advance the understanding of the roles of lncRNAs in development, cell biology and disease.

Topologically associating domain underlies tissue specific expression of long intergenic non-coding RNAs

Accumulating evidence indicates that long intergenic non-coding RNAs (lincRNAs) show more tissue-specific expression patterns than protein-coding genes (PCGs). However, although lincRNAs are subject to canonical transcriptional regulation like PCGs, the molecular basis for the specificity of their expression patterns remains unclear. Here, using expression data and coordinates of topologically associating domains (TADs) in human tissues, we show that lincRNA loci are significantly enriched in the more internal region of TADs compared to PCGs and that lincRNAs within TADs have higher tissue specificity than those outside TADs. Based on these, we propose an analytical framework to interpret transcriptional status using lincRNA as an indicator. We applied it to hypertrophic cardiomyopathy data and found disease-specific transcriptional regulation: ectopic expression of keratin at the TAD level and derepression of myocyte differentiation-related genes by E2F1 with down-regulation of LINC00881. Our results provide understanding of the function and regulation of lincRNAs according to genomic structure.

Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment

According to the World Health Organization, every year, an estimated 400,000+ new cancer cases affect children under the age of 20 worldwide. Unlike adult cancers, pediatric cancers develop very early in life due to alterations in signaling pathways that regulate embryonic development, and environmental factors do not contribute much to cancer development. The highly organized complex microenvironment controlled by synchronized gene expression patterns plays an essential role in the embryonic stages of development. Dysregulated development can lead to tumor initiation and growth. The low mutational burden in pediatric tumors suggests the predominant role of epigenetic changes in driving the cancer phenotype. However, one more upstream layer of regulation driven by ncRNAs regulates gene expression and signaling pathways involved in the development. Deregulation of ncRNAs can alter the epigenetic machinery of a cell, affecting the transcription and translation profiles of gene regulatory networks required for cellular proliferation and differentiation during embryonic development. Therefore, it is essential to understand the role of ncRNAs in pediatric tumor development to accelerate translational research to discover new treatments for childhood cancers. This review focuses on the role of ncRNA in regulating the epigenetics of pediatric tumors and their tumor microenvironment, the impact of their deregulation on driving pediatric tumor progress, and their potential as effective therapeutic targets.

HDAC1 participates in polycystic ovary syndrome through histone modification to regulate H19/miR-29a-3p/NLRP3-mediated granulosa cell pyroptosis

Histone deacetylase 1 (HDAC1) is known to participate in the molecular etiology of polycystic ovary syndrome (PCOS). However, its role in granulosa cell (GC) pyroptosis remains unclear. This study sought to investigate the mechanism of HDAC1 in PCOS-induced GC pyroptosis through histone modification. Clinical serum samples and the general data of study subjects were collected. PCOS mouse models were established using dehydroepiandrosterone and cell models were established in HGL5 cells using dihydrotestosterone. Expressions of HDAC1, H19, miR-29a-3p, and NLR family pyrin domain containing 3 (NLRP3) and pyroptosis-related proteins and levels of hormones and inflammatory cytokines were determined. Ovarian damage was observed by hematoxylin-eosin staining. Functional rescue experiments were conducted to verify the role of H19/miR-29a-3p/NLRP3 in GC pyroptosis in PCOS. HDAC1 and miR-29a-3p were downregulated whereas H19 and NLRP3 were upregulated in PCOS. HDAC1 upregulation attenuated ovarian damage and hormone disorders in PCOS mice and suppressed pyroptosis in ovarian tissues and HGL5 cells. HDAC1 inhibited H3K9ac on the H19 promoter and H19 competitively bound to miR-29a-3p to improve NLRP3 expression. Overexpressed H19 or NLRP3 or inhibited miR-29a-3p reversed the inhibition of GC pyroptosis by HDAC1 upregulation. Overall, HDAC1 suppressed GC pyroptosis in PCOS through deacetylation to regulate the H19/miR-29a-3p/NLRP3 axis.

Decoding the lncRNAome Across Diverse Cellular Stresses Reveals Core p53-effector Pan-cancer Suppressive lncRNAs

Despite long non-coding RNAs (lncRNAs) emerging as key contributors to malignancies, their transcriptional regulation, tissue-type expression under different conditions, and functions remain largely unknown. Developing a combined computational and experimental framework, which integrates pan-cancer RNAi/CRISPR screens, and genomic, epigenetic, and expression profiles (including single-cell RNA sequencing), we report across multiple cancers, core p53-transcriptionally regulated lncRNAs, which were thought to be primarily cell/tissue-specific. These lncRNAs were consistently directly transactivated by p53 with different cellular stresses in multiple cell types and associated with pan-cancer cell survival/growth suppression and patient survival. Our prediction results were verified through independent validation datasets, our own patient cohort, and cancer cell experiments. Moreover, a top predicted p53-effector tumor-suppressive lncRNA (we termed PTSL) inhibited cell proliferation and colony formation by modulating the G₂ regulatory network, causing G₂ cell-cycle arrest. Therefore, our results elucidated previously unreported, high-confidence core p53-targeted lncRNAs that suppress tumorigenesis across cell types and stresses.

Significance

Identification of pan-cancer suppressive lncRNAs transcriptionally regulated by p53 across different cellular stresses by integrating multilayered high-throughput molecular profiles. This study provides critical new insights into the p53 tumor suppressor by revealing the lncRNAs in the p53 cell-cycle regulatory network and their impact on cancer cell growth and patient survival.

A desert lncRNA HIDEN regulates human endoderm differentiation via interacting with IMP1 and stabilizing FZD5 mRNA

BACKGROUND

Extensive studies have revealed the function and mechanism of lncRNAs in development and differentiation, but the majority have focused on those lncRNAs adjacent to protein-coding genes. In contrast, lncRNAs located in gene deserts are rarely explored. Here, we utilize multiple differentiation systems to dissect the role of a desert lncRNA, HIDEN (human IMP1-associated "desert" definitive endoderm lncRNA), in definitive endoderm differentiation from human pluripotent stem cells.

RESULTS

We show that desert lncRNAs are highly expressed with cell-stage-specific patterns and conserved subcellular localization during stem cell differentiation. We then focus on the desert lncRNA HIDEN which is upregulated and plays a vital role during human endoderm differentiation. We find depletion of HIDEN by either shRNA or promoter deletion significantly impairs human endoderm differentiation. HIDEN functionally interacts with RNA-binding protein IMP1 (IGF2BP1), which is also required for endoderm differentiation. Loss of HIDEN or IMP1 results in reduced WNT activity, and WNT agonist rescues endoderm differentiation deficiency caused by the depletion of HIDEN or IMP1. Moreover, HIDEN depletion reduces the interaction between IMP1 protein and FZD5 mRNA and causes the destabilization of FZD5 mRNA, which is a WNT receptor and necessary for definitive endoderm differentiation.

CONCLUSIONS

These data suggest that desert lncRNA HIDEN facilitates the interaction between IMP1 and FZD5 mRNA, stabilizing FZD5 mRNA which activates WNT signaling and promotes human definitive endoderm differentiation.

Identification of immunotherapy-related lncRNA signature for predicting prognosis, immunotherapy responses and drug candidates in bladder cancer

BACKGROUND

Bladder cancer (BC) is one of the most common malignant diseases and the most common causes of cancer death worldwide. Immunotherapy has opened new avenues for precision treatment of bladder tumours, and immune checkpoint inhibitors (ICIs) have revolutionized the clinical treatment strategy of bladder tumours. In addition, long non-coding RNA (lncRNA) plays an important role in regulating tumour development and immunotherapy efficacy.

METHODS

We obtained genes with significant differences between anti-PD-L1 response and non-response from the Imvogor210 data set and combined with the bladder cancer expression data in the TCGA cohort to obtain immunotherapy-related lncRNA. Based on these lncRNAs, the prognostic risk model of bladder cancer was constructed and verified by GEO external data set. The characterization of immune cell infiltration and immunotherapy effects between high-risk and low-risk groups were then analysed. We predicted the ceRNA network and performed molecular docking of key target proteins. The functional experiments verified the function of SBF2-AS1.

RESULTS

Three immunotherapy-related lncRNAs were identified as independent prognostic biomarkers for bladder cancer and a prognostic model of immunotherapy-related prognosis was constructed. Prognosis, immune cell infiltration, and immunotherapy efficacy were significantly different between high- and low-risk groups based on risk scores. Additionally, we established a ceRNA network of lncRNA(SBF2-AS1)-miRNA(has-miR-582-5p)-mRNA (HNRNPA2B1). Targeting the protein HNRNPA2B1 identified the top eight small molecule drugs with the highest affinity.

CONCLUSION

We developed a prognostic risk score model based on immune-therapy-related lncRNA, which was subsequently determined to be significantly associated with immune cell infiltration and immunotherapy response. This study not only helps to promote our understanding of immunotherapy-related lncRNA in the prognosis of BC, but also provides new ideas for clinical immunotherapy and the development of novel therapeutic drugs for patients.

Mechanisms of circRNA/lncRNA-miRNA interactions and applications in disease and drug research

In recent years, breakthroughs in bioinformatics have been made with the discovery of many functionally significant non-coding RNAs (ncRNAs). The discovery of these ncRNAs has further demonstrated the multi-level characteristics of intracellular gene expression regulation, which plays an important role in assisting diagnosis, guiding clinical drug use and determining prognosis in the treatment process of various diseases. microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) are the three major types of ncRNAs that interact with each other. Studies have shown that lncRNAs and circRNAs can sponge miRNAs, thereby influencing normal physiological processes and regulating mRNA expression and, thus, the physiological state of cells. This paper summarizes the mechanism of action and research progress of the three ncRNA and seven types of modalities. This summary is intended to provide new ideas for diagnosing and treating diseases and researching and developing new drugs.

LncRNA DGUOK-AS1 facilitates non-small cell lung cancer growth and metastasis through increasing TRPM7 stability via m6A modification

BACKGROUND

N6-methyladenosine (m6A) modification plays key roles in tumor progression. LncRNA deoxyguanosine kinase antisense RNA 1 (DGUOK-AS1) has been reported as a promoter in tumors, but its role and mechanism in non-small cell lung cancer (NSCLC) development remain uncertain.

METHODS

Cell proliferation, migration, invasion and angiogenesis were investigated via CCK-8, colony formation, transwell, and tube formation assays, respectively. The location of DGUOK-AS1 was detected via FISH assay. The interaction relationship among DGUOK-AS1, IGF2BP2 and TRPM7 was confirmed by RIP and MeRIP assays. The effects of DGUOK-AS1 on NSCLC growth and metastasis in vivo were investigated using xenograft and pulmonary metastatic models.

RESULTS

DGUOK-AS1 was upregulated in NSCLC. DGUOK-AS1 silencing inhibited NSCLC cell proliferation, migration, invasion and angiogenesis. DGUOK-AS1 was mostly expressed in cytoplasm, and positively regulated IGF2BP2. METTL3/IGF2BP2 axis could increase TRPM7 mRNA stability in m6A-dependent manner. TRPM7 overexpression reversed the inhibitive function of DGUOK-AS1 silencing on NSCLC development. DGUOK-AS1 knockdown suppressed NSCLC cell growth and metastasis in nude mice.

CONCLUSION

DGUOK-AS1 silencing restrains NSCLC cell growth and metastasis through decreasing TRPM7 stability via regulation of the METTL3/IGF2BP2-mediated m6A modification.

Development of Ferroptosis-Associated ceRNA Network in Periodontitis

OBJECTIVES

Periodontitis is a chronic inflammatory illness that may lead to tooth loosening and even loss, and its pathogenesis is not fully understood. Ferroptosis is an iron-dependent, regulated cell death. The present study aims to find the key ferroptosis-related genes (FRGs) in periodontitis and develop an mRNA-miRNA-lncRNA network to deeply explore the pathogenesis of periodontitis.

METHODS

Data from the Gene Expression Omnibus (GEO) database and FerrDb database were downloaded to discover the differentially expressed mRNA, miRNA, and FRGs. Functional enrichment analysis was conducted for the differentially expressed FRGs (DE-FRGs), including gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) network analysis. Targetscan and miRtarbase were used to estimate the miRNAs that DE-FRGs may interact with, whilst StarBase v3.0 was used for lncRNA-miRNA interaction.

RESULTS

Seven DE-FRGs were identified through differential expression analysis. Interleukin 1 beta (IL1B) interacted with XBP1 and MMP13 in the PPI network. After taking the intersection between DE-miRNAs and predicted miRNAs, a ceRNA network containing IL1B, has-miR-185, has-miR-204, has-miR-211, has-miR-4306, and 28 lncRNAs was established.

CONCLUSIONS

Seven FRGs in periodontitis were identified, which might promote deeper understanding of ferroptosis in periodontitis.

Expression of the primate-specific LINC00473 RNA in mouse neurons promotes excitability and CREB-regulated transcription

The LINC00473 (Lnc473) gene has previously been shown to be associated with cancer and psychiatric disorders. Its expression is elevated in several types of tumors and decreased in the brains of patients diagnosed with schizophrenia or major depression. In neurons, Lnc473 transcription is strongly responsive to synaptic activity, suggesting a role in adaptive, plasticity-related mechanisms. However, the function of Lnc473 is largely unknown. Here, using a recombinant adeno-associated viral vector, we introduced a primate-specific human Lnc473 RNA into mouse primary neurons. We show that this resulted in a transcriptomic shift comprising downregulation of epilepsy-associated genes and a rise in cAMP response element binding protein (CREB) activity, which was driven by augmented CREB-regulated transcription coactivator 1 (CRTC1) nuclear localization. Moreover, we demonstrate that ectopic Lnc473 expression increased neuronal excitability as well as network excitability. These findings suggest that primates may possess a lineage-specific activity-dependent modulator of CREB-regulated neuronal excitability.

Nuclei on the Rise: When Nuclei-Based Methods Meet Next-Generation Sequencing

In the last decade, we have witnessed an upsurge in nuclei-based studies, particularly coupled with next-generation sequencing. Such studies aim at understanding the molecular states that exist in heterogeneous cell populations by applying increasingly more affordable sequencing approaches, in addition to optimized methodologies developed to isolate and select nuclei. Although these powerful new methods promise unprecedented insights, it is important to understand and critically consider the associated challenges. Here, we provide a comprehensive overview of the rise of nuclei-based studies and elaborate on their advantages and disadvantages, with a specific focus on their utility for transcriptomic sequencing analyses. Improved designs and appropriate use of the various experimental strategies will result in acquiring biologically accurate and meaningful information.

lncHUB2: aggregated and inferred knowledge about human and mouse lncRNAs

Long non-coding ribonucleic acids (lncRNAs) account for the largest group of non-coding RNAs. However, knowledge about their function and regulation is limited. lncHUB2 is a web server database that provides known and inferred knowledge about the function of 18 705 human and 11 274 mouse lncRNAs. lncHUB2 produces reports that contain the secondary structure fold of the lncRNA, related publications, the most correlated coding genes, the most correlated lncRNAs, a network that visualizes the most correlated genes, predicted mouse phenotypes, predicted membership in biological processes and pathways, predicted upstream transcription factor regulators, and predicted disease associations. In addition, the reports include subcellular localization information; expression across tissues, cell types, and cell lines, and predicted small molecules and CRISPR knockout (CRISPR-KO) genes prioritized based on their likelihood to up- or downregulate the expression of the lncRNA. Overall, lncHUB2 is a database with rich information about human and mouse lncRNAs and as such it can facilitate hypothesis generation for many future studies. The lncHUB2 database is available at https://maayanlab.cloud/lncHUB2. Database URL: https://maayanlab.cloud/lncHUB2.

Long non-coding RNA NCK1-AS1 functions as a ceRNA to regulate cell viability and invasion in esophageal squamous cell carcinoma via microRNA-133b/ENPEP axis

This study is designed to explore the role of long non-coding RNAs (lncRNAs) NCK1-AS1 in proliferative and invasive activities of esophageal squamous cell carcinoma (ESCC) cells by binding to microRNA-133b (miR-133b) to regulate ENPEP. Differentially expressed lncRNAs, miRs, genes and their targeting relationships were screened on ESCC-related gene expression datasets GSE17351 and GSE6188. The targeting relationships among NCK1-AS1, miR-133b, and ENPEP were verified using functional assays. Loss- and gain- of function assays were carried out to examine the roles of NCK1-AS1, miR-133b, and ENPEP in ESCC cell proliferative, invasive, migrative and apoptotic abilities as well as tumorigenesis in vivo. Elevated NCK1-AS1 and ENPEP but reduced miR-133b expression were found in ESCC. NCK1-AS1 knockdown or miR-133b overexpression inhibited the malignant properties of ESCC cells as well as tumorigenesis in vivo. NCK1-AS1 regulated the ENPEP expression by competitively binding to miR-133b. ENPEP overexpression reversed inhibition of NCK1-AS1 knockdown on the function of ESCC cells. This study provides evidence that silencing NCK1-AS1 inhibits expression of ENPEP by sponging miR-133b, thereby suppressing ESCC.