A pituitary-derived MEG3 isoform functions as a growth suppressor in tumor cells

IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier

Background

Identifying lncRNA-disease associations not only helps to better comprehend the underlying mechanisms of various human diseases at the lncRNA level but also speeds up the identification of potential biomarkers for disease diagnoses, treatments, prognoses, and drug response predictions. However, as the amount of archived biological data continues to grow, it has become increasingly difficult to detect potential human lncRNA-disease associations from these enormous biological datasets using traditional biological experimental methods. Consequently, developing new and effective computational methods to predict potential human lncRNA diseases is essential.

Results

Using a combination of incremental principal component analysis (IPCA) and random forest (RF) algorithms and by integrating multiple similarity matrices, we propose a new algorithm (IPCARF) based on integrated machine learning technology for predicting lncRNA-disease associations. First, we used two different models to compute a semantic similarity matrix of diseases from a directed acyclic graph of diseases. Second, a characteristic vector for each lncRNA-disease pair is obtained by integrating disease similarity, lncRNA similarity, and Gaussian nuclear similarity. Then, the best feature subspace is obtained by applying IPCA to decrease the dimension of the original feature set. Finally, we train an RF model to predict potential lncRNA-disease associations. The experimental results show that the IPCARF algorithm effectively improves the AUC metric when predicting potential lncRNA-disease associations. Before the parameter optimization procedure, the AUC value predicted by the IPCARF algorithm under 10-fold cross-validation reached 0.8529; after selecting the optimal parameters using the grid search algorithm, the predicted AUC of the IPCARF algorithm reached 0.8611.

Conclusions

We compared IPCARF with the existing LRLSLDA, LRLSLDA-LNCSIM, TPGLDA, NPCMF, and ncPred prediction methods, which have shown excellent performance in predicting lncRNA-disease associations. The compared results of 10-fold cross-validation procedures show that the predictions of the IPCARF method are better than those of the other compared methods.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04104-9.

A cross-nearest neighbor/Monte Carlo algorithm for single-molecule localization microscopy defines interactions between p53, Mdm2, and MEG3

The functions of long noncoding (lnc)RNAs, such as MEG3, are defined by their interactions with other RNAs and proteins. These interactions, in turn, are shaped by their subcellular localization and temporal context. Therefore, it is important to be able to analyze the relationships of lncRNAs while preserving cellular architecture. The ability of MEG3 to suppress cell proliferation led to its recognition as a tumor suppressor. MEG3 has been proposed to activate p53 by disrupting the interaction of p53 with mouse double minute 2 homolog (Mdm2). To test this mechanism in the native cellular context, we employed two-color direct stochastic optical reconstruction microscopy, a single-molecule localization microscopy technique, to detect and quantify the localizations of p53, Mdm2, and MEG3 in U2OS cells. We developed a new cross-nearest neighbor/Monte Carlo algorithm to quantify the association of these molecules. Proof of concept for our method was obtained by examining the association between FKBP1A and mTOR, MEG3 and p53, and Mdm2 and p53. In contrast to previous models, our data support a model in which MEG3 modulates p53 independently of the interaction with Mdm2.

RWSF-BLP: a novel lncRNA-disease association prediction model using random walk-based multi-similarity fusion and bidirectional label propagation

An increasing number of studies and experiments have demonstrated that long noncoding RNAs (lncRNAs) have a massive impact on various biological processes. Predicting potential associations between lncRNAs and diseases not only can improve our understanding of the molecular mechanisms of human diseases but also can facilitate the identification of biomarkers for disease diagnosis, treatment, and prevention. However, identifying such associations through experiments is costly and demanding, thereby prompting researchers to develop computational methods to complement these experiments. In this paper, we constructed a novel model called RWSF-BLP (a novel lncRNA-disease association prediction model using Random Walk-based multi-Similarity Fusion and Bidirectional Label Propagation), which applies an efficient random walk-based multi-similarity fusion (RWSF) method to fuse different similarity matrices and utilizes bidirectional label propagation to predict potential lncRNA-disease associations. Leave-one-out cross-validation (LOOCV) and 5-fold cross-validation (5-fold-CV) were implemented in the evaluation RWSF-BLP performance. Results showed that, RWSF-BLP has reliable AUCs of 0.9086 and 0.9115 ± 0.0044 under the framework of LOOCV and 5-fold-CV and outperformed other four canonical methods. Case studies on lung cancer and leukemia demonstrated that potential lncRNA-disease associations can be predicted through our method. Therefore, our method can accurately infer potential lncRNA-disease associations and may be a good choice in future biomedical research.

LncRNA Meg3-mediated regulation of the Smad pathway in atRA-induced cleft palate

Palatal mesenchymal cell proliferation is essential to the process of palatogenesis, and the proliferation of mouse embryonic palate mesenchymal (MEPM) cells is impacted by both all-trans retinoic acid (atRA) and the TGF-β/Smad signaling pathway. The long non-coding RNA (lncRNA) MEG3 has been shown to activate TGF-β/Smad signaling and to thereby regulate cell proliferation, differentiation, and related processes. Herein, we found that atRA treatment (100 mg/kg) promoted Meg3 upregulation in MEPM cells, and that such upregulation was linked to the suppression of MEPM cell proliferation in the context of secondary palate fusion on gestational day (GD) 13 and 14. Moreover, the demethylation of specific CpG sites within the lncRNA Meg3 promoter was detected in atRA-treated MEPM cells, likely explaining the observed upregulation of this lncRNA. Smad signaling was also suppressed by atRA treatment in these cells, and RNA immunoprecipitation analyses revealed that Smad2 can directly interact with Meg3 in MEPM cells following atRA treatment. Therefore, we propose a model wherein Meg3 is involved in the suppression of MEPM cell proliferation, functioning at least in part via interacting with the Smad2 protein and thereby suppressing Smad signaling in the context of atRA-induced cleft palate.

The Functions and Unique Features of LncRNAs in Cancer Development and Tumorigenesis

Over the past decades, research on cancer biology has focused on the involvement of protein-coding genes in cancer development. Long noncoding RNAs (lncRNAs), which are transcripts longer than 200 nucleotides that lack protein-coding potential, are an important class of RNA molecules that are involved in a variety of biological functions. Although the functions of a majority of lncRNAs have yet to be clarified, some lncRNAs have been shown to be associated with human diseases such as cancer. LncRNAs have been shown to contribute to many important cancer phenotypes through their interactions with other cellular macromolecules including DNA, protein and RNA. Here we describe the literature regarding the biogenesis and features of lncRNAs. We also present an overview of the current knowledge regarding the roles of lncRNAs in cancer from the view of various aspects of cellular homeostasis, including proliferation, survival, migration and genomic stability. Furthermore, we discuss the methodologies used to identify the function of lncRNAs in cancer development and tumorigenesis. Better understanding of the molecular mechanisms involving lncRNA functions in cancer is critical for the development of diagnostic and therapeutic strategies against tumorigenesis.

GH and IGF System: The Regulatory Role of miRNAs and lncRNAs in Cancer

Growth hormone (GH) and the insulin-like growth factor (IGF) system are involved in many biological processes and have growth-promoting actions regulating cell proliferation, differentiation, apoptosis and angiogenesis. A recent chapter in epigenetics is represented by microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) which regulate gene expression. Dysregulated miRNAs and lncRNAs have been associated with several diseases including cancer. Herein we report the most recent findings concerning miRNAs and lncRNAs regulating GH and the IGF system in the context of pituitary adenomas, osteosarcoma and colorectal cancer, shedding light on new possible therapeutic targets. Pituitary adenomas are increasingly common intracranial tumors and somatotroph adenomas determine supra-physiological GH secretion and cause acromegaly. Osteosarcoma is the most frequent bone tumor in children and adolescents and was reported in adults who were treated with GH in childhood. Colorectal cancer is the third cancer in the world and has a higher prevalence in acromegalic patients.

HAUBRW: Hybrid algorithm and unbalanced bi-random walk for predicting lncRNA-disease associations

An increasing number of research shows that long non-coding RNA plays a key role in many important biological processes. However, the number of disease-related lncRNAs found by researchers remains relatively small, and experimental identification is time consuming and labor intensive. In this study, we propose a novel method, namely HAUBRW, to predict undiscovered lncRNA-disease associations. First, the hybrid algorithm, which combines the heat spread algorithm and the probability diffusion algorithm, redistributes the resources. Second, unbalanced bi-random walk, is used to infer undiscovered lncRNA disease associations. Seven advanced models, i.e. BRWLDA, DSCMF, RWRlncD, IDLDA, KATZ, Ping's, and Yang's were compared with our method, and simulation results show that the AUC of our method is more perfect than the other models. In addition, case studies have shown that HAUBRW can effectively predict candidate lncRNAs for breast, osteosarcoma and cervical cancer. Therefore, our approach may be a good choice in future biomedical research.

Novel Insights into Pituitary Tumorigenesis: Genetic and Epigenetic Mechanisms

Substantial advances have been made recently in the pathobiology of pituitary tumors. Similar to many other endocrine tumors, over the last few years we have recognized the role of germline and somatic mutations in a number of syndromic or nonsyndromic conditions with pituitary tumor predisposition. These include the identification of novel germline variants in patients with familial or simplex pituitary tumors and establishment of novel somatic variants identified through next generation sequencing. Advanced techniques have allowed the exploration of epigenetic mechanisms mediated through DNA methylation, histone modifications and noncoding RNAs, such as microRNA, long noncoding RNAs and circular RNAs. These mechanisms can influence tumor formation, growth, and invasion. While genetic and epigenetic mechanisms often disrupt similar pathways, such as cell cycle regulation, in pituitary tumors there is little overlap between genes altered by germline, somatic, and epigenetic mechanisms. The interplay between these complex mechanisms driving tumorigenesis are best studied in the emerging multiomics studies. Here, we summarize insights from the recent developments in the regulation of pituitary tumorigenesis.

Long Non-coding RNAs in Cancer: Implications for Diagnosis, Prognosis, and Therapy

Long non-coding RNAs (lncRNAs) are major components of cellular transcripts that are arising as important players in various biological pathways. They have received extensive attention in recent years, regarded to be involved in both developmental processes and various diseases. Due to their specific expression and functional diversity in a variety of cancers, lncRNAs have promising applications in cancer diagnosis, prognosis and therapy. Studies have shown that lncRNAs with high specificity and accuracy have the potential to become biomarkers in cancers. LncRNAs can be noninvasively extracted from body fluids, tissues and cells, and can be used as independent or auxiliary biomarkers to improve the accuracy of diagnosis or prognosis. Currently, the most well-recognized lncRNA is PCA3, which has been approved for use in the diagnosis of prostate cancer. Moreover, the underlying mechanisms of lncRNAs were explored as therapeutic targets, which have been investigated in clinical trials of several cancers. In this review, we presented a compilation of recent publications, clinical trials and patents, addressing the potential of lncRNAs that could be considered as biomarkers or therapeutic targets, with the hopes of providing promised implications for future cancer therapy.

LncRNA, Important Player in Bone Development and Disease

BACKGROUND

Bone is an important tissue and its normal function requires tight coordination of transcriptional networks and signaling pathways, and many of these networks/ pathways are dysregulated in pathological conditions affecting cartilage and bones. Long non-coding RNA (lncRNA) refers to a class of RNAs with a length of more than 200 nucleotides, lack of protein-coding potential, and exhibiting a wide range of biological functions. Although studies on lcnRNAs are still in their infancy, they have emerged as critical players in bone biology and bone diseases. The functions and exact mechanism of bone-related lncRNAs have not been fully classified yet.

OBJECTIVE

The objective of this article is to summarize the current literature on lncRNAs on the basis of their role in bone biology and diseases, focusing on their emerging molecular mechanism, pathological implications and therapeutic potential.

DISCUSSION

A number of lncRNAs have been identified and shown to play important roles in multiple bone cells and bone disease. The function and mechanism of bone-related lncRNA remain to be elucidated.

CONCLUSION

At present, majority of knowledge is limited to cellular levels and less is known on how lncRNAs could potentially control the development and homeostasis of bone. In the present review, we highlight some lncRNAs in the field of bone biology and bone disease. We also delineate some lncRNAs that might have deep impacts on understanding bone diseases and providing new therapeutic strategies to treat these diseases.

LncRNAs in Cancer: From garbage to Junk

Sequencing-based transcriptomics has significantly redefined the concept of genome complexity, leading to the identification of thousands of lncRNA genes identification of thousands of lncRNA genes whose products possess transcriptional and/or post-transcriptional regulatory functions that help to shape cell functionality and fate. Indeed, it is well-established now that lncRNAs play a key role in the regulation of gene expression through epigenetic and posttranscriptional mechanims. The rapid increase of studies reporting lncRNAs alteration in cancers has also highlighted their relevance for tumorigenesis. Herein we describe the most prominent examples of well-established lncRNAs having oncogenic and/or tumor suppressive activity. We also discuss how technical advances have provided new therapeutic strategies based on their targeting, and also report the challenges towards their use in the clinical settings.

Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA)

Long noncoding RNAs (lncRNAs) are implicated in various genetic diseases and cancer, attributed to their critical role in gene regulation. They are a divergent group of RNAs and are easily differentiated from other types with unique characteristics, functions, and mechanisms of action. In this review, we provide a list of some of the prominent data repositories containing lncRNAs, their interactome, and predicted and validated disease associations. Next, we discuss various wet-lab experiments formulated to obtain the data for these repositories. We also provide a critical review of in silico methods available for the identification purpose and suggest techniques to further improve their performance. The bulk of the methods currently focus on distinguishing lncRNA transcripts from the coding ones. Functional annotation of these transcripts still remains a grey area and more efforts are needed in that space. Finally, we provide details of current progress, discuss impediments, and illustrate a roadmap for developing a generalized computational pipeline for comprehensive annotation of lncRNAs, which is essential to accelerate research in this area.

The molecular structure of long non-coding RNAs: emerging patterns and functional implications

Long non-coding RNAs (lncRNAs) are recently-discovered transcripts that regulate vital cellular processes and are crucially connected to diseases. Despite their unprecedented molecular complexity, it is emerging that lncRNAs possess distinct structural motifs. Remarkably, the 3D shape and topology of full-length, native lncRNAs have been visualized for the first time in the last year. These studies reveal that lncRNA structures dictate lncRNA functions. Here, we review experimentally determined lncRNA structures and emphasize that lncRNA structural characterization requires synergistic integration of computational, biochemical and biophysical approaches. Based on these emerging paradigms, we discuss how to overcome the challenges posed by the complex molecular architecture of lncRNAs, with the goal of obtaining a detailed understanding of lncRNA functions and molecular mechanisms in the future.

Hypermethylation and reduced expression of Gtl2, Rian and Mirg at the Dlk1-Dio3 imprinted locus as a marker for poor developmental potential of mouse embryonic stem cells

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Reduced expression of Gtl2, Rian and Mirg in ES cells compromised survival of chimaeric fetuses.

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Reduced expression of Gtl2, Rian and Mirg was associated with hypermethylation.

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Compromised ES cells can be identified and eliminated from experiments to reduce animal use.

Mouse embryonic stem cells (ESCs) have played a crucial role in biomedical research where they can be used to elucidate gene function through the generation of genetically modified mice. A critical requirement for the success of this technology is the ability of ESCs to contribute to viable chimaeras with germ-line transmission of the genetically modified allele. We have identified several ESC clones that cause embryonic death of chimaeras at mid to late gestation stages. These clones had a normal karyotype, were pathogen free and their in vitro differentiation potential was not compromised. Chimaeric embryos developed normally up to E13.5 but showed a significant decrease in embryo survival by E17.5 with frequent haemorrhaging. We investigated the relationship between the ESCs transcriptional and epigenomic state and their ability to contribute to viable chimaeras. RNA sequencing identified four genes (Gtl2, Rian, Mirg and Rtl1as) located in the Dlk1-Dio3 imprinted locus that were expressed at lower levels in the compromised ESC clones and this was confirmed by qRT-PCR. Bisulphite sequencing analysis showed significant hypermethylation at the Dlk1-Dio3 imprinted locus with no consistent differences in methylation patterns at other imprinted loci. Treatment of the compromised ESCs with 5-azacytidine reactivated stable expression of Gtl2 and rescued the lethal phenotype but only gave low level chimaeras.

Coding of Glioblastoma Progression and Therapy Resistance through Long Noncoding RNAs

Glioblastoma is the most aggressive and lethal primary brain malignancy, with an average patient survival from diagnosis of 14 months. Glioblastoma also usually progresses as a more invasive phenotype after initial treatment. A major step forward in our understanding of the nature of glioblastoma was achieved with large-scale expression analysis. However, due to genomic complexity and heterogeneity, transcriptomics alone is not enough to define the glioblastoma “fingerprint”, so epigenetic mechanisms are being examined, including the noncoding genome. On the basis of their tissue specificity, long noncoding RNAs (lncRNAs) are being explored as new diagnostic and therapeutic targets. In addition, growing evidence indicates that lncRNAs have various roles in resistance to glioblastoma therapies (e.g., MALAT1, H19) and in glioblastoma progression (e.g., CRNDE, HOTAIRM1, ASLNC22381, ASLNC20819). Investigations have also focused on the prognostic value of lncRNAs, as well as the definition of the molecular signatures of glioma, to provide more precise tumor classification. This review discusses the potential that lncRNAs hold for the development of novel diagnostic and, hopefully, therapeutic targets that can contribute to prolonged survival and improved quality of life for patients with glioblastoma.

Expression of ncRNAs on the DLK1-DIO3 Locus Is Associated With Basal and Mesenchymal Phenotype in Breast Epithelial Progenitor Cells

Epithelial-to-mesenchymal transition (EMT) and its reversed process mesenchymal-to-epithelial transition (MET) play a critical role in epithelial plasticity during development and cancer progression. Among important regulators of these cellular processes are non-coding RNAs (ncRNAs). The imprinted DLK1-DIO3 locus, containing numerous maternally expressed ncRNAs including the lncRNA maternally expressed gene 3 (MEG3) and a cluster of over 50 miRNAs, has been shown to be a modulator of stemness in embryonic stem cells and in cancer progression, potentially through the tumor suppressor role of MEG3. In this study we analyzed the expression pattern and functional role of ncRNAs from the DLK1-DIO3 locus in epithelial plasticity of the breast. We studied their expression in various cell types of breast tissue and revisit the role of the locus in EMT/MET using a breast epithelial progenitor cell line (D492) and its isogenic mesenchymal derivative (D492M). Marked upregulation of ncRNAs from the DLK1-DIO3 locus was seen after EMT induction in two cell line models of EMT. In addition, the expression of MEG3 and the maternally expressed ncRNAs was higher in stromal cells compared to epithelial cell types in primary breast tissue. We also show that expression of MEG3 is concomitant with the expression of the ncRNAs from the DLK1-DIO3 locus and its expression is therefore likely indicative of activation of all ncRNAs at the locus. MEG3 expression is correlated with stromal markers in normal tissue and breast cancer tissue and negatively correlated with the survival of breast cancer patients in two different cohorts. Overexpression of MEG3 using CRISPR activation in a breast epithelial cell line induced partial EMT and enriched for a basal-like phenotype. Conversely, knock down of MEG3 using CRISPR inhibition in a mesenchymal cell line reduced the mesenchymal and basal-like phenotype of the cell line. In summary our study shows that maternally expressed ncRNAs are markers of EMT and suggests that MEG3 is a novel regulator of EMT/MET in breast tissue. Nevertheless, further studies are needed to fully dissect the molecular pathways influenced by non-coding RNAs at the DLK1-DIO3 locus in breast tissue.

Role of non-coding RNAs as novel biomarkers for detection of colorectal cancer progression through interaction with the cell signaling pathways

Colorectal cancer (CRC) is one of the most common types of cancer which affects the colon and the rectum. Approximately one third of annual CRC mortality occurs due to the late detection of this type of cancer. Therefore, there is an urgent need for more powerful diagnostic and prognostic tools for identification and treatment of colorectal tumorigenesis. Non-coding RNAs (ncRNAs) have been implicated in the pathology of CRC and also linked to metastasis, proliferation, differentiation, migration, angiogenesis and apoptosis in numerous cancers. Recently, attention has turned towards ncRNAs as specific targets for diagnosis, prognosis and treatment of various types of cancers, including CRC. In this review, we have tried to outline the roles of ncRNAs, and their involvement in signaling pathways responsible for the progression of CRC.

Long non-coding RNA MEG3 is involved in osteogenic differentiation and bone diseases (Review)

Osteogenic differentiation originating from mesenchymal stem cells (MSCs) requires tight co-ordination of transcriptional factors, signaling pathways and biomechanical cues. Dysregulation of such reciprocal networks may influence the proliferation and apoptosis of MSCs and osteoblasts, thereby impairing bone metabolism and homeostasis. An increasing number of studies have shown that long non-coding (lnc)RNAs are involved in osteogenic differentiation and thus serve an important role in the initiation, development, and progression of bone diseases such as tumors, osteoarthritis and osteoporosis. It has been reported that the lncRNA, maternally expressed gene 3 (MEG3), regulates osteogenic differentiation of multiple MSCs and also acts as a critical mediator in the development of bone formation and associated diseases. In the present review, the proposed mechanisms underlying the roles of MEG3 in osteogenic differentiation and its potential effects on bone diseases are discussed. These discussions may help elucidate the roles of MEG3 in osteogenic differentiation and highlight potential biomarkers and therapeutic targets for the treatment of bone diseases.

The Emerging Roles of Long Noncoding RNAs in Bone Homeostasis and Their Potential Application in Bone-Related Diseases

Increasing evidence has announced the emerging roles of long noncoding RNAs (lncRNAs) in modulating bone homeostasis due to their potential regulating effects on bone-related cells' proliferation, migration, differentiation and apoptosis. Thus, lncRNAs have been considered as a promising gene tool to facilitate the bone regeneration process and then to predict and cure bone-related diseases such as osteosarcoma, osteoporosis, and osteoarthritis. In this review, we first enumerated several kinds of dysregulated lncRNAs and concisely summarized their regulating role in bone formation as well as resorption process. The related mechanisms were also discussed, respectively. Then, the positive or negative behavior of these lncRNAs in bone-related diseases was elucidated. This review provides an in-depth sight about the lncRNA's clinical values and limitations, which is conducive to explore new gene targets and further establish new therapeutic strategies for bone-related disease.

Dysregulations of MicroRNA and Gene Expression in Chronic Venous Disease

Chronic venous disease (CVD) is a vascular disease of lower limbs with high prevalence worldwide. Pathologic features include varicose veins, venous valves dysfunction and skin ulceration resulting from dysfunction of cell proliferation, apoptosis and angiogenesis. These processes are partly regulated by microRNA (miRNA)-dependent modulation of gene expression, pointing to miRNA as a potentially important target in diagnosis and therapy of CVD progression. The aim of the study was to analyze alterations of miRNA and gene expression in CVD, as well as to identify miRNA-mediated changes in gene expression and their potential link to CVD development. Using next generation sequencing, miRNA and gene expression profiles in peripheral blood mononuclear cells of subjects with CVD in relation to healthy controls were studied. Thirty-one miRNAs and 62 genes were recognized as potential biomarkers of CVD using DESeq2, Uninformative Variable Elimination by Partial Least Squares (UVE-PLS) and ROC (Receiver Operating Characteristics) methods. Regulatory interactions between potential biomarker miRNAs and genes were projected. Functional analysis of microRNA-regulated genes revealed terms closely related to cardiovascular diseases and risk factors. The study shed new light on miRNA-dependent regulatory mechanisms involved in the pathology of CVD. MicroRNAs and genes proposed as CVD biomarkers may be used to develop new diagnostic and therapeutic methods.

Role of noncoding RNAs in cholangiocarcinoma (Review)

Cholangiocarcinoma (CCA) is a malignant tumour originating from biliary epithelial cells, and is increasing in incidence. Radical surgery is the main treatment. However, the pathogenesis of CCA is unclear. Noncoding RNAs (ncRNAs) are non‑protein‑coding RNAs produced by genomic transcription that include microRNAs (miRNAs), circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs). They play important roles in gene expression, epigenetic modification, cell proliferation, differentiation and reproduction. ncRNAs also serve key roles in cancer development. Numerous studies have been carried out on ncRNAs, and associated publications have shown that ncRNAs are closely associated with the physiological and pathological mechanisms of CCA. The findings of these studies can provide new insights into the diagnosis, treatment and prognosis of CCA. The present review summarizes the pathophysiological mechanisms of different types of ncRNAs, including miRNAs, circRNAs and lncRNAs in CCA, and their applications in the diagnosis and treatment of CCA.

MEG3 regulates apoptosis of adipose‑derived stem cells

In plastic surgery, the maneuverability and safety of autologous fat transplantation have become increasingly recognized and continuously improved. However, the uncertainty of adipocyte survival makes it difficult to predict postoperative effects. Adipose‑derived stem cells (ADSCs) exhibit remarkable paracrine activity, and the number of ADSCs in adipose tissue is closely related to tissue survival. Maternally expressed gene 3 (MEG3) is known to modulate the apoptosis of various cell types. The present study aimed to evaluate the hypothesis that MEG3 serves an important role in ADSC apoptosis by regulating the expression of p53, and to explore the regulatory mechanisms of p53 in ADSC apoptosis. MEG3 was overexpressed in ADSCs and these cells were evaluated for viability, TP53 expression, apoptosis, morphology, and Bax and Bcl‑2 expression by performing MTT assays, reverse transcription‑quantitative PCR, flow cytometry analysis and western blotting. This study demonstrated that MEG3 may have an important role in the spontaneous apoptosis of ADSCs, and apoptosis induced by oxidative stress. In addition, this study revealed that p53 had a regulatory role in the downstream Bcl‑2/Bax pathway. This study provides insight into the role of MEG3 in ADSC apoptosis, thereby facilitating the survival of ADSCs during adipose tissue transplantation. Further in vivo and in vitro experiments should be conducted, along with the development of clinical applications.

A random forest based computational model for predicting novel lncRNA-disease associations

BACKGROUND

Accumulated evidence shows that the abnormal regulation of long non-coding RNA (lncRNA) is associated with various human diseases. Accurately identifying disease-associated lncRNAs is helpful to study the mechanism of lncRNAs in diseases and explore new therapies of diseases. Many lncRNA-disease association (LDA) prediction models have been implemented by integrating multiple kinds of data resources. However, most of the existing models ignore the interference of noisy and redundancy information among these data resources.

RESULTS

To improve the ability of LDA prediction models, we implemented a random forest and feature selection based LDA prediction model (RFLDA in short). First, the RFLDA integrates the experiment-supported miRNA-disease associations (MDAs) and LDAs, the disease semantic similarity (DSS), the lncRNA functional similarity (LFS) and the lncRNA-miRNA interactions (LMI) as input features. Then, the RFLDA chooses the most useful features to train prediction model by feature selection based on the random forest variable importance score that takes into account not only the effect of individual feature on prediction results but also the joint effects of multiple features on prediction results. Finally, a random forest regression model is trained to score potential lncRNA-disease associations. In terms of the area under the receiver operating characteristic curve (AUC) of 0.976 and the area under the precision-recall curve (AUPR) of 0.779 under 5-fold cross-validation, the performance of the RFLDA is better than several state-of-the-art LDA prediction models. Moreover, case studies on three cancers demonstrate that 43 of the 45 lncRNAs predicted by the RFLDA are validated by experimental data, and the other two predicted lncRNAs are supported by other LDA prediction models.

CONCLUSIONS

Cross-validation and case studies indicate that the RFLDA has excellent ability to identify potential disease-associated lncRNAs.

lncRNA MIAT promotes cell invasion and migration in esophageal cancer

Long non-coding RNAs (lncRNAs) serve crucial roles in carcinogenesis. Myocardial infarction-associated transcript (MIAT), originally isolated as a candidate gene for myocardial infarction, has been revealed to serve as an oncogene in chronic lymphocytic leukaemias and neuroendocrine prostate cancer. However, little is known about its expression pattern, biological function and underlying mechanism in esophageal cancer. Cell lines of esophageal cancer were used in the current study. The results of the present study revealed that MIAT knockdown decreased cell viability, migration, invasion and cell cycle arrest in the G1 phase. Mechanistic assessment revealed that MIAT interacts with histone methyltransferase mixed-lineage leukemia (MLL). The relative proteins expressions were measured by western blotting assay. MIAT knockdown suppressed cell invasion and migration by regulation MMP-2/9 protein expressions. The results of the current study indicated that MIAT expression was associated with esophageal cancer and may serve as a critical target in the progression and metastasis in esophageal cancer.

Deciphering the Mounting Complexity of the p53 Regulatory Network in Correlation to Long Non-Coding RNAs (lncRNAs) in Ovarian Cancer

Amongst the various gynecological malignancies affecting female health globally, ovarian cancer is one of the predominant and lethal among all. The identification and functional characterization of long non-coding RNAs (lncRNAs) are made possible with the advent of RNA-seq and the advancement of computational logarithm in understanding human disease biology. LncRNAs can interact with deoxyribonucleic acid (DNA), ribonucleic acid (RNA), proteins and their combinations. Moreover, lncRNAs regulate orchestra of diverse functions including chromatin organization and transcriptional and post-transcriptional regulation. LncRNAs have conferred their critical role in key biological processes in human cancer including tumor initiation, proliferation, cell cycle, apoptosis, necroptosis, autophagy, and metastasis. The interwoven function of tumor-suppressor protein p53-linked lncRNAs in the ovarian cancer paradigm is of paramount importance. Several lncRNAs operate as p53 regulators or effectors and modulates a diverse array of functions either by participating in various signaling cascades or via interaction with different proteins. This review highlights the recent progress made in the identification of p53 associated lncRNAs while elucidating their molecular mechanisms behind the altered expression in ovarian cancer tumorigenesis. Moreover, the development of novel clinical and therapeutic strategies for targeting lncRNAs in human cancers harbors great promise.

Computational models for lncRNA function prediction and functional similarity calculation

From transcriptional noise to dark matter of biology, the rapidly changing view of long non-coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by abnormal expression of lncRNAs. There is urgent need to discern potential functional roles of lncRNAs for further study of pathology, diagnosis, therapy, prognosis, prevention of human complex disease and disease biomarker detection at lncRNA level. Computational models are anticipated to be an effective way to combine current related databases for predicting most potential lncRNA functions and calculating lncRNA functional similarity on the large scale. In this review, we firstly illustrated the biological function of lncRNAs from five biological processes and briefly depicted the relationship between mutations or dysfunctions of lncRNAs and human complex diseases involving cancers, nervous system disorders and others. Then, 17 publicly available lncRNA function-related databases containing four types of functional information content were introduced. Based on these databases, dozens of developed computational models are emerging to help characterize the functional roles of lncRNAs. We therefore systematically described and classified both 16 lncRNA function prediction models and 9 lncRNA functional similarity calculation models into 8 types for highlighting their core algorithm and process. Finally, we concluded with discussions about the advantages and limitations of these computational models and future directions of lncRNA function prediction and functional similarity calculation. We believe that constructing systematic functional annotation systems is essential to strengthen the prediction accuracy of computational models, which will accelerate the identification process of novel lncRNA functions in the future.

MEG3/MIR-376B-3P/HMGA2 axis is involved in pituitary tumor invasiveness

OBJECTIVE

To date, long noncoding RNAs (lncRNAs) have proven to function as key regulators in tumorigenesis. Among these lncRNAs, MEG3 displays low levels in various neoplasms and tumor cell lines. However, the regulatory mechanism of MEG3 and MIR-376B-3P, one of the microRNAs from downstream gene clusters of the DLK1-MEG3 locus, remains insufficiently defined.

METHODS

The authors used quantitative real-time polymerase chain reaction analysis to analyze whether decreased MEG3 and MIR-376B-3P expression levels were associated with the invasiveness of clinical nonfunctioning pituitary adenomas (CNFPAs) in 30 patients. Furthermore, functional experiments unveiled the pathophysiological role of MEG3, MIR-376B-3P, and HMGA2 in pituitary-derived folliculostellate (PDFS) cell lines. Moreover, dual-luciferase reporter assay, Western blot analysis, and immunofluorescence were applied to reveal the correlations among MEG3, MIR-376B-3P, and HMGA2.

RESULTS

MEG3 and MIR-376B-3P were decreased in patients with CNFPA, and their transcriptional levels were highly associated with invasive CNFPAs. Moreover, excessive expression of MEG3 and MIR-376B-3P inhibited tumorigenesis and promoted apoptosis in PDFS cells. Importantly, the authors found that MEG3 acted as an enhancer of MIR-376B-3P expression. Furthermore, as a target gene of MIR-376B-3P, HMGA2 served as an oncogene in pituitary adenoma and could be negatively regulated by MEG3 via enriching MIR-376B-3P.

CONCLUSIONS

This study offers a novel mechanism of an MEG3/MIR-376B-3P/HMGA2 regulatory network in CNFPAs, which may become a breakthrough for anticancer treatments.

SDF-1α/MicroRNA-134 Axis Regulates Nonfunctioning Pituitary Neuroendocrine Tumor Growth via Targeting VEGFA

BACKGROUND

Nonfunctioning pituitary neuroendocrine tumor (NF-PitNET) is difficult to resect. Except for surgery, there is no effective treatment for NF-PitNET. MicroRNA-134 (miR-134) has been reported to inhibit proliferation and invasion ability of tumor cells. Herein, the mechanism underlying the effect of miR-134 on alleviating NF-PitNET tumor cells growth is explored.

METHODS

Mouse pituitary αT3-1 cells were transfected with miR-134 mimics and inhibitor, followed by treatment with stromal cell-derived factor-1α (SDF-1α) in vitro. MiR-134 expression level: we used quantitative real-time PCR (qRT-PCR) to detect the expression of miR-134. Cell behavior level: cell viability and invasion ability were assessed using a cell counting kit-8 (CCK8) assay and Transwell invasion assay respectively. Cytomolecular level: tumor cell proliferation was evaluated by Ki-67 staining; propidium iodide (PI) staining analyzed the effect of miR-134 on cell cycle arrest; western blot analysis and immunofluorescence staining evaluated tumor migration and invasive ability. Additionally, we collected 27 NF-PitNET tumor specimens and related clinical data. The specimens were subjected to qRT-PCR to obtain the relative miR-134 expression level of each specimen; linear regression analysis was used to analyze the miR-134 expression level in tumor specimens and the age of the NF-PitNET population, gender, tumor invasion, prognosis, and other indicators.

RESULTS

In vitro experiment, miR-134 was observed to significantly inhibit αT3-1 cells proliferation characterized by inhibited cell viability and expressions of vascular endothelial growth factor A (VEGFA) and cell cycle transition from G1 to S phase (P < 0.01). VEGFA was verified as a target of miR-134. Additionally, miR-134-induced inhibition of αT3-1 cell proliferation and invasion was attenuated by SDF-1α and VEGFA overexpression (P < 0.01). In primary NF-PitNET tumor analysis, miR-134 expression level was negatively correlated with tumor invasion (P = 0.003).

CONCLUSION

The regulation of the SDF-1α/miR-134/VEGFA axis represents a novel mechanism in the pathogenesis of NF-PitNETs and may serve as a potential therapeutic target for the treatment of NF-PitNETs.

IDLDA: An Improved Diffusion Model for Predicting LncRNA-Disease Associations

It has been demonstrated that long non-coding RNAs (lncRNAs) play important roles in a variety of biological processes associated with human diseases. However, the identification of lncRNA–disease associations by experimental methods is time-consuming and labor-intensive. Computational methods provide an effective strategy to predict more potential lncRNA–disease associations to some degree. Based on the hypothesis that phenotypically similar diseases are often associated with functionally similar lncRNAs and vice versa, we developed an improved diffusion model to predict potential lncRNA–disease associations (IDLDA). As a result, our model performed well in the global and local cross-validations, which indicated that IDLDA had a great performance in predicting novel associations. Case studies of colon cancer, breast cancer, and gastric cancer were also implemented, all lncRNAs which ranked top 10 in both databases were verified by databases and related literature. The results showed that IDLDA might play a key role in biomedical research.

Long non-coding RNA MEG3 promotes cerebral ischemia-reperfusion injury through increasing pyroptosis by targeting miR-485/AIM2 axis

OBJECTIVE

Inflammasome contributes to ischemic brain injury by inducing pyroptosis and inflammation. The aim of this study is to unravel the mechanism of long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3)-mediated regulation of absent in melanoma 2 (AIM2) inflammasome during cerebral ischemia/reperfusion (I/R).

METHODS

In vivo middle cerebral artery occlusion (MCAO) rat model and in vitro oxygen-glucose deprivation/reperfusion (OGD/R)-treated neurocytes model were generated. TTC, H&E staining and TUNEL were performed to assess the cerebral ischemic injury. LDH and MTT assays were used to detect cell viability and cytotoxicity. qRT-PCR was used to detect the expression levels of MEG3, miR-485 and AIM2. Immunohistochemistry (IHC) and immunofluorescence were conducted to detect the AIM2 expression. ELISA and Western blotting were performed to determine the secretion and protein levels of inflammasome signaling proteins. Dual luciferase reporter assay and Ago2-RIP were used to validate the direct interaction among MEG3, miR-485 and AIM2.

RESULTS

In both MCAO rats and OGD/R-treated neurocytes, MEG3 and AIM2 were significantly up-regulated, whereas miR-485 was down-regulated. MCAO induces pyroptosis and release of IL-1β and IL-18 in ischemia brain. MEG3 acted as a molecular sponge to suppress miR-485, and AIM2 was identified as a direct target of miR-485. Knockdown of MEG3 inhibited OGD/R-induced pyroptosis and inflammation, and lack of MEG3 inhibited caspase1 signaling and decreased the expression of AIM2, ASC, cleaved-caspase1 and GSDMD-N. While overexpression of MEG3 exerted opposite effects.

CONCLUSION

MEG3/miR-485/AIM2 axis contributes to pyroptosis via activating caspase1 signaling during cerebral I/R, suggesting that this axis may be a potent therapeutic target in ischemic stroke.

Long noncoding RNAs in cancer: From discovery to therapeutic targets

Long noncoding RNAs (lncRNAs) have recently gained considerable attention as key players in biological regulation; however, the mechanisms by which lncRNAs govern various disease processes remain mysterious and are just beginning to be understood. The ease of next-generation sequencing technologies has led to an explosion of genomic information, especially for the lncRNA class of noncoding RNAs. LncRNAs exhibit the characteristics of mRNAs, such as polyadenylation, 5' methyl capping, RNA polymerase II-dependent transcription, and splicing. These transcripts comprise more than 200 nucleotides (nt) and are not translated into proteins. Directed interrogation of annotated lncRNAs from RNA-Seq datasets has revealed dramatic differences in their expression, largely driven by alterations in transcription, the cell cycle, and RNA metabolism. The fact that lncRNAs are expressed cell- and tissue-specifically makes them excellent biomarkers for ongoing biological events. Notably, lncRNAs are differentially expressed in several cancers and show a distinct association with clinical outcomes. Novel methods and strategies are being developed to study lncRNA function and will provide researchers with the tools and opportunities to develop lncRNA-based therapeutics for cancer.

The Role of Long Noncoding RNAs in the Biology of Pituitary Adenomas

Long noncoding RNAs (lncRNAs) are a large group of noncoding RNAs 200 nucleotides long. lncRNAs that function as regulatory factors have been identified for several complex cellular processes, such as cell death, growth, differentiation, apoptosis, epigenetic regulation, and so on. Many lncRNAs have altered expression and are likely to play a functional role in oncogenesis. The pituitary adenoma is the second most common intracranial tumor. Despite this situation, the molecular mechanism of pituitary adenoma formation has not yet been fully identified. This review summarizes recent progress in the study of lncRNAs on the pathogenesis of pituitary tumors. We cover the latest results associated with this role and highlight the therapeutic possibilities for pituitary adenomas.

Long Noncoding RNAs in Acute Myeloid Leukemia: Functional Characterization and Clinical Relevance

Acute Myeloid Leukemia (AML) is the most common form of leukemia in adults with an incidence of 4.3 per 100,000 cases per year. Historically, the identification of genetic alterations in AML focused on protein-coding genes to provide biomarkers and to understand the molecular complexity of AML. Despite these findings and because of the heterogeneity of this disease, questions as to the molecular mechanisms underlying AML development and progression remained unsolved. Recently, transcriptome-wide profiling approaches have uncovered a large family of long noncoding RNAs (lncRNAs). Larger than 200 nucleotides and with no apparent protein coding potential, lncRNAs could unveil a new set of players in AML development. Originally considered as dark matter, lncRNAs have critical roles to play in the different steps of gene expression and thus affect cellular homeostasis including proliferation, survival, differentiation, migration or genomic stability. Consequently, lncRNAs are found to be differentially expressed in tumors, notably in AML, and linked to the transformation of healthy cells into leukemic cells. In this review, we aim to summarize the knowledge concerning lncRNAs functions and implications in AML, with a particular emphasis on their prognostic and therapeutic potential.

Genome-wide discovery and characterization of long noncoding RNAs in patients with multiple myeloma

Background

Long noncoding RNAs (lncRNAs) are involved in a wide range of biological processes in tumorigenesis. However, the role of lncRNA expression in the biology, prognosis, and molecular classification of human multiple myeloma (MM) remains unclear, especially the biological functions of the vast majority of lncRNAs. Recently, lncRNAs have been identified in neoplastic hematologic disorders. Evidence has accumulated on the molecular mechanisms of action of lncRNAs, providing insight into their functional roles in tumorigenesis. This study aimed to characterize potential lncRNAs in patients with MM.

Methods

In this study, the whole-transcriptome strand-specific RNA sequencing of samples from three newly diagnosed patients with MM was performed. The whole transcriptome, including lncRNAs, microRNAs, and mRNAs, was analyzed. Using these data, MM lncRNAs were systematically analyzed, and the lncRNAs involved in the occurrence of MM were identified.

Results

The results revealed that MM lncRNAs had distinctive characteristics different from those of other malignant tumors. Further, the functions of a set of lncRNAs preferentially expressed in MM were verified, and several lncRNAs were identified as competing endogenous RNAs. More importantly, the aberrant expression of certain lncRNAs, including maternally expressed gene3, colon cancer–associated transcript1, and coiled-coil domain-containing 26, as well as some novel lncRNAs involved in the occurrence of MM was established. Further, lncRNAs were related to some microRNAs, regulated each other, and participated in MM development.

Conclusions

Genome-wide screening and functional analysis enabled the identification of a set of lncRNAs involved in the occurrence of MM. The interaction exists among microRNAs and lncRNAs.

Integrated analysis of co-expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.

Functional impact of the long non-coding RNA MEG3 deletion by CRISPR/Cas9 in the human triple negative metastatic Hs578T cancer cell line

Long non-coding RNAs (lncRNAs) serve critical roles in regulating cellular homeostasis, and their deregulated expression/activity is associated with neoplastic transformation. The maternally expressed gene 3 (MEG3) has been extensively described as a tumor suppressor gene in different types of cancer, including breast cancer. Interestingly, using a panel of seven different breast cancer cell lines, the present study revealed that MEG3 is highly expressed in the triple negative metastatic human Hs578T breast cancer cell line, which is refractory to different therapeutic approaches. Therefore, the present study aimed to investigate the phenotypic impact of MEG3 deletion in this cell line. Using the CRISPR/Cas9 system, complete knockout (KO) of MEG3 was achieved. Deletion was confirmed by genomic PCR and reverse transcription-quantitative PCR. The MEG3_KO cell population displaying the highest efficiency of genomic editing was selected for phenotypic in vitro assays, including wound scratch and Transwell assays, flow cytometry and immunofluorescence. The results demonstrated that MEG3 deletion increased cell proliferation, anchorage-independent cell growth and cell motility, which was consistent with its well-known tumor suppressor function. However, the present study revealed that MEG3_KO also lead to decreased cell invasiveness ability, supporting previous evidence that MEG3 modulates epithelial-to-mesenchymal inducing factors. The present study demonstrated that deletion of MEG3 promoted an increase in transforming growth factor β and N-cadherin protein levels and significant reduction in matrix metallopeptidase 2, zinc-finger E-box binding homeobox 1 and collagen type III α1 chain gene expression levels. Additionally, MEG3_KO cells displayed significant resistance to doxorubicin treatment, demonstrating the role of this lncRNA in cancer cell survival by regulating apoptosis. The present study highlighted the utility of CRISPR/Cas9 for anticancer studies of intergenic lncRNAs and demonstrated that, although Hs578T cells express MEG3 at high levels, these cells display mechanisms to escape the growth suppression effects of this lncRNA. Notably, the detailed pathological mechanisms of MEG3 concerning tumor metastasis remain to be elucidated prior to applying MEG3 expression/activation in future therapeutic approaches for breast cancer treatment.

Long noncoding RNA (MEG3) in urinal exosomes functions as a biomarker for the diagnosis of Hunner-type interstitial cystitis (HIC)

BACKGROUND

Toll-like receptor-7 (TLR7) is functionally involved in the pathogenesis of Hunner-type interstitial cystitis (HIC). In addition, maternally expressed gene 3 (MEG3) is implicated in many urethral diseases. In this study, we aimed to verify the hypothesis that exosomal MEG3 in urine can be used as a novel diagnostic biomarker for HIC.

METHODS

Electron microscopy was utilized to observe the distribution of urinary exosomes between the case group and the control group. Receiver operating characteristic analysis was utilized to compare the diagnostic values of MEG3 and miR-19a-3p. Computational analysis and luciferase assay were conducted to identify the correlation between MEG3 and miR-19a-3p as well as between TLR7 and miR-19a-3p. In addition, real-time polymerase chain reaction and Western blot were performed to establish the signaling pathways implicated in the pathogenesis of HIC.

RESULTS

When age and gender distributions are excluded, urinary exosomes were equally distributed between case and control groups. The area under the curve of MEG3 was larger than that of miR-19a-3p, indicating that MEG3 has a better value in the diagnosis of HIC. In addition, patients with HIC showed elevated MEG3 expression and inhibited miR-19a-3p expression, thus establishing a negative correlation between MEG3 and miR-19a-3p. MEG3 and TLR7 were both identified as targets of miR-19a-3p, establishing a MEG3/miR-19a-3p/TLR7 signaling pathway, in which MEG3 enhances the expression of TLR7 via inhibiting the expression of miR-19a-3p.

CONCLUSION

MEG3 level was upregulated in patients with HIC. In addition, MEG3 downregulated miR-19a-3p expression while upregulating TLR7 expression. Furthermore, MEG3 contributes to the pathogenesis of HIC. Therefore, exosomal MEG3 in urine can be used as a biomarker for HIC diagnosis.

Long non‑coding RNA MEG3 suppresses the growth of glioma cells by regulating the miR‑96‑5p/MTSS1 signaling pathway

Glioma is one of the most common types of tumor of the central nervous system with high mobility and mortality. The prognosis of patients with high-grade glioma is poor. Therefore, it is urgent to develop the therapeutic strategies for the treatment of glioma. Long non-coding RNAs (lncRNAs) have been reported as potential inducers or suppressors of numerous types of tumors including glioma. Previous studies have revealed that lncRNA maternally expressed gene 3 (MEG3) is involved in the initiation and progression of cancer; however, the underlying mechanisms remain unclear. In the present study, MEG3 was downregulated in glioma tissue. In addition, downregulation of MEG3 was observed in human glioma cell lines compared with normal astrocyte cells. Furthermore, overexpressed MEG3 inhibited the proliferation, migration and invasion of glioma cells. Additionally, microRNA-96-5p (miR-96-5p) was a promising target of MEG3, and the promoting effects of miR-96-5p on cell growth and metastasis could be reversed by upregulated MEG3. Metastasis suppressor 1 (MTSS1) was predicted as the putative target of miR-96-5p, and its expression was restored by MEG3. In summary, the present data provided novel insight into the roles of MEG3 in glioma, and MEG3/miR-96-5p/MTSS1 signaling could be a promising therapeutic target for the treatment of patients with glioma.

Inferring Latent Disease-lncRNA Associations by Faster Matrix Completion on a Heterogeneous Network

Current studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in a variety of fundamental biological processes related to complex human diseases. The prediction of latent disease-lncRNA associations can help to understand the pathogenesis of complex human diseases at the level of lncRNA, which also contributes to the detection of disease biomarkers, and the diagnosis, treatment, prognosis and prevention of disease. Nevertheless, it is still a challenging and urgent task to accurately identify latent disease-lncRNA association. Discovering latent links on the basis of biological experiments is time-consuming and wasteful, necessitating the development of computational prediction models. In this study, a computational prediction model has been remodeled as a matrix completion framework of the recommendation system by completing the unknown items in the rating matrix. A novel method named faster randomized matrix completion for latent disease-lncRNA association prediction (FRMCLDA) has been proposed by virtue of improved randomized partial SVD (rSVD-BKI) on a heterogeneous bilayer network. First, the correlated data source and experimentally validated information of diseases and lncRNAs are integrated to construct a heterogeneous bilayer network. Next, the integrated heterogeneous bilayer network can be formalized as a comprehensive adjacency matrix which includes lncRNA similarity matrix, disease similarity matrix, and disease-lncRNA association matrix where the uncertain disease-lncRNA associations are referred to as blank items. Then, a matrix approximate to the original adjacency matrix has been designed with predicted scores to retrieve the blank items. The construction of the approximate matrix could be equivalently resolved by the nuclear norm minimization. Finally, a faster singular value thresholding algorithm with a randomized partial SVD combing a new sub-space reuse technique has been utilized to complete the adjacency matrix. The results of leave-one-out cross-validation (LOOCV) experiments and 5-fold cross-validation (5-fold CV) experiments on three different benchmark databases have confirmed the availability and adaptability of FRMCLDA in inferring latent relationships of disease-lncRNA pairs, and in inferring lncRNAs correlated with novel diseases without any prior interaction information. Additionally, case studies have shown that FRMCLDA is able to effectively predict latent lncRNAs correlated with three widespread malignancies: prostate cancer, colon cancer, and gastric cancer.

Emerging Role of USP8, HMGA, and Non-Coding RNAs in Pituitary Tumorigenesis

Two novel molecular mechanisms with a driver role in pituitary tumorigenesis have been recently identified. They are (a) mutations in the Ubiquitin-Specific Protease 8 (USP8) gene in corticotroph tumors and (b) overexpression of the HMGA1 and HMGA2 genes in most of the pituitary tumors. Moreover, deregulated expression of the non-coding RNAs has been very frequently observed in this neoplasia. The aim of this review is to better elucidate the role, the mechanisms, and the possible clinical impact of these novel alterations in the development of pituitary neoplasia.

Conserved Pseudoknots in lncRNA MEG3 Are Essential for Stimulation of the p53 Pathway

Long non-coding RNAs (lncRNAs) are key regulatory molecules, but unlike with other RNAs, the direct link between their tertiary structure motifs and their function has proven elusive. Here we report structural and functional studies of human maternally expressed gene 3 (MEG3), a tumor suppressor lncRNA that modulates the p53 response. We found that, in an evolutionary conserved region of MEG3, two distal motifs interact by base complementarity to form alternative, mutually exclusive pseudoknot structures ("kissing loops"). Mutations that disrupt these interactions impair MEG3-dependent p53 stimulation in vivo and disrupt MEG3 folding in vitro. These findings provide mechanistic insights into regulation of the p53 pathway by MEG3 and reveal how conserved motifs of tertiary structure can regulate lncRNA biological function.

LncRNA MEG3 inhibits cell proliferation and induces apoptosis in laryngeal cancer via miR-23a/APAF-1 axis

Long non‐coding RNA (LncRNA) MEG3 serves a regulatory role in the progression of several types of cancer, but the role of MEG3 in laryngeal cancer is still unknown. The aim of this study was to explore the regulatory role and mechanism of MEG3 in laryngeal cancer. MEG3 expression in 50 laryngeal cancer tissue samples was detected by reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR). The effects of MEG3 overexpression on laryngeal cancer cells were investigated in vitro and in vivo. The mechanism of competitive endogenous RNA (ceRNA) was validated through luciferase reporter assay, RT‐qPCR and Western blotting. MEG3 was down‐regulated in laryngeal cancer tissues, and the low MEG3 expression was associated with advanced clinical stage. Additionally, MEG3 overexpression inhibited the proliferation and induced the apoptosis of laryngeal cancer cells in vitro and in vivo. Particularly, MEG3 bound to miR‐23a specifically and a reciprocal negative regulation existed between miR‐23a and MEG3. Moreover, MEG3 up‐regulated apoptotic protease activating factor‐1 (APAF‐1), a known miR‐23a's target, thereby leading to the activation of caspase‐9 and caspase‐3. Meanwhile, these activated effects were rescued by miR‐23a overexpression. In conclusion, the present study demonstrated that MEG3 functions as a novel tumour suppressive LncRNA in laryngeal cancer for the first time. Furthermore, MEG3 may act as a ceRNA to regulate APAF‐1 expression by competitive binding to miR‐23a, thereby regulating the progression of laryngeal cancer.

Genome imprinting in stem cells: A mini-review

Genomic imprinting is an epigenetic process result in silencing of one of the two alleles (maternal or paternal) based on the parent of origin. Dysregulation of imprinted genes results in detectable developmental and differential abnormalities. Epigenetics erasure is required for resetting the cell identity to a ground state during the production of induced pluripotent stem (iPS) cells from somatic cells. There are some contradictory reports regarding the status of the imprinting marks in the genome of iPS cells. Additionally, many studies highlighted the existence of subtle differences in the imprinting loci between different types of iPS cells and embryonic stem (ES) cells. These observations could ultimately undermine the use of patient-derived iPS cells for regenerative medicine.

Cadmium exposure and MEG3 methylation differences between Whites and African Americans in the NEST Cohort

Cadmium (Cd) is a ubiquitous environmental pollutant associated with a wide range of health outcomes including cancer. However, obscure exposure sources often hinder prevention efforts. Further, although epigenetic mechanisms are suspected to link these associations, gene sequence regions targeted by Cd are unclear. Aberrant methylation of a differentially methylated region (DMR) on the MEG3 gene that regulates the expression of a cluster of genes including MEG3, DLK1, MEG8, MEG9 and DIO3 has been associated with multiple cancers. In 287 infant-mother pairs, we used a combination of linear regression and the Getis-Ord Gi* statistic to determine if maternal blood Cd concentrations were associated with offspring CpG methylation of the sequence region regulating a cluster of imprinted genes including MEG3. Correlations were used to examine potential sources and routes. We observed a significant geographic co-clustering of elevated prenatal Cd levels and MEG3 DMR hypermethylation in cord blood (P = 0.01), and these findings were substantiated in our statistical models (β = 1.70, se = 0.80, P = 0.03). These associations were strongest in those born to African American women (β = 3.52, se = 1.32, P = 0.01) compared with those born to White women (β = 1.24, se = 2.11, P = 0.56) or Hispanic women (β = 1.18, se = 1.24, P = 0.34). Consistent with Cd bioaccumulation during the life course, blood Cd levels increased with age (β = 0.015 µg/dl/year, P = 0.003), and Cd concentrations were significantly correlated between blood and urine (ρ > 0.47, P < 0.01), but not hand wipe, soil or house dust concentrations (P > 0.05). Together, these data support that prenatal Cd exposure is associated with aberrant methylation of the imprint regulatory element for the MEG3 gene cluster at birth. However, neither house-dust nor water are likely exposure sources, and ingestion via contaminated hands is also unlikely to be a significant exposure route in this population. Larger studies are required to identify routes and sources of exposure.

The Role of Non-Coding RNAs Involved in Nickel-Induced Lung Carcinogenic Mechanisms

Nickel is a naturally occurring element found in the Earth’s crust and an International Agency for Research on Cancer (IARC)-classified human carcinogen. While low levels found in the natural environment pose a minor concern, the extensive use of nickel in industrial settings such as in the production of stainless steel and various alloys complicate human exposure and health effects. Notably, interactions with nickel macromolecules, primarily through inhalation, have been demonstrated to promote lung cancer. Mechanisms of nickel-carcinogenesis range from oxidative stress, DNA damage, and hypoxia-inducible pathways to epigenetic mechanisms. Recently, non-coding RNAs have drawn increased attention in cancer mechanistic studies. Specifically, nickel has been found to disrupt expression and functions of micro-RNAs and long-non-coding RNAs, resulting in subsequent changes in target gene expression levels, some of which include key cancer genes such as p53, MDM2, c-myc, and AP-1. Non-coding RNAs are also involved in well-studied mechanisms of nickel-induced lung carcinogenesis, such as the hypoxia-inducible factor (HIF) pathway, oxidative stress, DNA damage and repair, DNA hypermethylation, and alterations in tumor suppressors and oncogenes. This review provides a summary of the currently known epigenetic mechanisms involved in nickel-induced lung carcinogenesis, with a particular focus on non-coding RNAs.

Structural characterization of maternally expressed gene 3 RNA reveals conserved motifs and potential sites of interaction with polycomb repressive complex 2

Long non-coding RNAs (lncRNAs) have emerged as key players in gene regulation. However, our incomplete understanding of the structure of lncRNAs has hindered molecular characterization of their function. Maternally expressed gene 3 (Meg3) lncRNA is a tumor suppressor that is downregulated in various types of cancer. Mechanistic studies have reported a role for Meg3 in epigenetic regulation by interacting with chromatin-modifying complexes such as the polycomb repressive complex 2 (PRC2), guiding them to genomic sites via DNA-RNA triplex formation. Resolving the structure of Meg3 RNA and characterizing its interactions with cellular binding partners will deepen our understanding of tumorigenesis and provide a framework for RNA-based anti-cancer therapies. Herein, we characterize the architectural landscape of Meg3 RNA and its interactions with PRC2 from a functional standpoint.

High glucose regulates ERp29 in hepatocellular carcinoma by LncRNA MEG3-miRNA 483-3p pathway

AIMS

Blood glucose dysregulation is an adverse factor in the prognosis of hepatocellular carcinoma (HCC). Endoplasmic reticulum (ER) is thought to be crucial component in the development of cancer and diabetes. This study aimed to investigate the mechanisms of poor outcomes in HCC patients with diabetes.

MAIN METHODS

ER protein 29 (ERp29) was predicted by proteomics, immunohistochemistry, Western blot, Cell Counting Kit-8 (CCK-8) and cell scratch test were used to identify the expression and biological effects of ERp29 under high glucose (HG) in HCC cells. Bioinformatics found a competing endogenous RNAs (ceRNAs) regulatory network between microRNA-483-3p (miR-483-3p) and Long noncoding RNA (LncRNA MEG3), the above methods also were used to identify their expression, biological effects and their roles of HG on regulation of REp29 in HCC cells, Dual-luciferase reporter assay was carried out to study the interaction of ERp29 with miR-483-3p and miR-483-3p with MEG3.

KEY FINDINGS

HG upregulated miR-483-3p expression in HCC cells and miR-483-3p overexpression suppressed ERp29 expression and also increased HCC cell proliferation and migration. Furthermore, we found that MEG3 was decreased in HCC cells incubated in medium with high glucose and knockdown of MEG3 downregulated ERp29 expression. Bioinformatics analysis found that MEG3 mediated its protective effects via binding to miR-483-3p.

SIGNIFICANCE

Overall, our study established a novel regulatory network of LncRNA MEG3/miR483-3p/ERp29 in HCC which may be helpful in better understanding the effect of high glucose on poor prognosis of HCC and in exploring new diagnostic and therapeutic tools for managing HCC in patients with diabetes.