Ultraconserved regions encoding ncRNAs are altered in human leukemias and carcinomas

Non-coding transcribed ultraconserved region uc.290 in colon mucosa promotes intestinal fibrosis in chronic active ulcerative colitis

BACKGROUND AND AIMS

TGF-β1 induces epithelial-mesenchymal transition (EMT) and leads to intestinal fibrosis in ulcerative colitis (UC). We aimed to investigate the expression of transcribed ultraconserved region uc.290 in chronic UC and its role in intestinal fibrosis.

METHODS

Colon specimens were taken from thirty chronic active UC, chronic inactive UC and healthy controls respectively. Modified Mayo score, expressions of uc.290, TGF-β1, EMT biomarkers (Vimentin, α-SMA and E-cadherin) and intestinal fibrosis biomarker (collagen Ⅲ) in colon biopsy specimens were determined in human. Expressions of TGF-β1, EMT biomarkers and collagen Ⅲ were determined in uc.290 overexpressed or silenced epithelial colon cells (HT29).

RESULTS

Uc.290, TGF-β1 and collagen Ⅲ were overexpressed, and EMT was prominent in chronic active UC. Uc.290 level had a positive correlation with modified Mayo score in chronic active UC. TGF-β1 and collagen Ⅲ were overexpressed, and EMT was prominent in uc.290 overexpressed HT29 cells.

CONCLUSIONS

Uc.290 was overexpressed in chronic active UC and might promote intestinal fibrosis by TGF-β1/EMT/collagen Ⅲ pathway.

RPI-EDLCN: An Ensemble Deep Learning Framework Based on Capsule Network for ncRNA-Protein Interaction Prediction

Noncoding RNAs (ncRNAs) play crucial roles in many cellular life activities by interacting with proteins. Identification of ncRNA-protein interactions (ncRPIs) is key to understanding the function of ncRNAs. Although a number of computational methods for predicting ncRPIs have been developed, the problem of predicting ncRPIs remains challenging. It has always been the focus of ncRPIs research to select suitable feature extraction methods and develop a deep learning architecture with better recognition performance. In this work, we proposed an ensemble deep learning framework, RPI-EDLCN, based on a capsule network (CapsuleNet) to predict ncRPIs. In terms of feature input, we extracted the sequence features, secondary structure sequence features, motif information, and physicochemical properties of ncRNA/protein. The sequence and secondary structure sequence features of ncRNA/protein are encoded by the conjoint k-mer method and then input into an ensemble deep learning model based on CapsuleNet by combining the motif information and physicochemical properties. In this model, the encoding features are processed by convolution neural network (CNN), deep neural network (DNN), and stacked autoencoder (SAE). Then the advanced features obtained from the processing are input into the CapsuleNet for further feature learning. Compared with other state-of-the-art methods under 5-fold cross-validation, the performance of RPI-EDLCN is the best, and the accuracy of RPI-EDLCN on RPI1807, RPI2241, and NPInter v2.0 data sets was 93.8%, 88.2%, and 91.9%, respectively. The results of the independent test indicated that RPI-EDLCN can effectively predict potential ncRPIs in different organisms. In addition, RPI-EDLCN successfully predicted hub ncRNAs and proteins in Mus musculus ncRNA-protein networks. Overall, our model can be used as an effective tool to predict ncRPIs and provides some useful guidance for future biological studies.

AMPFLDAP: Adaptive Message Passing and Feature Fusion on Heterogeneous Network for LncRNA-Disease Associations Prediction

Exploration of the intricate connections between long noncoding RNA (lncRNA) and diseases, referred to as lncRNA-disease associations (LDAs), plays a pivotal and indispensable role in unraveling the underlying molecular mechanisms of diseases and devising practical treatment approaches. It is imperative to employ computational methods for predicting lncRNA-disease associations to circumvent the need for superfluous experimental endeavors. Graph-based learning models have gained substantial popularity in predicting these associations, primarily because of their capacity to leverage node attributes and relationships within the network. Nevertheless, there remains much room for enhancing the performance of these techniques by incorporating and harmonizing the node attributes more effectively. In this context, we introduce a novel model, i.e., Adaptive Message Passing and Feature Fusion (AMPFLDAP), for forecasting lncRNA-disease associations within a heterogeneous network. Firstly, we constructed a heterogeneous network involving lncRNA, microRNA (miRNA), and diseases based on established associations and employing Gaussian interaction profile kernel similarity as a measure. Then, an adaptive topological message passing mechanism is suggested to address the information aggregation for heterogeneous networks. The topological features of nodes in the heterogeneous network were extracted based on the adaptive topological message passing mechanism. Moreover, an attention mechanism is applied to integrate both topological and semantic information to achieve the multimodal features of biomolecules, which are further used to predict potential LDAs. The experimental results demonstrated that the performance of the proposed AMPFLDAP is superior to seven state-of-the-art methods. Furthermore, to validate its efficacy in practical scenarios, we conducted detailed case studies involving three distinct diseases, which conclusively demonstrated AMPFLDAP's effectiveness in the prediction of LDAs.

A first comprehensive analysis of Transcribed Ultra Conserved Regions uncovers important regulatory functions of novel non-coding transcripts in gliomas

Transcribed Ultra-Conserved Regions (TUCRs) represent a severely understudied class of putative non-coding RNAs (ncRNAs) that are 100% conserved across multiple species. We performed the first-ever analysis of TUCRs in glioblastoma (GBM) and low-grade gliomas (LGG). We leveraged large human datasets to identify the genomic locations, chromatin accessibility, transcription, differential expression, correlation with survival, and predicted functions of all 481 TUCRs, and identified TUCRs that are relevant to glioma biology. Of these, we investigated the expression, function, and mechanism of action of the most highly upregulated intergenic TUCR, uc.110, identifying it as a new oncogene. Uc.110 was highly overexpressed in GBM and LGG, where it promoted malignancy and tumor growth. Uc.110 activated the WNT pathway by upregulating the expression of membrane frizzled-related protein (MFRP), by sponging the tumor suppressor microRNA miR-544. This pioneering study shows important roles for TUCRs in gliomas and provides an extensive database and novel methods for future TUCR research.

Non-coding RNAs in disease: from mechanisms to therapeutics

Non-coding RNAs (ncRNAs) are a heterogeneous group of transcripts that, by definition, are not translated into proteins. Since their discovery, ncRNAs have emerged as important regulators of multiple biological functions across a range of cell types and tissues, and their dysregulation has been implicated in disease. Notably, much research has focused on the link between microRNAs (miRNAs) and human cancers, although other ncRNAs, such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), are also emerging as relevant contributors to human disease. In this Review, we summarize our current understanding of the roles of miRNAs, lncRNAs and circRNAs in cancer and other major human diseases, notably cardiovascular, neurological and infectious diseases. Further, we discuss the potential use of ncRNAs as biomarkers of disease and as therapeutic targets.

Non-Coding RNAs as Key Regulators in Lung Cancer

For several decades, most lung cancer investigations have focused on the search for mutations in candidate genes; however, in the last decade, due to the fact that most of the human genome is occupied by sequences that do not code for proteins, much attention has been paid to non-coding RNAs (ncRNAs) that perform regulatory functions. In this review, we principally focused on recent studies of the function, regulatory mechanisms, and therapeutic potential of ncRNAs including microRNA (miRNA), long ncRNA (lncRNA), and circular RNA (circRNA) in different types of lung cancer.

The expression and function of long noncoding RNAs in hepatocellular carcinoma

With the deepening of the genome project study, attention on noncoding RNAs is increasing. Long noncoding RNAs (lncRNAs) have become a new research hotspot. A growing number of studies have revealed that lncRNAs are involved in tumorigenesis and tumor suppressor pathways. Aberrant expressions of lncRNAs have been found in a variety of human tumors including hepatocellular carcinoma (HCC). In this review, we provide a brief introduction to lncRNA and highlight recent research on the functions and clinical significance of lncRNAs in HCC.

Traditional Banxia Xiexin decoction inhibits invasion, metastasis, and epithelial mesenchymal transition in gastric cancer by reducing lncRNA TUC338 expression

Background

Banxia Xiexin decoction (BXD) is a classic traditional Chinese medicine (TCM) formula clinically used to treat chronic gastritis, gastric ulcers, gastric cancer, and many other gastrointestinal diseases. Long noncoding RNAs (lncRNAs) have been shown to play an important role in maintaining the malignant phenotype of tumors. However, no relevant studies have shown whether Banxia Xiexin decoction regulates and controls lncRNA TUC338, and the effect of TUC338 on the regulation of gastric cancer invasion and metastasis remains unclear.

Purpose

To investigate the ability of the traditional Chinese medicine (TCM) Banxia Xiexin decoction (BXD) to inhibit the migration and invasion of human gastric cancer AGS cells by regulating the long noncoding RNA (lncRNA) TUC338.

Methods

UHPLC‒MS/MS was used to analyze the chemical components of BXD. MTT was performed to determine the effects of BXD on the proliferation of AGS cells. qRT‒PCR was used to determine the expression of lncRNA TUC338 in gastric cancer tissues, paracarcinoma tissues, AGS human gastric cancer cells and GES-1 normal gastric mucosa cells and to evaluate the effects of BXD on the expression of lncRNA TUC338 in AGS cells. Lentiviral transfection was used to establish human gastric cancer AGS cells with knocked down lncRNA TUC338 expression. The effects of lncRNA TUC338 knockdown on the migration and invasion of AGS cells were observed by a scratch assay and Transwell migration assay, respectively. Western blotting was performed to analyze the effects of lncRNA TUC338 knockdown on epithelial-to-mesenchymal transition (EMT) in AGS cells. We performed quality control on three batches of BXD. We used UHPLC‒MS/MS to control the quality of three random batches of BXD used throughout the study.

Results

Ninety-five chemical components were identified from the water extract of BXD, some of which have anticancer effects. The expression of TUC.338 in gastric cancer tissues was higher than that in para-carcinoma tissues. BXD inhibited the invasion and migration of gastric cancer cells by inhibiting the expression of lncRNA TUC338, which reduced EMT. After knockdown of lncRNA TUC338, the migration and invasion of AGS cells were reduced; the expression of the EMT-related protein E-cadherin was increased, and the expression of N-cadherin and vimentin was reduced.

Conclusions

The present results suggest that BXD has potential as an effective treatment for gastric cancer through the inhibition of lncRNA TUC338 expression.

Delineating highly transcribed noncoding elements landscape in breast cancer

Highly transcribed noncoding elements (HTNEs) are critical noncoding elements with high levels of transcriptional capacity in particular cohorts involved in multiple cellular biological processes. Investigation of HTNEs with persistent aberrant expression in abnormal tissues could be of benefit in exploring their roles in disease occurrence and progression. Breast cancer is a highly heterogeneous disease for which early screening and prognosis are exceedingly crucial. In this study, we developed a HTNE identification framework to systematically investigate HTNE landscapes in breast cancer patients and identified over ten thousand HTNEs. The robustness and rationality of our framework were demonstrated via public datasets. We revealed that HTNEs had significant chromatin characteristics of enhancers and long noncoding RNAs (lncRNAs) and were significantly enriched with RNA-binding proteins as well as targeted by miRNAs. Further, HTNE-associated genes were significantly overexpressed and exhibited strong correlations with breast cancer. Ultimately, we explored the subtype-specific transcriptional processes associated with HTNEs and uncovered the HTNE signatures that could classify breast cancer subtypes based on the properties of hormone receptors. Our results highlight that the identified HTNEs as well as their associated genes play crucial roles in breast cancer progression and correlate with subtype-specific transcriptional processes of breast cancer.

Long non-coding RNAs in lung cancer: Unraveling the molecular modulators of MAPK signaling

Lung cancer (LC) continues to pose a significant global medical burden, necessitating a comprehensive understanding of its molecular foundations to establish effective treatment strategies. The mitogen-activated protein kinase (MAPK) signaling system has been scientifically associated with LC growth; however, the intricate regulatory mechanisms governing this system remain unknown. Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of diverse cellular activities, including cancer growth. LncRNAs have been implicated in LC, which can function as oncogenes or tumor suppressors, and their dysregulation has been linked to cancer cell death, metastasis, spread, and proliferation. Due to their involvement in critical pathophysiological processes, lncRNAs are gaining attention as potential candidates for anti-cancer treatments. This article aims to elucidate the regulatory role of lncRNAs in MAPK signaling in LC. We provide a comprehensive review of the key components of the MAPK pathway and their relevance in LC, focusing on aberrant signaling processes associated with disease progression. By examining recent research and experimental findings, this article examines the molecular mechanisms through which lncRNAs influence MAPK signaling in lung cancer, ultimately contributing to tumor development.

Crosstalk between long noncoding RNA and microRNA in Cancer

miRNAs and lncRNAs play a central role in cancer-associated gene regulations. The dysregulated expression of lncRNAs has been reported as a hallmark of cancer progression, acting as an independent prediction marker for an individual cancer patient. The interplay of miRNA and lncRNA decides the variation of tumorigenesis that could be mediated by acting as sponges for endogenous RNAs, regulating miRNA decay, mediating intra-chromosomal interactions, and modulating epigenetic components. This paper focuses on the influence of crosstalk between lncRNA and miRNA on cancer hallmarks such as epithelial-mesenchymal transition, hijacking cell death, metastasis, and invasion. Other cellular roles of crosstalks, such as neovascularization, vascular mimicry, and angiogenesis were also discussed. Additionally, we reviewed crosstalk mechanism with specific host immune responses and targeting interplay (between lncRNA and miRNA) in cancer diagnosis and management.

Targeting miRNAs and Other Non-Coding RNAs as a Therapeutic Approach: An Update

Since the discovery of the first microRNAs (miRNAs, miRs), the understanding of miRNA biology has expanded substantially. miRNAs are involved and described as master regulators of the major hallmarks of cancer, including cell differentiation, proliferation, survival, the cell cycle, invasion, and metastasis. Experimental data indicate that cancer phenotypes can be modified by targeting miRNA expression, and because miRNAs act as tumor suppressors or oncogenes (oncomiRs), they have emerged as attractive tools and, more importantly, as a new class of targets for drug development in cancer therapeutics. With the use of miRNA mimics or molecules targeting miRNAs (i.e., small-molecule inhibitors such as anti-miRS), these therapeutics have shown promise in preclinical settings. Some miRNA-targeted therapeutics have been extended to clinical development, such as the mimic of miRNA-34 for treating cancer. Here, we discuss insights into the role of miRNAs and other non-coding RNAs in tumorigenesis and resistance and summarize some recent successful systemic delivery approaches and recent developments in miRNAs as targets for anticancer drug development. Furthermore, we provide a comprehensive overview of mimics and inhibitors that are in clinical trials and finally a list of clinical trials based on miRNAs.

Ultra-conserved RNA: a novel biological tool with diagnostic and therapeutic potential

Ultra-conserved RNA (ucRNA) is a subset of long non-coding RNA, that is highly conserved among mice, rats and humans. UcRNA has attracted extensive attention in recent years for its potential biological significance in normal physiological function and diseases. However, due to the instability of RNA and the technical limitation, the function and mechanism of ucRNAs are largely unknown. Over the last two decades, researchers have made a lot of efforts to try to lift the veil of ucRNA in nervous, cardiovascular system and other systems as well as cancers. Since the concept of the glymphatic system is relatively new, we summarized here recent findings on the functions, regulation and the underlying mechanisms of ucRNAs in physiology and pathology. Meanwhile, pathology in some diseases is likely to contribute to abnormal expression of ucRNA in turn. We also discuss the technical challenges and bright prospects for future applications of ucRNAs in the diagnosis and treatment of diseases.

LINC00115 regulates lung adenocarcinoma progression via sponging miR-154-3p to modulate Sp3 expression

The most commonly diagnosed and most lethal subtype of lung cancer is lung adenocarcinoma (LUAD). Therefore, more detailed understanding of the potential mechanism and identification of potential targets of lung adenocarcinoma is needed. A growing number of reports reveals that long non-coding RNAs (lncRNAs) play crucial roles in cancer progression. In present study, we found that lncRNA LINC00115 was upregulated in LUAD tissues and cells. Functional studies revealed that LINC00115 knockdown inhibits the proliferation, growth, invasion, and migration of LUAD cells. Mechanically, we indicated that miR-154-3p is target microRNA of LINC00115, and the effect of downregulated LINC00115 on LUAD cells was partially reversed by the miR-154-3p antisense oligonucleotide (ASO-miR-154-3p). Further investigation revealed that Specificity protein 3 (Sp3) directly interacted with miR-154-3p, and the Sp3 level was positively correlated with the LINC00115 expression. Rescue experiments further showed that Sp3 overexpression partially restored the effect of downregulated LINC00115 on LUAD cells. Similarly, in vivo experiments confirmed that downregulated LINC00115 inhibited xenograft growth and Sp3 expression. Our results demonstrated that LINC00115 knockdown inhibited LUAD progression via sponging miR-154-3p to modulate Sp3 expression. These data indicate that the LINC00115/miR-154-3p/Sp3 axis can be a potential therapeutic target of LUAD.

A new biomarker panel of ultraconserved long non-coding RNAs for bladder cancer prognosis by a machine learning based methodology

BACKGROUND

Recent studies have indicated that a special class of long non-coding RNAs (lncRNAs), namely Transcribed-Ultraconservative Regions are transcribed from specific DNA regions (T-UCRs), 100[Formula: see text] conserved in human, mouse, and rat genomes. This is noticeable, as lncRNAs are usually poorly conserved. Despite their peculiarities, T-UCRs remain very understudied in many diseases, including cancer and, yet, it is known that dysregulation of T-UCRs is associated with cancer as well as with human neurological, cardiovascular, and developmental pathologies. We have recently reported the T-UCR uc.8+ as a potential prognostic biomarker in bladder cancer.

RESULTS

The aim of this work is to develop a methodology, based on machine learning techniques, for the selection of a predictive signature panel for bladder cancer onset. To this end, we analyzed the expression profiles of T-UCRs from surgically removed normal and bladder cancer tissues, by using custom expression microarray. Bladder tissue samples from 24 bladder cancer patients (12 Low Grade and 12 High Grade), with complete clinical data, and 17 control samples from normal bladder epithelium were analysed. After the selection of preferentially expressed and statistically significant T-UCRs, we adopted an ensemble of statistical and machine learning based approaches (i.e., logistic regression, Random Forest, XGBoost and LASSO) for ranking the most important diagnostic molecules. We identified a signature panel of 13 selected T-UCRs with altered expression profiles in cancer, able to efficiently discriminate between normal and bladder cancer patient samples. Also, using this signature panel, we classified bladder cancer patients in four groups, each characterized by a different survival extent. As expected, the group including only Low Grade bladder cancer patients had greater overall survival than patients with the majority of High Grade bladder cancer. However, a specific signature of deregulated T-UCRs identifies sub-types of bladder cancer patients with different prognosis regardless of the bladder cancer Grade.

CONCLUSIONS

Here we present the results for the classification of bladder cancer (Low and High Grade) patient samples and normal bladder epithelium controls by using a machine learning application. The T-UCR's panel can be used for learning an eXplainable Artificial Intelligent model and develop a robust decision support system for bladder cancer early diagnosis providing urinary T-UCRs data of new patients. The use of this system instead of the current methodology will result in a non-invasive approach, reducing uncomfortable procedures (such as cystoscopy) for the patients. Overall, these results raise the possibility of new automatic systems, which could help the RNA-based prognosis and/or the cancer therapy in bladder cancer patients, and demonstrate the successful application of Artificial Intelligence to the definition of an independent prognostic biomarker panel.

Construction of a three-component regulatory network of transcribed ultraconserved regions for the identification of prognostic biomarkers in gastric cancer

Altered expression and functional roles of the transcribed ultraconserved regions (T-UCRs), as genomic sequences with 100% conservation between the genomes of human, mouse, and rat, in the pathophysiology of neoplasms has already been investigated. Nevertheless, the relevance of the functions for T-UCRs in gastric cancer (GC) is still the subject of inquiry. In the current study, we first used a genome-wide profiling approach to analyze the expression of T-UCRs in GC patients. Then, we constructed a three-component regulatory network and investigated potential diagnostic and prognostic values of the T-UCRs. The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) dataset was used as a resource for the RNA-sequencing data. FeatureCounts was utilized to quantify the number of reads mapped to each T-UCR. Differential expression analysis was then conducted using DESeq2. In the following, interactions between T-UCRs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were combined into a three-component network. Enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. The R Survival package was utilized to identify survival-related significantly differentially expressed T-UCRs (DET-UCRs). Using an in-house cohort of GC tissues, expression of two DET-UCRs was furthermore experimentally verified. Our results showed that several T-UCRs were dysregulated in TCGA-STAD tumoral samples compared to nontumoral counterparts. The three-component network was constructed which composed of DET-UCRs, miRNAs, and mRNAs nodes. Functional enrichment and PPI network analyses revealed important enriched signaling pathways and gene ontologies such as "pathway in cancer" and regulation of cell proliferation and apoptosis. Five T-UCRs were significantly correlated with the overall survival of GC patients. While no expression of uc.232 was observed in our in-house cohort of GC tissues, uc.343 showed an increased expression, although not statistically significant, in gastric tumoral tissues. The constructed three-component regulatory network of T-UCRs in GC presents a comprehensive understanding of the underlying gene expression regulation processes involved in tumor development and can serve as a basis to investigate potential prognostic biomarkers and therapeutic targets.

Emerging role of oncogenic long noncoding RNA as cancer biomarkers

The view of long noncoding RNAs as nonfunctional "garbage" has been definitely outdated by the large body of evidence indicating this class of ncRNAs as "golden junk", especially in precision oncology. Indeed, in light of their oncogenic role and the higher expression in multiple cancer types compared with paired adjacent tissues, the clinical interest for lncRNAs as diagnostic and/or prognostic biomarkers has been rapidly increasing. The emergence of large-scale sequencing technologies, their subsequent diffusion even in small research and clinical centers, the technological advances for the detection of low-copy lncRNAs in body fluids, coupled to the huge reduction of operating costs, have nowadays made possible to rapidly and comprehensively profile them in multiple tumors and large cohorts. In this review, we first summarize some relevant data about the oncogenic role of well-studied lncRNAs having a clinical relevance. Then, we focus on the description of their potential use as diagnostic/prognostic biomarkers, including an updated overview about licensed patents or clinical trials on lncRNAs in oncology.

ncDENSE: a novel computational method based on a deep learning framework for non-coding RNAs family prediction

BACKGROUND

Although research on non-coding RNAs (ncRNAs) is a hot topic in life sciences, the functions of numerous ncRNAs remain unclear. In recent years, researchers have found that ncRNAs of the same family have similar functions, therefore, it is important to accurately predict ncRNAs families to identify their functions. There are several methods available to solve the prediction problem of ncRNAs family, whose main ideas can be divided into two categories, including prediction based on the secondary structure features of ncRNAs, and prediction according to sequence features of ncRNAs. The first type of prediction method requires a complicated process and has a low accuracy in obtaining the secondary structure of ncRNAs, while the second type of method has a simple prediction process and a high accuracy, but there is still room for improvement. The existing methods for ncRNAs family prediction are associated with problems such as complicated prediction processes and low accuracy, in this regard, it is necessary to propose a new method to predict the ncRNAs family more perfectly.

RESULTS

A deep learning model-based method, ncDENSE, was proposed in this study, which predicted ncRNAs families by extracting ncRNAs sequence features. The bases in ncRNAs sequences were encoded by one-hot coding and later fed into an ensemble deep learning model, which contained the dynamic bi-directional gated recurrent unit (Bi-GRU), the dense convolutional network (DenseNet), and the Attention Mechanism (AM). To be specific, dynamic Bi-GRU was used to extract contextual feature information and capture long-term dependencies of ncRNAs sequences. AM was employed to assign different weights to features extracted by Bi-GRU and focused the attention on information with greater weights. Whereas DenseNet was adopted to extract local feature information of ncRNAs sequences and classify them by the full connection layer. According to our results, the ncDENSE method improved the Accuracy, Sensitivity, Precision, F-score, and MCC by 2.08[Formula: see text], 2.33[Formula: see text], 2.14[Formula: see text], 2.16[Formula: see text], and 2.39[Formula: see text], respectively, compared with the suboptimal method.

CONCLUSIONS

Overall, the ncDENSE method proposed in this paper extracts sequence features of ncRNAs by dynamic Bi-GRU and DenseNet and improves the accuracy in predicting ncRNAs family and other data.

Lnc-uc.147 Is Associated with Disease Stage of Liver, Gastric, and Renal Cancer

Lnc-uc.147, a long non-coding RNA derived from a transcribed ultraconserved region (T-UCR), was previously evidenced in breast cancer. However, the role of this region in other tumor types was not previously investigated. The present study aimed to investigate lnc-uc.147 in different types of cancer, as well as to suggest lnc-uc.147 functional and regulation aspects. From solid tumor datasets analysis of The Cancer Genome Atlas (TCGA), deregulated lnc-uc.147 expression was associated with the histologic grade of hepatocellular carcinoma, and with the tumor stage of clear cell renal and gastric adenocarcinoma. Considering the epidemiologic relevance of liver cancer, silencing lnc-uc.147 reduced the viability and clonogenic capacity of HepG2 cell lines. Additionally, we suggest a relation between the transcription factor TEAD4 and lnc-uc.147 in liver and breast cancer cells.

Multi-view contrastive heterogeneous graph attention network for lncRNA-disease association prediction

MOTIVATION

Exploring the potential long noncoding RNA (lncRNA)-disease associations (LDAs) plays a critical role for understanding disease etiology and pathogenesis. Given the high cost of biological experiments, developing a computational method is a practical necessity to effectively accelerate experimental screening process of candidate LDAs. However, under the high sparsity of LDA dataset, many computational models hardly exploit enough knowledge to learn comprehensive patterns of node representations. Moreover, although the metapath-based GNN has been recently introduced into LDA prediction, it discards intermediate nodes along the meta-path and results in information loss.

RESULTS

This paper presents a new multi-view contrastive heterogeneous graph attention network (GAT) for lncRNA-disease association prediction, MCHNLDA for brevity. Specifically, MCHNLDA firstly leverages rich biological data sources of lncRNA, gene and disease to construct two-view graphs, feature structural graph of feature schema view and lncRNA-gene-disease heterogeneous graph of network topology view. Then, we design a cross-contrastive learning task to collaboratively guide graph embeddings of the two views without relying on any labels. In this way, we can pull closer the nodes of similar features and network topology, and push other nodes away. Furthermore, we propose a heterogeneous contextual GAT, where long short-term memory network is incorporated into attention mechanism to effectively capture sequential structure information along the meta-path. Extensive experimental comparisons against several state-of-the-art methods show the effectiveness of proposed framework.The code and data of proposed framework is freely available at https://github.com/zhaoxs686/MCHNLDA.

Transcribed Ultraconserved Regions: New regulators in cancer signaling and potential biomarkers

The ultraconserved regions (UCRs) are 481 genomic elements, longer than 200 bp, 100% conserved in human, mouse, and rat genomes. Usually, coding regions are more conserved, but more than 80% of UCRs are either intergenic or intronic, and many of them produce long non-coding RNAs (lncRNAs). Recently, the deregulated expression of transcribed UCRs (T-UCRs) has been associated with pathological conditions. But, differently from many lncRNAs with recognized crucial effects on malignant cell processes, the role of T-UCRs in the control of cancer cell networks is understudied. Furthermore, the potential utility of these molecules as molecular markers is not clear. Based on this information, the present review aims to organize information about T-UCRs with either oncogenic or tumor suppressor role associated with cancer cell signaling, and better describe T-UCRs with potential utility as prognosis markers. Out of 481 T-UCRs, 297 present differential expression in cancer samples, 23 molecules are associated with tumorigenesis processes, and 12 have more clear potential utility as prognosis markers. In conclusion, T-UCRs are deregulated in several tumor types, highlighted as important molecules in cancer networks, and with potential utility as prognosis markers, although further investigation for translational medicine is still needed.

The Role of Fascin-1 in Human Urologic Cancers: A Promising Biomarker or Therapeutic Target?

Human cancer statistics show that an increased incidence of urologic cancers such as bladder cancer, prostate cancer, and renal cell carcinoma. Due to the lack of early markers and effective therapeutic targets, their prognosis is poor. Fascin-1 is an actin-binding protein, which functions in the formation of cell protrusions by cross-linking with actin filaments. Studies have found that fascin-1 expression is elevated in most human cancers and is related to outcomes such as neoplasm metastasis, reduced survival, and increased aggressiveness. Fascin-1 has been considered as a potential therapeutic target for urologic cancers, but there is no comprehensive review to evaluate these studies. This review aimed to provide an enhanced literature review, outline, and summarize the mechanism of fascin-1 in urologic cancers and discuss the therapeutic potential of fascin-1 and the possibility of its use as a potential marker. We also focused on the correlation between the overexpression of fascin-1 and clinicopathological parameters. Mechanistically, fascin-1 is regulated by several regulators and signaling pathways (such as long noncoding RNA, microRNA, c-Jun N-terminal kinase, and extracellular regulated protein kinases). The overexpression of fascin-1 is related to clinicopathologic parameters such as pathological stage, bone or lymph node metastasis, and reduced disease-free survival. Several fascin-1 inhibitors (G2, NP-G2-044) have been evaluated in vitro and in preclinical models. The study proved the promising potential of fascin-1 as a newly developing biomarker and a potential therapeutic target that needs further investigation. The data also highlight the inadequacy of fascin-1 to serve as a novel biomarker for prostate cancer.

Long Non-Coding RNAs as Epigenetic Regulators of Immune Checkpoints in Cancer Immunity

In recent years, cancer treatment has undergone significant changes, predominantly in the shift towards immunotherapeutic strategies using immune checkpoint inhibitors. Despite the clinical efficacy of many of these inhibitors, the overall response rate remains modest, and immunotherapies for many cancers have proved ineffective, highlighting the importance of knowing the tumor microenvironment and heterogeneity of each malignancy in patients. Long non-coding RNAs (lncRNAs) have attracted increasing attention for their ability to control various biological processes by targeting different molecular pathways. Some lncRNAs have a regulatory role in immune checkpoints, suggesting they might be utilized as a target for immune checkpoint treatment. The focus of this review is to describe relevant lncRNAs and their targets and functions to understand key regulatory mechanisms that may contribute in regulating immune checkpoints. We also provide the state of the art on super-enhancers lncRNAs (selncRNAs) and circular RNAs (circRNAs), which have recently been reported as modulators of immune checkpoint molecules within the framework of human cancer. Other feasible mechanisms of interaction between lncRNAs and immune checkpoints are also reported, along with the use of miRNAs and circRNAs, in generating new tumor immune microenvironments, which can further help avoid tumor evasion.

Recent advances in machine learning methods for predicting LncRNA and disease associations

Long non-coding RNAs (lncRNAs) are involved in almost the entire cell life cycle through different mechanisms and play an important role in many key biological processes. Mutations and dysregulation of lncRNAs have been implicated in many complex human diseases. Therefore, identifying the relationship between lncRNAs and diseases not only contributes to biologists' understanding of disease mechanisms, but also provides new ideas and solutions for disease diagnosis, treatment, prognosis and prevention. Since the existing experimental methods for predicting lncRNA-disease associations (LDAs) are expensive and time consuming, machine learning methods for predicting lncRNA-disease associations have become increasingly popular among researchers. In this review, we summarize some of the human diseases studied by LDAs prediction models, association and similarity features of LDAs prediction, performance evaluation methods of models and some advanced machine learning prediction models of LDAs. Finally, we discuss the potential limitations of machine learning-based methods for LDAs prediction and provide some ideas for designing new prediction models.

Regulation Mechanisms of Meiotic Recombination Revealed from the Analysis of a Fission Yeast Recombination Hotspot ade6-M26

Meiotic recombination is a pivotal event that ensures faithful chromosome segregation and creates genetic diversity in gametes. Meiotic recombination is initiated by programmed double-strand breaks (DSBs), which are catalyzed by the conserved Spo11 protein. Spo11 is an enzyme with structural similarity to topoisomerase II and induces DSBs through the nucleophilic attack of the phosphodiester bond by the hydroxy group of its tyrosine (Tyr) catalytic residue. DSBs caused by Spo11 are repaired by homologous recombination using homologous chromosomes as donors, resulting in crossovers/chiasmata, which ensure physical contact between homologous chromosomes. Thus, the site of meiotic recombination is determined by the site of the induced DSB on the chromosome. Meiotic recombination is not uniformly induced, and sites showing high recombination rates are referred to as recombination hotspots. In fission yeast, ade6-M26, a nonsense point mutation of ade6 is a well-characterized meiotic recombination hotspot caused by the heptanucleotide sequence 5'-ATGACGT-3' at the M26 mutation point. In this review, we summarize the meiotic recombination mechanisms revealed by the analysis of the fission ade6-M26 gene as a model system.

Long noncoding RNA uc.230/CUG-binding protein 1 axis sustains intestinal epithelial homeostasis and response to tissue injury

Intestinal epithelial integrity is commonly disrupted in patients with critical disorders, but the exact underlying mechanisms are unclear. Long noncoding RNAs transcribed from ultraconserved regions (T-UCRs) control different cell functions and are involved in pathologies. Here, we investigated the role of T-UCRs in intestinal epithelial homeostasis and identified T-UCR uc.230 as a major regulator of epithelial renewal, apoptosis, and barrier function. Compared with controls, intestinal mucosal tissues from patients with ulcerative colitis and from mice with colitis or fasted for 48 hours had increased levels of uc.230. Silencing uc.230 inhibited the growth of intestinal epithelial cells (IECs) and organoids and caused epithelial barrier dysfunction. Silencing uc.230 also increased IEC vulnerability to apoptosis, whereas increasing uc.230 levels protected IECs against cell death. In mice with colitis, reduced uc.230 levels enhanced mucosal inflammatory injury and delayed recovery. Mechanistic studies revealed that uc.230 increased CUG-binding protein 1 (CUGBP1) by acting as a natural decoy RNA for miR-503, which interacts with Cugbp1 mRNA and represses its translation. These findings indicate that uc.230 sustains intestinal mucosal homeostasis by promoting epithelial renewal and barrier function and that it protects IECs against apoptosis by serving as a natural sponge for miR-503, thereby preserving CUGBP1 expression.

Predicting miRNA-lncRNA interactions on plant datasets based on bipartite network embedding method

The research of miRNA-lncRNA interactions (MLIs) has received great attention recently due to their vital roles in microbiology and profound significance in diseases. Currently, many related studies mainly focus on animals and the link prediction problem on plants is rarely discussed comprehensively. Motivated by this, we achieve link prediction task based on the concept of bipartite graph and verify encouraging performance of our conclusions by conducting experiments on plant datasets. In this work, we firstly extract attribute information and structure information as base features and further process these information for network embedding. Intra-partition and inter-partition proximity modelling are conducted to construct the loss function, which facilitates the training of parameters. Finally, the superiority of our presented approach is shown by carrying out experiments on four plant datasets, which reflects the significance of this work to the research of microbiology and disease.

Role of transcribed ultraconserved regions in gastric cancer and therapeutic perspectives

Gastric cancer (GC) is the fourth leading cause of cancer-related death. The occurrence and development of GC is a complex process involving multiple biological mechanisms. Although traditional regulation modulates molecular functions related to the occurrence and development of GC, the comprehensive mechanisms remain unclear. Ultraconserved region (UCR) refers to a genome sequence that is completely conserved in the homologous regions of the human, rat and mouse genomes, with 100% identity, without any insertions or deletions, and often located in fragile sites and tumour-related genes. The transcribed UCR (T-UCR) is transcribed from the UCR and is a new type of long noncoding RNA. Recent studies have found that the expression level of T-UCRs changes during the occurrence and development of GC, revealing a new mechanism underlying GC. Therefore, this article aims to review the relevant research on T-UCRs in GC, as well as the function of T-UCRs and their regulatory role in the occurrence and development of GC, to provide new strategies for GC diagnosis and treatment.

Growth Inhibition of Retinoblastoma Cell Line by Exosome-Mediated Transfer of miR-142-3p

Introduction

Retinoblastoma (Rb) is the most common ocular paediatric malignancy and is caused by a mutation of the two alleles of the tumor suppressor gene, RB1. The tumor microenvironment (TME) represents a complex system whose function is not yet well defined and where microvesicles, such as exosomes, play a key role in intercellular communication. Micro-RNAs (mRNAs) have emerged as important modifiers of biological mechanisms involved in cancer and been able to regulate tumor progression.

Methods

Co-culture of monocytes with retinoblastoma cell lines, showed a significant growth decrease. Given the interaction between Rb cells and monocytes, we investigated the role of the supernatant in the cross-talk between cell lines, by taking the product of the co-culture and then using it as a culture medium for Rb cells.

Results

miR-142-3p showed to be particularly over-expressed both in the Rb cell line and in the medium used for their culture, comparing to control cell line and the normal supernatant, respectively. Therefore, we provided evidence that miR-142-3p is released by monocytes in the co-culture medium’s exosomes and that it is subsequently up-taken by Rb cells, causing the inhibition of proliferation of Rb cell line by affecting cell cycle progression.

Conclusion

This study highlights the role of exosomic miR-142-3p in the TME of Rb and identifies new molecular targets, which are able to control tumor growth aiming the development of a forward-looking miR-based strategy.

Structural Analysis of microRNAs in Myeloid Cancer Reveals Consensus Motifs

MicroRNAs (miRNAs) are short non-coding RNAs that function in post-transcriptional gene silencing and mRNA regulation. Although the number of nucleotides of miRNAs ranges from 17 to 27, they are mostly made up of 22 nucleotides. The expression of miRNAs changes significantly in cancer, causing protein alterations in cancer cells by preventing some genes from being translated into proteins. In this research, a structural analysis of 587 miRNAs that are differentially expressed in myeloid cancer was carried out. Length distribution studies revealed a mean and median of 22 nucleotides, with an average of 21.69 and a variance of 1.65. We performed nucleotide analysis for each position where Uracil was the most observed nucleotide and Adenine the least observed one with 27.8% and 22.6%, respectively. There was a higher frequency of Adenine at the beginning of the sequences when compared to Uracil, which was more frequent at the end of miRNA sequences. The purine content of each implicated miRNA was also assessed. A novel motif analysis script was written to detect the most frequent 3–7 nucleotide (3–7n) long motifs in the miRNA dataset. We detected CUG (42%) as the most frequent 3n motif, CUGC (15%) as a 4n motif, AGUGC (6%) as a 5n motif, AAGUGC (4%) as a 6n motif, and UUUAGAG (4%) as a 7n motif. Thus, in the second part of our study, we further characterized the motifs by analyzing whether these motifs align at certain consensus sequences in our miRNA dataset, whether certain motifs target the same genes, and whether these motifs are conserved within other species. This thorough structural study of miRNA sequences provides a novel strategy to study the implications of miRNAs in health and disease. A better understanding of miRNA structure is crucial to developing therapeutic settings.

Transcribed Ultraconserved Regions in Cancer

Transcribed ultraconserved regions are putative lncRNA molecules that are transcribed from DNA that is 100% conserved in human, mouse, and rat genomes. This is notable, as lncRNAs are typically poorly conserved. TUCRs remain very understudied in many diseases, including cancer. In this review, we summarize the current literature on TUCRs in cancer with respect to expression deregulation, functional roles, mechanisms of action, and clinical perspectives.

Non-coding RNAs transcribed from ultra-conserved regions (T-UCRs) are differentially expressed in dental follicle tissues of impacted mandibular third molars

INTRODUCTION

Transcribed ultra-conserved regions (T-UCRs) are a new class of long non-coding RNA molecules transcribed from ultra-conserved regions (UCRs) of the human genome. T-UCRs are extremely conserved in the human, rat, and mouse genomes. Deletions of genomic areas containing UCRs resulted in live mice that developed without discernible phenotypes, implying that T-UCRs are involved in developmental processes. In addition, there is increasing evidence that dental follicle tissues exhibit various cellular alterations involving deregulation of protein-coding genes and non-coding RNAs. Accordingly, the main objective of the present study was to determine the clinical significance and distinct expression signatures of non-coding RNA molecules transcribed from ultra-conserved regions in dental follicle samples.

MATERIALS AND METHODS

From March 2021 to December 2022, a total 42 patients who referred to clinic of oral and maxillofacial surgery department with the indications of impacted mandibular third molar extraction from 38^th and 48^th positions were enrolled for the study. For the analysis of T-UCR expression levels, real-time quantitative reverse transcription PCR method was used.

RESULTS

Findings of the present study indicated that T-UCRs are distinctly expressed in dental follicle tissues of impacted mandibular third molars. The expression of uc.38, uc.112, and uc.338 was found to be significantly increased in the dental follicles of impacted mandibular third molars, indicating a clinical significance of these molecules. In addition, no differences in T-UCR expression were found as a function of demographic factors.

CONCLUSIONS

Collectively, transcribed ultra-conserved elements, such as uc.38, uc.112, and uc.338, are considerably deregulated in the dental follicle tissues of impacted mandibular third molars and might be responsible for the molecular changes acquired by dental follicle tissues of impacted mandibular third molars.

Targeting non-coding RNAs to overcome cancer therapy resistance

It is now well known that non-coding RNAs (ncRNAs), rather than protein-coding transcripts, are the preponderant RNA transcripts. NcRNAs, particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are widely appreciated as pervasive regulators of multiple cancer hallmarks such as proliferation, apoptosis, invasion, metastasis, and genomic instability. Despite recent discoveries in cancer therapy, resistance to chemotherapy, radiotherapy, targeted therapy, and immunotherapy continue to be a major setback. Recent studies have shown that ncRNAs also play a major role in resistance to different cancer therapies by rewiring essential signaling pathways. In this review, we present the intricate mechanisms through which dysregulated ncRNAs control resistance to the four major types of cancer therapies. We will focus on the current clinical implications of ncRNAs as biomarkers to predict treatment response (intrinsic resistance) and to detect resistance to therapy after the start of treatment (acquired resistance). Furthermore, we will present the potential of targeting ncRNA to overcome cancer treatment resistance, and we will discuss the challenges of ncRNA-targeted therapy—especially the development of delivery systems.

Zooming in on Long Non-Coding RNAs in Ewing Sarcoma Pathogenesis

Ewing sarcoma (ES) is a rare aggressive cancer of bone and soft tissue that is mainly characterized by a reciprocal chromosomal translocation. As a result, about 90% of cases express the EWS-FLI1 fusion protein that has been shown to function as an aberrant transcription factor driving sarcomagenesis. ES is the second most common malignant bone tumor in children and young adults. Current treatment modalities include dose-intensified chemo- and radiotherapy, as well as surgery. Despite these strategies, patients who present with metastasis or relapse still have dismal prognosis, warranting a better understanding of treatment resistant-disease biology in order to generate better prognostic and therapeutic tools. Since the genomes of ES tumors are relatively quiet and stable, exploring the contributions of epigenetic mechanisms in the initiation and progression of the disease becomes inevitable. The search for novel biomarkers and potential therapeutic targets of cancer metastasis and chemotherapeutic drug resistance is increasingly focusing on long non-coding RNAs (lncRNAs). Recent advances in genome analysis by high throughput sequencing have immensely expanded and advanced our knowledge of lncRNAs. They are non-protein coding RNA species with multiple biological functions that have been shown to be dysregulated in many diseases and are emerging as crucial players in cancer development. Understanding the various roles of lncRNAs in tumorigenesis and metastasis would determine eclectic avenues to establish therapeutic and diagnostic targets. In ES, some lncRNAs have been implicated in cell proliferation, migration and invasion, features that make them suitable as relevant biomarkers and therapeutic targets. In this review, we comprehensively discuss known lncRNAs implicated in ES that could serve as potential biomarkers and therapeutic targets of the disease. Though some current reviews have discussed non-coding RNAs in ES, to our knowledge, this is the first review focusing exclusively on ES-associated lncRNAs.

MicroRNAs/LncRNAs Modulate MDSCs in Tumor Microenvironment

Myeloid-derived suppressor cells (MDSCs) are a heterogeneous group of immature cells derived from bone marrow that play critical immunosuppressive functions in the tumor microenvironment (TME), promoting cancer progression. According to base length, Non-coding RNAs (ncRNAs) are mainly divided into: microRNAs (miRNAs), lncRNAs, snRNAs and CircRNAs. Both miRNA and lncRNA are transcribed by RNA polymerase II, and they play an important role in gene expression under both physiological and pathological conditions. The increasing data have shown that MiRNAs/LncRNAs regulate MDSCs within TME, becoming one of potential breakthrough points at the investigation and treatment of cancer. Therefore, we summarize how miRNAs/lncRNAs mediate the differentiation, expansion and immunosuppressive function of tumor MDSCs in TME. We will then focus on the regulatory mechanisms of exosomal MicroRNAs/LncRNAs on tumor MDSCs. Finally, we will discuss how the interaction of miRNAs/lncRNAs modulates tumor MDSCs.

Analysis of the circRNA and T-UCR populations identifies convergent pathways in mouse and human models of Rett syndrome

Noncoding RNAs play regulatory roles in physiopathology, but their involvement in neurodevelopmental diseases is poorly understood. Rett syndrome is a severe, progressive neurodevelopmental disorder linked to loss-of-function mutations of the MeCP2 gene for which no cure is yet available. Analysis of the noncoding RNA profile corresponding to the brain-abundant circular RNA (circRNA) and transcribed-ultraconserved region (T-UCR) populations in a mouse model of the disease reveals widespread dysregulation and enrichment in glutamatergic excitatory signaling and microtubule cytoskeleton pathways of the corresponding host genes. Proteomic analysis of hippocampal samples from affected individuals confirms abnormal levels of several cytoskeleton-related proteins together with key alterations in neurotransmission. Importantly, the glutamate receptor GRIA3 gene displays altered biogenesis in affected individuals and in vitro human cells and is influenced by expression of two ultraconserved RNAs. We also describe post-transcriptional regulation of SIRT2 by circRNAs, which modulates acetylation and total protein levels of GluR-1. As a consequence, both regulatory mechanisms converge on the biogenesis of AMPA receptors, with an effect on neuronal differentiation. In both cases, the noncoding RNAs antagonize MeCP2-directed regulation. Our findings indicate that noncoding transcripts may contribute to key alterations in Rett syndrome and are not only useful tools for revealing dysregulated processes but also molecules of biomarker value.

Perfect and imperfect views of ultraconserved sequences

Across the human genome, there are nearly 500 'ultraconserved' elements: regions of at least 200 contiguous nucleotides that are perfectly conserved in both the mouse and rat genomes. Remarkably, the majority of these sequences are non-coding, and many can function as enhancers that activate tissue-specific gene expression during embryonic development. From their first description more than 15 years ago, their extreme conservation has both fascinated and perplexed researchers in genomics and evolutionary biology. The intrigue around ultraconserved elements only grew with the observation that they are dispensable for viability. Here, we review recent progress towards understanding the general importance and the specific functions of ultraconserved sequences in mammalian development and human disease and discuss possible explanations for their extreme conservation.

LDA-LNSUBRW: lncRNA-Disease Association Prediction Based on Linear Neighborhood Similarity and Unbalanced bi-Random Walk

Increasing number of experiments show that lncRNAs are involved in many biological processes, and their mutations and disorders are associated with many diseases. However, verifying the relationships between lncRNAs and diseases is time consuming and laborio. Searching for effective computational methods will contribute to our understanding of the underlying mechanisms of disease and identifying biomarkers of diseases. Therefore, we proposed a method called lncRNA-disease association prediction based on linear neighborhood similarity and unbalanced bi-random walk (LDA-LNSUBRW). Given that the known lncRNA-disease associations are rare, a pretreatment step should be performed to obtain the interaction possibility of unknown cases, so as to help us predict the potential associations. In the framework of leave-one-out cross-validation (LOOCV)and fivefold cross-validation (5-fold CV), LDA-LNSUBRW achieved effective performance with AUC of 0.8874 and 0.8632 ± 0.0051, respectively. The experimental results in this paper show that the proposed method is superior to five other state-of-the-art methods. In addition, case studies of three diseases (lung cancer, breast cancer, and osteosarcoma)were carried out to illustrate that LDA-LNSUBRW could predict the relevant lncRNAs.

MicroRNAs and 'Sponging' Competitive Endogenous RNAs Dysregulated in Colorectal Cancer: Potential as Noninvasive Biomarkers and Therapeutic Targets

The gastrointestinal (GI) tract in mammals is comprised of dozens of cell types with varied functions, structures, and histological locations that respond in a myriad of ways to epigenetic and genetic factors, environmental cues, diet, and microbiota. The homeostatic functioning of these cells contained within this complex organ system has been shown to be highly regulated by the effect of microRNAs (miRNA). Multiple efforts have uncovered that these miRNAs are often tightly influential in either the suppression or overexpression of inflammatory, apoptotic, and differentiation-related genes and proteins in a variety of cell types in colorectal cancer (CRC). The early detection of CRC and other GI cancers can be difficult, attributable to the invasive nature of prophylactic colonoscopies. Additionally, the levels of miRNAs associated with CRC in biofluids can be contradictory and, therefore, must be considered in the context of other inhibiting competitive endogenous RNAs (ceRNA) such as lncRNAs and circRNAs. There is now a high demand for disease treatments and noninvasive screenings such as testing for bloodborne or fecal miRNAs and their inhibitors/targets. The breadth of this review encompasses current literature on well-established CRC-related miRNAs and the possibilities for their use as biomarkers in the diagnoses of this potentially fatal GI cancer.

The dark matter of the human genome and its role in human cancers

The transcribed ultra-conserved regions (T-UCRs) are a novel family of non-coding RNAs which are absolutely conserved (100%) across orthologous regions of the human, mouse, and rat genomes. T-UCRs represent a small portion of the human genome that is likely to be functional but does not code for proteins and is referred to as the "dark matter" of the human genome. Although T-UCRs are ubiquitously expressed, tissue- and disease-specific expression of T-UCRs have also been observed. Accumulating evidence suggests that T-UCRs are differentially expressed and involved in the malignant transformation of human tumors through various genetic and epigenetic regulatory mechanisms. Therefore, T-UCRs are novel candidate predisposing biomarkers for cancer development. T-UCRs have shown to drive malignant transformation of human cancers through regulating non-coding RNAs and/or protein coding genes. However, the functions and fate of most T-UCRs remain mysterious. Here, we review and highlight the current knowledge on these ultra-conserved elements in the formation and progression of human cancers.

Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma

Glioblastoma (GBM), originating in the brain, is a universally aggressive malignant tumor with a particularly poor prognosis. Therefore, insight into the critical role of underlying genetic mechanisms is essential to developing new therapeutic approaches. This study aims to identify potential markers with clinical and prognostic significance in GBM. To this end, increasing numbers of differentially expressed RNA have been identified used to construct competitive endogenous RNA networks for prognostic analysis via comparison and analysis of RNA expression levels of tumor and normal tissues in glioblastoma. This analysis demonstrated that the RNA expression patterns of normal and tumor samples were significantly different. Thus, the resulting differentially expressed RNAs were used to construct competitive endogenous RNA (competing endogenous RNA, ceRNA) networks. The functional enrichment indicated mRNAs in the network are critically involved in a variety of biological functions. Additionally, the prognostic analysis suggested 27 lncRNAs, including LOXL1-AS1, AL356414.1, etc., were significantly associated with patient survival. Given the prognostic significance of these 27 lncRNAs in GBM, we sought to classify the samples. Importantly, Kaplan-Meier analysis revealed that survival times varied significantly among the different categories. Overall, these results identify that the candidate lncRNAs are potential prognostic markers of GBM and its corresponding mRNAs may be a potential target for therapy.

Transcribed Ultraconserved Regions Are Associated with Clinicopathological Features in Breast Cancer

Ultraconserved regions (UCRs) are 481 genome segments, with length longer than 200 bp, that are 100% conserved among humans, mice, and rats. The majority of UCRs are transcriptionally active (T-UCRs) as many of them produce non-coding RNAs. In a previous study, we evaluated the expression level of T-UCRs in breast cancer (BC) patients and found that 63% of transcripts correlated with some clinical and/or molecular parameter of BC. In this study, we delved into the expression levels of 12 T-UCRs and correlated them with clinicopathological parameters, immunohistochemical markers, and overall survival in two breast cancer cohorts: TCGA and Brazilian patients. We found that uc.268 is more expressed in TCGA patients under 40 years of age, associated with progesterone receptor (PR) and estrogen receptor (ER), and its high expression is found in luminal A. Lower uc.84 and uc.376 were respectively observed in metastatic and stage IV tumors associated with good prognostic in luminal B. Moreover, uc.84 was only related to the HER2+, while uc.376 was related to ER+ and PR+, and HER2+. A panel composed of uc.147, uc.271, and uc.427 distinguished luminal A from triple negative patients with an AUC of 0.9531 (sensitivity 92.19% and specificity 86.76%). These results highlight the potential role of T-UCRs in BC and provide insights into the potential application of T-UCRs as biomarkers.

LncRNA MAGI2-As3 Suppresses the Proliferation and Invasion of Cervical Cancer by Sponging MiR-15b

BACKGROUND

Cervical cancer is the leading cause of cancer deaths among women, and more than 85% of cervical cancer deaths occur in low and middle-income countries. The purpose of this study is to investigate the functions of MAGI2-AS3 and miR-15b in cervical cancer.

MATERIALS AND METHODS

The mRNA levels of MAGI2-AS3, miR-15b, and CCNE1 were evaluated using RT-qPCR assay. Dual-luciferase reporter gene assay was used to confirm whether miR-15b binds to CCNE1.

RESULTS

LncRNA MAGI2-AS3 was downregulated, while miR-15b was upregulated in cervical cancer. Cervical cancer patients with low expression of MAGI2-AS3 have a poor prognosis. Upregulation of MAGI2-AS3 inhibited proliferative and invasive abilities of HeLa cells via regulating the expression of miRNA-15b. MiR-15b inhibitor suppressed cell proliferation and invasion. CCNE1 was a direct target gene of miR-15b, which binds to the 3'-UTR of its mRNA. MiR-15b partially reversed the inhibitory effect of overexpression of MAGI2-AS3 on the proliferation and invasion of HeLa cells. MAGI2-AS3 mediated the expression of CCNE1 in HeLa cells.

CONCLUSION

LncRNA MAGI2-AS3 inhibits the proliferation and invasion of cervical cancer cells via the miRNA-15/CCNE1 axis. Our results illustrates that MAGI2-AS3 can be used as a useful clinical predictor for early diagnosis and prognosis assessment of cervical cancer.

Long Noncoding RNA LINC00941 Promotes Cell Proliferation and Invasion by Interacting with hnRNPK in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is a prevalent carcinoma of the head, neck and mouth. Recently studies involving the role of long noncoding RNAs (lncRNAs) that play key regulatory roles in altering gene expression has been reported in the context of promoting tumorigenesis. However, the functions of lncRNAs in the context of oral squamous cell carcinoma have not been extensively described. In this study, we report a never identified before lncRNA, LINC00941, which was highly expressed in OSCC tissues and cells. Expression of LINC00941 promoted cell proliferation, migration, invasion, and metastasis of OSCC cells In Vitro by inducing epithelial-mesenchymal transition (EMT) and activating the Wnt/β-catenin signaling cascade. In silico analyses revealed heterogeneous nuclear ribonucleoprotein K (hnRNPK) to be a strong positive regulator of LINC00941 activity. Experimental verification of this association revealed a direct interaction of LINC00941 and hnRNPK to induce cell growth and invasion by activating EMT in OSCC cells. Therefore, our study reports that LINC00941 promotes progression of OSCC by its interaction with hnRNPK, and it may present a promising strategy for diagnosis and treatment of OSCC.

Overexpression of ultraconserved region 83- induces lung cancer tumorigenesis

The expression of non-coding RNAs (ncRNAs) is dysregulated in human cancers. The transcribed ultraconserved regions (T-UCRs) express long ncRNAs involved in human carcinogenesis. T-UCRs are non-coding genomic sequence that are 100% conserved across humans, rats and mice. Conservation of genomic sequences across species intrinsically implies an essential functional role and so we considered the expression of T-UCRs in lung cancer. Using a custom microarray we analyzed the global expression of T-UCRs. Among these T-UCRs, the greatest variation was observed for antisense ultraconserved element 83 (uc.83-), which was upregulated in human lung cancer tissues compared with adjacent non cancerous tissues. Even though uc.83- is located within the long intergenic non-protein coding RNA 1876 (LINC01876) gene, we found that the transcribed uc.83- is expressed independently of LINC01876 and was cloned as a 1143-bp RNA gene. In this study, functional analysis confirmed important effects of uc.83- on genes involved in cell growth of human cells. siRNA against uc.83- decreased the growth of lung cancer cells while the upregulation through a vector overexpressing the uc.83- RNA increased cell proliferation. We also show the oncogenic function of uc.83- is mediated by the phosphorylation of AKT and ERK 1/2, two important biomarkers of lung cancer cell proliferation. Based on our findings, inhibition against uc.83- could be a future therapeutic treatment for NSCLC to achieve simultaneous blockade of pathways involved in lung carcinogenesis.

MicroRNAs Regulate Cell Cycle and Cell Death Pathways in Glioblastoma

Glioblastoma (GBM), a grade IV brain tumor, is known for its heterogenicity and its resistance to the current treatment regimen. Over the last few decades, a significant amount of new molecular and genetic findings has been reported regarding factors contributing to GBM’s development into a lethal phenotype and its overall poor prognosis. MicroRNA (miRNAs) are small non-coding sequences of RNA that regulate and influence the expression of multiple genes. Many research findings have highlighted the importance of miRNAs in facilitating and controlling normal biological functions, including cell differentiation, proliferation, and apoptosis. Furthermore, miRNAs’ ability to initiate and promote cancer development, directly or indirectly, has been shown in many types of cancer. There is a clear association between alteration in miRNAs expression in GBM’s ability to escape apoptosis, proliferation, and resistance to treatment. Further, miRNAs regulate the already altered pathways in GBM, including P53, RB, and PI3K-AKT pathways. Furthermore, miRNAs also contribute to autophagy at multiple stages. In this review, we summarize the functions of miRNAs in GBM pathways linked to dysregulation of cell cycle control, apoptosis and resistance to treatment, and the possible use of miRNAs in clinical settings as treatment and prediction biomarkers.

UC.183, UC.110, and UC.84 Ultra-Conserved RNAs Are Mutually Exclusive with miR-221 and Are Engaged in the Cell Cycle Circuitry in Breast Cancer Cell Lines

In the human genome, there are about 600 ultra-conserved regions (UCRs), long DNA sequences extremely conserved in vertebrates. We performed a large-scale study to quantify transcribed UCR (T-UCR) and miRNA levels in over 6000 cancer and normal tissue samples to find possible correlation between these kinds of regulatory molecules. Our analysis evidenced several non-coding RNAs showing negative co-regulation with miRNAs; among them, we focused on miR-221 to investigate any relationship with its pivotal role in the cell cycle. We have chosen breast cancer as model, using two cell lines with different phenotypes to carry out in vitro treatments with siRNAs against T-UCRs. Our results demonstrate that the expression of uc.183, uc.110, and uc.84 T-UCRs is mutually exclusive with miR-221 and is engaged in the regulation of CDKN1B expression. In addition, tests with a set of anticancer drugs, including BYL719, AZD5363, AZD8055, AZD7762, and XL765, revealed the modulation of specific T-UCRs without alteration of miR-221 levels.

The transcribed ultraconserved element uc.51 promotes the proliferation and metastasis of breast cancer by stabilizing NONO

Long noncoding RNAs have recently emerged as significant contributors to cancers, including breast cancer (BC). One class of long noncoding RNAs called transcribed ultraconserved regions (T-UCRs) is highly conserved in many species and closely related to diverse physiological and pathological processes. However, the function of T-UCRs in BC remains largely unclear. In this study, we identified uc.51, a T-UCR that is overexpressed in both BC tissues and cell lines and is correlated with larger tumor size. Loss- and gain-of-function assays were performed in vitro and demonstrated that uc.51 promotes the proliferation, migration, and invasion of BC cells. Mechanistically, non-POU domain-containing octamer-binding protein (NONO) was found to physically interact with uc.51 by RNA pulldown followed by mass spectrometry. This interaction was further verified by RNA immunoprecipitation. Moreover, uc.51 positively regulated the expression of NONO, maintained its stability through the ubiquitin-proteasome system, and activated the phosphorylation of CREB. Rescue experiments demonstrated that NONO overexpression compensated for the attenuated influence on BC progression resulting from downregulation of uc.51, indicating that NONO functions downstream of uc.51. In vivo functional experiments also revealed a positive correlation between uc.51 expression and tumor size. Ki-67 and NONO levels in the lv-uc.51-shRNA group were decreased compared with those in the lv-con-shRNA group, according to the immunohistochemical staining results, and a decreased incidence of distant metastasis was observed in the lv-uc.51-shRNA group in the xenograft model. Collectively, our results reveal a substantial role for the uc.51-NONO axis in BC progression and indicate that the uc.51-NONO axis has potential to be a therapeutic target for BC.