Dataset Information

New Cross-Talk Layer between Ultraconserved Non-Coding RNAs, MicroRNAs and Polycomb Protein YY1 in Bladder Cancer.

ABSTRACT: MicroRNAs (miRNAs) are highly conserved elements in mammals, and exert key regulatory functions. Growing evidence shows that miRNAs can interact with another class of non-coding RNAs, so-called transcribed ultraconserved regions (T-UCRs), which take part in transcriptional, post-transcriptional and epigenetic regulation processes. We report here the interaction of miRNAs and T-UCRs as a network modulating the availability of these non-coding RNAs in bladder cancer cells. In our cell system, antagomiR-596 increased the expression of T-UCR 201+. Moreover, T-UCR 8+ silencing increased miR-596 expression, which in turn reduced total T-UCR 283+, showing that the perturbation of one element in this network changes the expression of other interactors. In addition, we identify the polycomb protein Yin Yang 1 (YY1) as mediator of binding between miR-596 and T-UCR 8+. These new findings describe for the first time a network between T-UCRs, miRNAs and YY1 protein, highlighting the existence of an additional layer of gene expression regulation.

SUBMITTER: Terreri S

PROVIDER: S-EPMC5192503 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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New Cross-Talk Layer between Ultraconserved Non-Coding RNAs, MicroRNAs and Polycomb Protein YY1 in Bladder Cancer.

Terreri Sara S Durso Montano M Colonna Vincenza V Romanelli Alessandra A Terracciano Daniela D Ferro Matteo M Perdonà Sisto S Castaldo Luigi L Febbraio Ferdinando F de Nigris Filomena F Cimmino Amelia A

Genes 20161214 12

MicroRNAs (miRNAs) are highly conserved elements in mammals, and exert key regulatory functions. Growing evidence shows that miRNAs can interact with another class of non-coding RNAs, so-called transcribed ultraconserved regions (T-UCRs), which take part in transcriptional, post-transcriptional and epigenetic regulation processes. We report here the interaction of miRNAs and T-UCRs as a network modulating the availability of these non-coding RNAs in bladder cancer cells. In our cell system, anta ...[more]

PMID: 27983635

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Project description:BackgroundRecent 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.ResultsThe 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.ConclusionsHere 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.

Project description:Ultraconserved regions (UCRs) have been shown to originate non-coding RNA transcripts (T-UCRs) that have different expression profiles and play functional roles in the pathophysiology of multiple cancers. The relevance of these functions to the pathogenesis of bladder cancer (BlCa) is speculative. To elucidate this relevance, we first used genome-wide profiling to evaluate the expression of T-UCRs in BlCa tissues. Analysis of two datasets comprising normal bladder tissues and BlCa specimens with a custom T-UCR microarray identified ultraconserved RNA (uc.) 8+ as the most upregulated T-UCR in BlCa tissues, although its expression was lower than in pericancerous bladder tissues. These results were confirmed on BlCa tissues by real-time PCR and by in situ hybridization. Although uc.8+ is located within intron 1 of CASZ1, a zinc-finger transcription factor, the transcribed non-coding RNA encoding uc.8+ is expressed independently of CASZ1. In vitro experiments evaluating the effects of uc.8+ silencing, showed significantly decreased capacities for cancer cell invasion, migration, and proliferation. From this, we proposed and validated a model of interaction in which uc.8+ shuttles from the nucleus to the cytoplasm of BlCa cells, interacts with microRNA (miR)-596, and cooperates in the promotion and development of BlCa. Using computational analysis, we investigated the miR-binding domain accessibility, as determined by base-pairing interactions within the uc.8+ predicted secondary structure, RNA binding affinity, and RNA species abundance in bladder tissues and showed that uc.8+ is a natural decoy for miR-596. Thus uc.8+ upregulation results in increased expression of MMP9, increasing the invasive potential of BlCa cells. These interactions between evolutionarily conserved regions of DNA suggest that natural selection has preserved this potentially regulatory layer that uses RNA to modulate miR levels, opening up the possibility for development of useful markers for early diagnosis and prognosis as well as for development of new RNA-based cancer therapies.

Dataset Information

New Cross-Talk Layer between Ultraconserved Non-Coding RNAs, MicroRNAs and Polycomb Protein YY1 in Bladder Cancer.

Publications

New Cross-Talk Layer between Ultraconserved Non-Coding RNAs, MicroRNAs and Polycomb Protein YY1 in Bladder Cancer.

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