Roles of Noncoding RNAs in Islet Biology.

The discovery that most mammalian genome sequences are transcribed to ribonucleic acids (RNA) has revolutionized our understanding of the mechanisms governing key cellular processes and of the causes of human diseases, including diabetes mellitus. Pancreatic islet cells were found to contain thousands of noncoding RNAs (ncRNAs), including micro-RNAs (miRNAs), PIWI-associated RNAs, small nucleolar RNAs, tRNA-derived fragments, long non-coding RNAs, and circular RNAs. While the involvement of miRNAs in islet function and in the etiology of diabetes is now well documented, there is emerging evidence indicating that other classes of ncRNAs are also participating in different aspects of islet physiology. The aim of this article will be to provide a comprehensive and updated view of the studies carried out in human samples and rodent models over the past 15 years on the role of ncRNAs in the control of α- and β-cell development and function and to highlight the recent discoveries in the field. We not only describe the role of ncRNAs in the control of insulin and glucagon secretion but also address the contribution of these regulatory molecules in the proliferation and survival of islet cells under physiological and pathological conditions. It is now well established that most cells release part of their ncRNAs inside small extracellular vesicles, allowing the delivery of genetic material to neighboring or distantly located target cells. The role of these secreted RNAs in cell-to-cell communication between β-cells and other metabolic tissues as well as their potential use as diabetes biomarkers will be discussed. © 2020 American Physiological Society. Compr Physiol 10:893-932, 2020

Small RNAs derived from tRNA fragmentation regulate the functional maturation of neonatal β cells.

tRNA-derived fragments (tRFs) are an emerging class of small non-coding RNAs with distinct cellular functions. Here, we studied the contribution of tRFs to the regulation of postnatal β cell maturation, a critical process that may lead to diabetes susceptibility in adulthood. We identified three tRFs abundant in neonatal rat islets originating from 5' halves (tiRNA-5s) of histidine and glutamate tRNAs. Their inhibition in these islets reduced β cell proliferation and insulin secretion. Mitochondrial respiration was also perturbed, fitting with the mitochondrial enrichment of nuclear-encoded tiRNA-5 <sup>HisGTG</sup> and tiRNA-5 <sup>GluCTC</sup> . Notably, tiRNA-5 inhibition reduced Mpc1, a mitochondrial pyruvate carrier whose knock down largely phenocopied tiRNA-5 inhibition. tiRNA-5 <sup>HisGTG</sup> interactome revealed binding to Musashi-1, which was essential for the mitochondrial enrichment of tiRNA-5 <sup>HisGTG</sup> . Finally, tiRNA-5s were dysregulated in the islets of diabetic and diabetes-prone animals. Altogether, tiRNA-5s represent a class of regulators of β cell maturation, and their deregulation in neonatal islets may lead to diabetes susceptibility in adulthood

A circular RNA generated from an intron of the insulin gene controls insulin secretion.

Fine-tuning of insulin release from pancreatic β-cells is essential to maintain blood glucose homeostasis. Here, we report that insulin secretion is regulated by a circular RNA containing the lariat sequence of the second intron of the insulin gene. Silencing of this intronic circular RNA in pancreatic islets leads to a decrease in the expression of key components of the secretory machinery of β-cells, resulting in impaired glucose- or KCl-induced insulin release and calcium signaling. The effect of the circular RNA is exerted at the transcriptional level and involves an interaction with the RNA-binding protein TAR DNA-binding protein 43 kDa (TDP-43). The level of this circularized intron is reduced in the islets of rodent diabetes models and of type 2 diabetic patients, possibly explaining their impaired secretory capacity. The study of this and other circular RNAs helps understanding β-cell dysfunction under diabetes conditions, and the etiology of this common metabolic disorder

Emerging Classes of Small Non-Coding RNAs With Potential Implications in Diabetes and Associated Metabolic Disorders.

Most of the sequences in the human genome do not code for proteins but generate thousands of non-coding RNAs (ncRNAs) with regulatory functions. High-throughput sequencing technologies and bioinformatic tools significantly expanded our knowledge about ncRNAs, highlighting their key role in gene regulatory networks, through their capacity to interact with coding and non-coding RNAs, DNAs and proteins. NcRNAs comprise diverse RNA species, including amongst others PIWI-interacting RNAs (piRNAs), involved in transposon silencing, and small nucleolar RNAs (snoRNAs), which participate in the modification of other RNAs such as ribosomal RNAs and transfer RNAs. Recently, a novel class of small ncRNAs generated from the cleavage of tRNAs or pre-tRNAs, called tRNA-derived small RNAs (tRFs) has been identified. tRFs have been suggested to regulate protein translation, RNA silencing and cell survival. While for other ncRNAs an implication in several pathologies is now well established, the potential involvement of piRNAs, snoRNAs and tRFs in human diseases, including diabetes, is only beginning to emerge. In this review, we summarize fundamental aspects of piRNAs, snoRNAs and tRFs biology. We discuss their biogenesis while emphasizing on novel sequencing technologies that allow ncRNA discovery and annotation. Moreover, we give an overview of genomic approaches to decrypt their mechanisms of action and to study their functional relevance. The review will provide a comprehensive landscape of the regulatory roles of these three types of ncRNAs in metabolic disorders by reporting their differential expression in endocrine pancreatic tissue as well as their contribution to diabetes incidence and diabetes-underlying conditions such as inflammation. Based on these discoveries we discuss the potential use of piRNAs, snoRNAs and tRFs as promising therapeutic targets in metabolic disorders

A novel computer based expert decision making model for prostate cancer disease management

PubMedID: 16280831Purpose: We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Materials and Methods: Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Results: Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of sub-objectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. Conclusions: This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias. Copyright © 2005 by American Urological Association

Evaluation of the effects of androgen receptor gene trinucleotide repeats and prostate-specific antigen gene polymorphisms on prostate cancer

The number of trinucleotide repeats [CAG (coding for polyglutamine), GGC (coding for polyglycine)] in the first exon of the androgen receptor (AR) gene and prostate-specific antigen (PSA) gene androgen response element I A/G polymorphism are both related to prostate cancer prognosis. We investigated whether these genomic changes occur in the AR and PSA genes, which are usually found in individuals with prostate cancer, of Turkish patients and to find out their distribution in the population. We used PCR and PCR-RFLP assays for AR and PSA genes, respectively, to detect molecular changes in 44 prostate cancer patients. Our findings indicate that individuals with prostate cancer tend to have around 18 CAG trinucleotide repeats. We observed significant differences between 22 controls, 33 benign prostate hyperplasia (BPH) patients and 44 adenocarcinoma patients for long CAG repeats. However, we did not find any significant differences in GGC repeats between controls, BPH and adenocarcinoma patients (P = 0.408). We also did not observe significant differences in the PSA A/G polymorphism frequency between controls, BPH and adenocarcinoma patients (P = 0.483). In conclusion, CAG and GGC repeats in the AR and PSA gene polymorphisms may be associated with prostate cancer risk and BPH in the Turkish population. © FUNPEC-RP