Post-transcriptional knowledge in pathway analysis increases the accuracy of phenotypes classification

Motivation: Prediction of phenotypes from high-dimensional data is a crucial task in precision biology and medicine. Many technologies employ genomic biomarkers to characterize phenotypes. However, such elements are not sufficient to explain the underlying biology. To improve this, pathway analysis techniques have been proposed. Nevertheless, such methods have shown lack of accuracy in phenotypes classification. Results: Here we propose a novel methodology called MITHrIL (Mirna enrIched paTHway Impact anaLysis) for the analysis of signaling pathways, which has built on top of the work of Tarca et al., 2009. MITHrIL extends pathways by adding missing regulatory elements, such as microRNAs, and their interactions with genes. The method takes as input the expression values of genes and/or microRNAs and returns a list of pathways sorted according to their deregulation degree, together with the corresponding statistical significance (p-values). Our analysis shows that MITHrIL outperforms its competitors even in the worst case. In addition, our method is able to correctly classify sets of tumor samples drawn from TCGA. Availability: MITHrIL is freely available at the following URL: http://alpha.dmi.unict.it/mithril

A-to-I RNA Editing: Current Knowledge Sources and Computational Approaches with Special Emphasis on Non-Coding RNA Molecules

RNA editing is a dynamic mechanism for gene regulation attained through the alteration of the sequence of primary RNA transcripts. A-to-I (Adenosine-to-Inosine) RNA editing, which is catalyzed by members of the Adenosine Deaminase Acting on RNA (ADAR) family of enzymes, is the most common post-transcriptional modification in humans. The ADARs bind double-stranded regions and deaminate adenosine (A) into inosine (I), which in turn is interpreted by the translation and splicing machineries as guanosine (G). In recent years, this modification has been discovered to occur not only in coding RNAs but also in non-coding RNAs (ncRNA), such as microRNAs (miRNAs), small interfering RNAs (siRNAs), transfer RNAs (tRNAs), and long non-coding RNAs (lncRNAs). This may have several consequences, such as the creation or disruption of microRNA/mRNA binding sites, and thus affect the biogenesis, stability, and target recognition properties of ncRNAs. The malfunction of the editing machinery is not surprisingly associated with various human diseases, such as neurodegenerative, cardiovascular and carcinogenic diseases.Despite the enormous efforts made so far, the real biological function of this phenomenon, as well as the features of the ADAR substrate, in particular in non-coding RNAs, has still not been fully understood. In this work we focus on the current knowledge of RNA editing on ncRNA molecules and provide a few examples of computational approaches to elucidate its biological function

RNA Methylation in ncRNA: Classes, Detection, and Molecular Associations

Nearly all classes of coding and non-coding RNA undergo post-transcriptional modification, as more than 150 distinct modification types have been reported. Since RNA modifications were first described over 50 years ago, our understanding of their functional relevance in cellular control mechanisms and phenotypes has truly progressed only in the last 15 years due to advancements in detection and experimental techniques. Specifically, the phenomenon of RNA methylation in the context of ncRNA has emerged as a novel process in the arena of epitranscriptomics. Methylated ncRNA molecules may indeed contribute to a potentially vast functional panorama, from regulation of post-transcriptional gene expression to adaptive cellular responses. Recent discoveries have uncovered novel dynamic mechanisms and new layers of complexity, paving the way to a greater understanding of the role of such phenomena within the broader molecular cellular context of human disease

MicroRNA profiling of paediatric AML with FLT-ITD or MLL-rearrangements: Expression signatures and in vitro modulation of miR-221-3p and miR-222-3p with BRD4/HATs inhibitors.

Novel therapeutic strategies are needed for paediatric patients affected by Acute Myeloid Leukaemia (AML), particularly for those at high-risk for relapse. MicroRNAs (miRs) have been extensively studied as biomarkers in cancer and haematological disorders, and their expression has been correlated to the presence of recurrent molecular abnormalities, expression of oncogenes, as well as to prognosis/clinical outcome. In the present study, expression signatures of different miRs related both to presence of myeloid/lymphoid or mixed-lineage leukaemia 1 and Fms like tyrosine kinase 3 internal tandem duplications rearrangements and to the clinical outcome of paediatric patients with AML were identified. Notably, miR-221-3p and miR-222-3p resulted as a possible relapse-risk related miR. Thus, miR-221-3p and miR-222-3p expression modulation was investigated by using a Bromodomain‑containing protein 4 (BRD4) inhibitor (JQ1) and a natural compound that acts as histone acetyl transferase inhibitor (curcumin), alone or in association, in order to decrease acetylation of histone tails and potentiate the effect of BRD4 inhibition. JQ1 modulates miR-221-3p and miR-222-3p expression in AML with a synergic effect when associated with curcumin. Moreover, changes were observed in the expression of CDKN1B, a known target of miR-221-3p and miR-222-3p, increase in apoptosis and downregulation of miR-221-3p and miR-222-3p expression in CD34+ AML primary cells. Altogether, these findings suggested that several miRs expression signatures at diagnosis may be used for risk stratification and as relapse prediction biomarkers in paediatric AML outlining that epigenetic drugs, could represent a novel therapeutic strategy for high-risk paediatric patients with AML. For these epigenetic drugs, additional research for enhancing activity, bioavailability and safety is needed

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements