PHENSIM: Phenotype Simulator.

Despite the unprecedented growth in our understanding of cell biology, it still remains challenging to connect it to experimental data obtained with cells and tissues' physiopathological status under precise circumstances. This knowledge gap often results in difficulties in designing validation experiments, which are usually labor-intensive, expensive to perform, and hard to interpret. Here we propose PHENSIM, a computational tool using a systems biology approach to simulate how cell phenotypes are affected by the activation/inhibition of one or multiple biomolecules, and it does so by exploiting signaling pathways. Our tool's applications include predicting the outcome of drug administration, knockdown experiments, gene transduction, and exposure to exosomal cargo. Importantly, PHENSIM enables the user to make inferences on well-defined cell lines and includes pathway maps from three different model organisms. To assess our approach's reliability, we built a benchmark from transcriptomics data gathered from NCBI GEO and performed four case studies on known biological experiments. Our results show high prediction accuracy, thus highlighting the capabilities of this methodology. PHENSIM standalone Java application is available at https://github.com/alaimos/phensim, along with all data and source codes for benchmarking. A web-based user interface is accessible at https://phensim.tech/.

Pan-Cancer Analysis of Canonical and Modified miRNAs Enhances the Resolution of the Functional miRNAome in Cancer.

Epitranscriptomic studies of miRNAs have added a new layer of complexity to the cancer field. Although there is fast-growing interest in adenosine-to-inosine (A-to-I) miRNA editing and alternative cleavage that shifts miRNA isoforms, simultaneous evaluation of both modifications in cancer is still missing. Here, we concurrently profiled multiple miRNA modification types, including A-to-I miRNA editing and shifted miRNA isoforms, in >13,000 adult and pediatric tumor samples across 38 distinct cancer cohorts from The Cancer Genome Atlas and The Therapeutically Applicable Research to Generate Effective Treatments data sets. The differences between canonical miRNAs and the wider miRNAome in terms of expression, clustering, dysregulation, and prognostic standpoint were investigated. The combination of canonical miRNAs and modified miRNAs boosted the quality of clustering results, outlining unique clinicopathologic features among cohorts. Certain modified miRNAs showed opposite expression from their canonical counterparts in cancer, potentially impacting their targets and function. Finally, a shifted and edited miRNA isoform was experimentally validated to directly bind and suppress a unique target. These findings outline the importance of going beyond the well-established paradigm of one mature miRNA per miRNA arm to elucidate novel mechanisms related to cancer progression. SIGNIFICANCE: Modified miRNAs may act as cancer biomarkers and function as allies or antagonists of their canonical counterparts in gene regulation, suggesting the concurrent consideration of canonical and modified miRNAs can boost patient stratification.

Detecting and Characterizing A-To-I microRNA Editing in Cancer.

Adenosine to inosine (A-to-I) editing consists of an RNA modification where single adenosines along the RNA sequence are converted into inosines. Such a biochemical transformation is catalyzed by enzymes belonging to the family of adenosine deaminases acting on RNA (ADARs) and occurs either co- or post-transcriptionally. The employment of powerful, high-throughput detection methods has recently revealed that A-to-I editing widely occurs in non-coding RNAs, including microRNAs (miRNAs). MiRNAs are a class of small regulatory non-coding RNAs (ncRNAs) acting as translation inhibitors, known to exert relevant roles in controlling cell cycle, proliferation, and cancer development. Indeed, a growing number of recent researches have evidenced the importance of miRNA editing in cancer biology by exploiting various detection and validation methods. Herein, we briefly overview early and currently available A-to-I miRNA editing detection and validation methods and discuss the significance of A-to-I miRNA editing in human cancer.

MiREDiBase, a manually curated database of validated and putative editing events in microRNAs.

MicroRNAs (miRNAs) are regulatory small non-coding RNAs that function as translational repressors. MiRNAs are involved in most cellular processes, and their expression and function are presided by several factors. Amongst, miRNA editing is an epitranscriptional modification that alters the original nucleotide sequence of selected miRNAs, possibly influencing their biogenesis and target-binding ability. A-to-I and C-to-U RNA editing are recognized as the canonical types, with the A-to-I type being the predominant one. Albeit some bioinformatics resources have been implemented to collect RNA editing data, it still lacks a comprehensive resource explicitly dedicated to miRNA editing. Here, we present MiREDiBase, a manually curated catalog of editing events in miRNAs. The current version includes 3,059 unique validated and putative editing sites from 626 pre-miRNAs in humans and three primates. Editing events in mature human miRNAs are supplied with miRNA-target predictions and enrichment analysis, while minimum free energy structures are inferred for edited pre-miRNAs. MiREDiBase represents a valuable tool for cell biology and biomedical research and will be continuously updated and expanded at https://ncrnaome.osumc.edu/miredibase .

Management of Cancer Cachexia: Attempting to Develop New Pharmacological Agents for New Effective Therapeutic Options.

Cancer cachexia (CC) is a multifactorial syndrome characterized by systemic inflammation, uncontrolled weight loss and dramatic metabolic alterations. This includes myofibrillar protein breakdown, increased lipolysis, insulin resistance, elevated energy expediture, and reduced food intake, hence impairing the patient's response to anti-cancer therapies and quality of life. While a decade ago the syndrome was considered incurable, over the most recent years much efforts have been put into the study of such disease, leading to the development of potential therapeutic strategies. Several important improvements have been reached in the management of CC from both the diagnostic-prognostic and the pharmacological viewpoint. However, given the heterogeneity of the disease, it is impossible to rely only on single variables to properly treat patients presenting this metabolic syndrome. Moreover, the cachexia symptoms are strictly dependent on the type of tumor, stage and the specific patient's response to cancer therapy. Thus, the attempt to translate experimentally effective therapies into the clinical practice results in a great challenge. For this reason, it is of crucial importance to further improve our understanding on the interplay of molecular mechanisms implicated in the onset and progression of CC, giving the opportunity to develop new effective, safe pharmacological treatments. In this review we outline the recent knowledge regarding cachexia mediators and pathways involved in skeletal muscle (SM) and adipose tissue (AT) loss, mainly from the experimental cachexia standpoint, then retracing the unimodal treatment options that have been developed to the present day.

MicroRNAs in Skeletal Muscle and Hints on Their Potential Role in Muscle Wasting During Cancer Cachexia.

Cancer-associated cachexia is a heterogeneous, multifactorial syndrome characterized by systemic inflammation, unintentional weight loss, and profound alteration in body composition. The main feature of cancer cachexia is represented by the loss of skeletal muscle tissue, which may or may not be accompanied by significant adipose tissue wasting. Such phenotypic alteration occurs as the result of concomitant increased myofibril breakdown and reduced muscle protein synthesis, actively contributing to fatigue, worsening of quality of life, and refractoriness to chemotherapy. According to the classical view, this condition is primarily triggered by interactions between specific tumor-induced pro-inflammatory cytokines and their cognate receptors expressed on the myocyte membrane. This causes a shift in gene expression of muscle cells, eventually leading to a pronounced catabolic condition and cell death. More recent studies, however, have shown the involvement of regulatory non-coding RNAs in the outbreak of cancer cachexia. In particular, the role exerted by microRNAs is being widely addressed, and several mechanistic studies are in progress. In this review, we discuss the most recent findings concerning the role of microRNAs in triggering or exacerbating muscle wasting in cancer cachexia, while mentioning about possible roles played by long non-coding RNAs and ADAR-mediated miRNA modifications.

Investigating miRNA-lncRNA Interactions: Computational Tools and Resources.

In the last two decades noncoding RNAs have been the recipients of increasing scientific interest. In particular, miRNAs, short (~22 nts) noncoding transcripts, have been thoroughly investigated since their essential role in posttranscriptional gene expression regulation had been established in the early 2000s. With the advent and the advancements of high-throughput sequencing technologies in recent years, long noncoding RNAs have also started to emerge as important actors in cellular functions and processes. Such transcripts, on average longer than 200 nt, whose functions have yet to be fully characterized, have recently been identified as regulatory elements of the RNAi pathway, harboring several miRNA response elements, uncovering the phenomena of competing endogenous RNAs (ceRNAs), or "sponge RNAs." The present chapter aims to provide a brief update on the actual biomedical relevance of ceRNAs, together with a summary of resources, tools, and practical examples of their application to aid researchers in the discovery and further elucidation of lncRNA-miRNA interactions.

ncRNA Editing: Functional Characterization and Computational Resources.

Noncoding RNAs (ncRNAs) have received much attention due to their central role in gene expression and translational regulation as well as due to their involvement in several biological processes and disease development. Small noncoding RNAs (sncRNAs), such as microRNAs and piwiRNAs, have been thoroughly investigated and functionally characterized. Long noncoding RNAs (lncRNAs), known to play an important role in chromatin-interacting transcription regulation, posttranscriptional regulation, cell-to-cell signaling, and protein regulation, are also being investigated to further elucidate their functional roles.Next-generation sequencing (NGS) technologies have greatly aided in characterizing the ncRNAome. Moreover, the coupling of NGS technology together with bioinformatics tools has been essential to the genome-wide detection of RNA modifications in ncRNAs. RNA editing, a common human co-transcriptional and posttranscriptional modification, is a dynamic biological phenomenon able to alter the sequence and the structure of primary transcripts (both coding and noncoding RNAs) during the maturation process, consequently influencing the biogenesis, as well as the function, of ncRNAs. In particular, the dysregulation of the RNA editing machineries have been associated with the onset of human diseases.In this chapter we discuss the potential functions of ncRNA editing and describe the knowledge base and bioinformatics resources available to investigate such phenomenon.

Current Knowledge and Computational Techniques for Grapevine Meta-Omics Analysis.

Growing grapevine (Vitis vinifera) is a key contribution to the economy of many countries. Tools provided by genomics and bioinformatics did help researchers in obtaining biological knowledge about the different cultivars. Several genetic markers for common diseases were identified. Recently, the impact of microbiome has been proved to be of fundamental importance both in humans and in plants for its ability to confer protection or induce diseases. In this review we report current knowledge about grapevine microbiome, together with a description of the available computational methodologies for meta-omics analysis.