Aptamer-conjugated gold nanoparticles enable oligonucleotide delivery into muscle stem cells to promote regeneration of dystrophic muscles.

Inefficient targeting of muscle stem cells (MuSCs), also called satellite cells, represents a major bottleneck of current therapeutic strategies for muscular dystrophies, as it precludes the possibility of promoting compensatory regeneration. Here we describe a muscle-targeting delivery platform, based on gold nanoparticles, that enables the release of therapeutic oligonucleotides into MuSCs. We demonstrate that AuNPs conjugation to an aptamer against α7/β1 integrin dimers directs either local or systemic delivery of microRNA-206 to MuSCs, thereby promoting muscle regeneration and improving muscle functionality, in a mouse model of Duchenne Muscular Dystrophy.

Network medicine and systems pharmacology approaches to predicting adverse drug effects.

Identifying and understanding the relationships between drug intake and adverse effects that can occur due to inadvertent molecular interactions between drugs and targets is a difficult task, especially considering the numerous variables that can influence the onset of such events. The ability to predict these side effects in advance would help physicians develop strategies to avoid or counteract them. In this article, we review the main computational methods for predicting side effects caused by drug molecules, highlighting their performance, limitations and application cases.

Correlation-based network integration of lung RNA sequencing and DNA methylation data in chronic obstructive pulmonary disease.

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous, chronic inflammatory process of the lungs and, like other complex diseases, is caused by both genetic and environmental factors. Detailed understanding of the molecular mechanisms of complex diseases requires the study of the interplay among different biomolecular layers, and thus the integration of different omics data types. In this study, we investigated COPD-associated molecular mechanisms through a correlation-based network integration of lung tissue RNA-seq and DNA methylation data of COPD cases (n = 446) and controls (n = 346) derived from the Lung Tissue Research Consortium.

Pan-neuronal expression of human mutant SOD1 in Drosophila impairs survival and motor performance, induces early neuroinflammation and chromosome aberrations.

Several mutations in the SOD1 gene encoding for the antioxidant enzyme Superoxide Dismutase 1, are associated with amyotrophic lateral sclerosis, a rare and devastating disease characterized by motor neuron degeneration and patients' death within 2-5 years from diagnosis. Motor neuron loss and related symptomatology manifest mostly in adult life and, to date, there is still a gap of knowledge on the precise cellular and molecular events preceding neurodegeneration. To deepen our awareness of the early phases of the disease, we leveraged two Drosophila melanogaster models pan-neuronally expressing either the mutation A4V or G85R of the human gene SOD1 (hSOD1 or hSOD1).

Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors.

Background: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). Herein, we provide a GM functional characterization, based on GM metabolomics, mapping of bacterial biochemical pathways, and anamnestic, clinical, and nutritional patient metadata.

Hepatitis B Virus and microRNAs: A Bioinformatics Approach.

In recent decades, microRNAs (miRNAs) have emerged as key regulators of gene expression, and the identification of viral miRNAs (v-miRNAs) within some viruses, including hepatitis B virus (HBV), has attracted significant attention. HBV infections often progress to chronic states (CHB) and may induce fibrosis/cirrhosis and hepatocellular carcinoma (HCC). The presence of HBV can dysregulate host miRNA expression, influencing several biological pathways, such as apoptosis, innate and immune response, viral replication, and pathogenesis.

An ontology-based approach for modelling and querying Alzheimer's disease data.

Background: The recent advances in biotechnology and computer science have led to an ever-increasing availability of public biomedical data distributed in large databases worldwide. However, these data collections are far from being "standardized" so to be harmonized or even integrated, making it impossible to fully exploit the latest machine learning technologies for the analysis of data themselves. Hence, facing this huge flow of biomedical data is a challenging task for researchers and clinicians due to their complexity and high heterogeneity.

Circular RNA mediated gene regulation in human breast cancer: A bioinformatics analysis.

Circular RNAs (circRNAs) are a new acknowledged class of RNAs that has been shown to play a major role in several biological functions both in physiological and pathological conditions, operating as critical part of regulatory processes, like competing endogenous RNA (ceRNA) networks. The ceRNA hypothesis is a recently discovered molecular mechanism that adds a new key layer of post-transcriptional regulation, whereby various types of RNAs can reciprocally influence each other's expression competing for binding the same pool of microRNAs, even affecting disease development. In this study, we build a network of circRNA-miRNA-mRNA interactions in human breast cancer, called CERNOMA, that is a bipartite graph with one class of nodes corresponding to differentially expressed miRNAs (DEMs) and the other one corresponding to differentially expressed circRNAs (DEC) and mRNAs (DEGs).

Upper gut heat shock proteins HSP70 and GRP78 promote insulin resistance, hyperglycemia, and non-alcoholic steatohepatitis.

A high-fat diet increases the risk of insulin resistance, type-2 diabetes, and non-alcoholic steato-hepatitis. Here we identified two heat-shock proteins, Heat-Shock-Protein70 and Glucose-Regulated Protein78, which are increased in the jejunum of rats on a high-fat diet. We demonstrated a causal link between these proteins and hepatic and whole-body insulin-resistance, as well as the metabolic response to bariatric/metabolic surgery.

Evaluating homophily in networks via HONTO (HOmophily Network TOol): a case study of chromosomal interactions in human PPI networks.

Summary: It has been observed in different kinds of networks, such as social or biological ones, a typical behavior inspired by the general principle 'similarity breeds connections'. These networks are defined as homophilic as nodes belonging to the same class preferentially interact with each other. In this work, we present HONTO (HOmophily Network TOol), a user-friendly open-source Python3 package designed to evaluate and analyze homophily in complex networks.

Identification of Potential Repurposable Drugs in Alzheimer's Disease Exploiting a Bioinformatics Analysis.

Alzheimer's disease (AD) is a neurologic disorder causing brain atrophy and the death of brain cells. It is a progressive condition marked by cognitive and behavioral impairment that significantly interferes with daily activities. AD symptoms develop gradually over many years and eventually become more severe, and no cure has been found yet to arrest this process.

Alzheimer's disease: insights from a network medicine perspective.

Alzheimer's disease (AD) is the most common neurodegenerative disease that currently lacks available effective therapy. Thus, identifying novel molecular biomarkers for diagnosis and treatment of AD is urgently demanded. In this study, we exploited tools and concepts of the emerging research area of Network Medicine to unveil a novel putative disease gene signature associated with AD.

Rethinking purinergic concepts and updating the emerging role of P2X7 and P2X4 in amyotrophic lateral sclerosis.

The topic of the present review regards the ubiquitous and phylogenetically most ancient prototype of intercellular signaling, the one mediated by extracellular nucleosides and nucleotides, bearing a strong influence on pathophysiological processes in the nervous system. Not by chance, purine and pyrimidine molecules are the most prevalent and ubiquitous chemical messengers in the animal and plant kingdoms, operating through a large plethora of purinergic metabolizing enzymes, P1 and P2 receptors, nucleoside and nucleotide channels and transporters. Because ectonucleotidases degrade the agonists of P2 receptors while simultaneously generate the agonists for P1 receptors, and because several agonists, or antagonists, simultaneously bind and activate, or inhibit, more than one receptor subtype, it follows that an all-inclusive "purinergic network" perspective should be better considered when looking at purinergic actions.

Gut Microbiota Ecology and Inferred Functions in Children With ASD Compared to Neurotypical Subjects.

Autism spectrum disorders (ASDs) is a multifactorial neurodevelopmental disorder. The communication between the gastrointestinal (GI) tract and the central nervous system seems driven by gut microbiota (GM). Herein, we provide GM profiling, considering GI functional symptoms, neurological impairment, and dietary habits.

StaRTrEK:in silico estimation of RNA half-lives from genome-wide time-course experiments without transcriptional inhibition.

Background: Gene expression is the result of the balance between transcription and degradation. Recent experimental findings have shown fine and specific regulation of RNA degradation and the presence of various molecular machinery purposely devoted to this task, such as RNA binding proteins, non-coding RNAs, etc. A biological process can be studied by measuring time-courses of RNA abundance in response of internal and/or external stimuli, using recent technologies, such as the microarrays or the Next Generation Sequencing devices.

An integrative in-silico analysis discloses a novel molecular subset of colorectal cancer possibly eligible for immune checkpoint immunotherapy.

Background: Historically, the molecular classification of colorectal cancer (CRC) was based on the global genomic status, which identified microsatellite instability in mismatch repair (MMR) deficient CRC, and chromosomal instability in MMR proficient CRC. With the introduction of immune checkpoint inhibitors, the microsatellite and chromosomal instability classification regained momentum as the microsatellite instability condition predicted sensitivity to immune checkpoint inhibitors, possibly due to both high tumor mutation burden (TMB) and high levels of infiltrating lymphocytes. Conversely, proficient MMR CRC are mostly resistant to immunotherapy.

SPINNAKER: an R-based tool to highlight key RNA interactions in complex biological networks.

Background: Recently, we developed a mathematical model for identifying putative competing endogenous RNA (ceRNA) interactions. This methodology has aroused a broad acknowledgment within the scientific community thanks to the encouraging results achieved when applied to breast invasive carcinoma, leading to the identification of PVT1, a long non-coding RNA functioning as ceRNA for the miR-200 family. The main shortcoming of the model is that it is no freely available and implemented in MATLAB®, a proprietary programming platform requiring a paid license for installing, operating, manipulating, and running the software.

Comprehensive network medicine-based drug repositioning via integration of therapeutic efficacy and side effects.

Despite advances in modern medicine that led to improvements in cardiovascular outcomes, cardiovascular disease (CVD) remains the leading cause of mortality and morbidity globally. Thus, there is an urgent need for new approaches to improve CVD drug treatments. As the development time and cost of drug discovery to clinical application are excessive, alternate strategies for drug development are warranted.

A Comparison of Network-Based Methods for Drug Repurposing along with an Application to Human Complex Diseases.

Drug repurposing strategy, proposing a therapeutic switching of already approved drugs with known medical indications to new therapeutic purposes, has been considered as an efficient approach to unveil novel drug candidates with new pharmacological activities, significantly reducing the cost and shortening the time of de novo drug discovery. Meaningful computational approaches for drug repurposing exploit the principles of the emerging field of Network Medicine, according to which human diseases can be interpreted as local perturbations of the human interactome network, where the molecular determinants of each disease (disease genes) are not randomly scattered, but co-localized in highly interconnected subnetworks (disease modules), whose perturbation is linked to the pathophenotype manifestation. By interpreting drug effects as local perturbations of the interactome, for a drug to be on-target effective against a specific disease or to cause off-target adverse effects, its targets should be in the nearby of disease-associated genes.

In silico recognition of a prognostic signature in basal-like breast cancer patients.

Background: Triple-negative breast cancers (TNBCs) display poor prognosis, have a high risk of tumour recurrence, and exhibit high resistance to drug treatments. Based on their gene expression profiles, the majority of TNBCs are classified as basal-like breast cancers. Currently, there are not available widely-accepted prognostic markers to predict outcomes in basal-like subtype, so the selection of new prognostic indicators for this BC phenotype represents an unmet clinical challenge.