Innovative Therapeutic Approaches for Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is the most common childhood muscular dystrophy affecting ~1:5000 live male births. Following the identification of pathogenic variations in the dystrophin gene in 1986, the underlining genotype/phenotype correlations emerged and the role of the dystrophin protein was elucidated in skeletal, smooth, and cardiac muscles, as well as in the brain. When the dystrophin protein is absent or quantitatively or qualitatively modified, the muscle cannot sustain the stress of repeated contractions. Dystrophin acts as a bridging and anchoring protein between the sarcomere and the sarcolemma, and its absence or reduction leads to severe muscle damage that eventually cannot be repaired, with its ultimate substitution by connective tissue and fat. The advances of an understanding of the molecular pathways affected in DMD have led to the development of many therapeutic strategies that tackle different aspects of disease etiopathogenesis, which have recently led to the first successful approved orphan drugs for this condition. The therapeutic advances in this field have progressed exponentially, with second-generation drugs now entering in clinical trials as gene therapy, potentially providing a further effective approach to the condition

Duchenne muscular dystrophy: From diagnosis to therapy

Duchenne muscular dystrophy (DMD) is an X-linked inherited neuromuscular disorder due to mutations in the dystrophin gene. It is characterized by progressive muscle weakness and wasting due to the absence of dystrophin protein that causes degeneration of skeletal and cardiac muscle. The molecular diagnostic of DMD involves a deletions/duplications analysis performed by quantitative technique such as microarray-based comparative genomic hybridization (array-CGH), Multiple Ligation Probe Assay MLPA. Since traditional methods for detection of point mutations and other sequence variants require high cost and are time consuming, especially for a large gene like dystrophin, the use of next-generation sequencing (NGS) has become a useful tool available for clinical diagnosis. The dystrophin gene is large and finely regulated in terms of tissue expression, and RNA processing and editing includes a variety of fine tuned processes. At present, there are no effective treatments and the steroids are the only fully approved drugs used in DMD therapy able to slow disease progression. In the last years, an increasing variety of strategies have been studied as a possible therapeutic approach aimed to restore dystrophin production and to preserve muscle mass, ameliorating the DMD phenotype. RNA is the most studied target for the development of clinical strategies and Antisense Oligonucleotides (AONs) are the most used molecules for RNA modulation. The identification of delivery system to enhance the efficacy and to reduce the toxicity of AON is the main purpose in this area and nanomaterials are a very promising model as DNA/RNA molecules vectors. Dystrophinopathies therefore represent a pivotal field of investigation, which has opened novel avenues in molecular biology, medical genetics and novel therapeutic options

Detection of non-Hodgkin's lymphoma liver disease in cirrhotic patients

Computer tomography (CT) scan and ultrasound scan (US) are the preferred methods for staging subdiaphragmatic non-Hodgkin’s lymphoma (NHL),1 but their sensitivity in detecting focal lesions in the liver may be reduced if fibrosis is present. We investigated 6 NHL patients who also had a viral liver disease (chronic active hepatitis or cirrhosis) by US and CT liver scans and liver biopsy. US was performed using a Spazio-Hitachi instrument with a 3.5 MHz probe. With the exception of two patients, who underwent laparotomy as a diagnostic procedure, liver biopsy was performed under US guidance using a Menghini fine needle with automatic aspiration (1.2 mm in diameter x 150 mm in length), or a Chiba fine needle (0.7 mm x 150 mm)

Multi-omic characterisation as a tool to improve knowledge, valorisation and conservation of wild fruit genetic resources: the case of Arbutus unedo L

The valorisation and conservation of plant genetic resources (PGRs) and wild fruit PGRs are critical to ensure the maintenance of genetic and cultural heritage and to promote new perspectives on resource use. New strategies to characterize PGRs are needed, and the omics approach can provide information that is still largely unknown. The Strawberry tree (Arbutus unedo L.) is an underutilized, drought and fire-resistant species distributed in the Mediterranean area and its berries have large ethnobotanical use. Although their phenolic profile and antioxidant capacity are known, they are not well characterised, particularly from a proteomic perspective. The aim of this work is the characterisation of two ecotypes of A. unedo (Campania and Sicily) from a molecular viewpoint to valorise and encourage the preservation of this wild fruit. Samples were collected from two different geographical areas to assess whether different geographical conditions could influence the characteristics of leaves and fruits at the three stages of ripening (green, veraison, red). Proteomic analysis identified 904 proteins, of which 122 showed significance along the ripening. Some of these differentially abundant proteins, such as chalcone synthase, show a marked increase during ripening. The protein functional classes with the highest representation are involved in protein and amino acid metabolism, glycolysis and in secondary metabolism. From a proteomic perspective, there are no differences between the fruits from the two regions compared by the ripening stage. However, the pedoclimatic metabolic imprinting allowed the observation of good diversity in the metabolomic profiles between the two ecotypes, especially for anthocyanins, 4 times more abundant in the Sicilian veraisoned fruit than in the Campania one, and catechins, with double the abundance in the Campania ecotype compared to the Sicilian ecotype in the green phase, but more abundant (3x) in the Sicilian veraisoned fruit. Phenolic compounds show a 20% greater abundance in the Campania green arbutus fruit than in the Sicilian one, values that then equalise as ripening progresses. Multi-omic characterisation enhanced the knowledge on a wild fruit plant species which shows specific adaptations and responses to the environment to be considered when addressing the issue of local agrobiodiversity

Urine-Derived Stem Cells Express 571 Neuromuscular Disorders Causing Genes, Making Them a Potential in vitro Model for Rare Genetic Diseases

Background: Neuromuscular disorders (NMDs) are a heterogeneous group of genetic diseases, caused by mutations in genes involved in spinal cord, peripheral nerve, neuromuscular junction, and muscle functions. To advance the knowledge of the pathological mechanisms underlying NMDs and to eventually identify new potential drugs paving the way for personalized medicine, limitations regarding the availability of neuromuscular disease-related biological samples, rarely accessible from patients, are a major challenge. Aim: We characterized urinary stem cells (USCs) by in-depth transcriptome and protein profiling to evaluate whether this easily accessible source of patient-derived cells is suitable to study neuromuscular genetic diseases, focusing especially on those currently involved in clinical trials. Methods: The global transcriptomics of either native or MyoD transformed USCs obtained from control individuals was performed by RNA-seq. The expression of 610 genes belonging to 16 groups of disorders (http://www.musclegenetable.fr/) whose mutations cause neuromuscular diseases, was investigated on the RNA-seq output. In addition, protein expression of 11 genes related to NMDs including COL6A, EMD, LMNA, SMN, UBA1, DYNC1H1, SOD1, C9orf72, DYSF, DAG1, and HTT was analyzed in native USCs by immunofluorescence and/or Western blot (WB). Results: RNA-seq profile of control USCs shows that 571 out of 610 genes known to be involved in NMDs, are expressed in USCs. Interestingly, the expression levels of the majority of NMD genes remain unmodified following USCs MyoD transformation. Most genes involved in the pathogenesis of all 16 groups of NMDs are well represented except for channelopathies and malignant hyperthermia related genes. All tested proteins showed high expression values, suggesting consistency between transcription and protein representation in USCs. Conclusion: Our data suggest that USCs are human cells, obtainable by non-invasive means, which might be used as a patient-specific cell model to study neuromuscular disease-causing genes and that they can be likely adopted for a variety of in vitro functional studies such as mutation characterization, pathway identification, and drug screening

Circadian Genes as Exploratory Biomarkers in DMD: Results From Both the mdx Mouse Model and Patients

Duchenne muscular dystrophy (DMD) is a rare genetic disease due to dystrophin gene mutations which cause progressive weakness and muscle wasting. Circadian rhythm coordinates biological processes with the 24-h cycle and it plays a key role in maintaining muscle functions, both in animal models and in humans. We explored expression profiles of circadian circuit master genes both in Duchenne muscular dystrophy skeletal muscle and in its animal model, the mdx mouse. We designed a customized, mouse-specific Fluidic-Card-TaqMan-based assay (Fluid-CIRC) containing thirty-two genes related to circadian rhythm and muscle regeneration and analyzed gastrocnemius and tibialis anterior muscles from both unexercised and exercised mdx mice. Based on this first analysis, we prioritized the 7 most deregulated genes in mdx mice and tested their expression in skeletal muscle biopsies from 10 Duchenne patients. We found that CSNK1E, SIRT1, and MYOG are upregulated in DMD patient biopsies, consistent with the mdx data. We also demonstrated that their proteins are detectable and measurable in the DMD patients’ plasma. We suggest that CSNK1E, SIRT1, and MYOG might represent exploratory circadian biomarkers in DMD

Changing presentation of prostate cancer in a UK population--10 year trends in prostate cancer risk profiles in the East of England.

BACKGROUND: Prostate cancer incidence is rising in the United Kingdom but there is little data on whether the disease profile is changing. To address this, we interrogated a regional cancer registry for temporal changes in presenting disease characteristics. METHODS: Prostate cancers diagnosed from 2000 to 2010 in the Anglian Cancer Network (n=21,044) were analysed. Risk groups (localised disease) were assigned based on NICE criteria. Age standardised incidence rates (IRs) were compared between 2000-2005 and 2006-2010 and plotted for yearly trends. RESULTS: Over the decade, overall IR increased significantly (P<0.00001), whereas metastasis rates fell (P<0.0007). For localised disease, IR across all risk groups also increased but at different rates (P<0.00001). The most striking change was a three-fold increase in intermediate-risk cancers. Increased IR was evident across all PSA and stage ranges but with no upward PSA or stage shift. In contrast, IR of histological diagnosis of low-grade cancers fell over the decade, whereas intermediate and high-grade diagnosis increased significantly (P<0.00001). CONCLUSION: This study suggests evidence of a significant upward migration in intermediate and high-grade histological diagnosis over the decade. This is most likely to be due to a change in histological reporting of diagnostic prostate biopsies. On the basis of this data, increasing proportions of newly diagnosed cancers will be considered eligible for radical treatment, which will have an impact on health resource planning and provision

Prediction of pathological stage in patients with prostate cancer: a neuro-fuzzy model

The prediction of cancer staging in prostate cancer is a process for estimating the likelihood that the cancer has spread before treatment is given to the patient. Although important for determining the most suitable treatment and optimal management strategy for patients, staging continues to present significant challenges to clinicians. Clinical test results such as the pre-treatment Prostate-Specific Antigen (PSA) level, the biopsy most common tumor pattern (Primary Gleason pattern) and the second most common tumor pattern (Secondary Gleason pattern) in tissue biopsies, and the clinical T stage can be used by clinicians to predict the pathological stage of cancer. However, not every patient will return abnormal results in all tests. This significantly influences the capacity to effectively predict the stage of prostate cancer. Herein we have developed a neuro-fuzzy computational intelligence model for classifying and predicting the likelihood of a patient having Organ-Confined Disease (OCD) or Extra-Prostatic Disease (ED) using a prostate cancer patient dataset obtained from The Cancer Genome Atlas (TCGA) Research Network. The system input consisted of the following variables: Primary and Secondary Gleason biopsy patterns, PSA levels, age at diagnosis, and clinical T stage. The performance of the neuro-fuzzy system was compared to other computational intelligence based approaches, namely the Artificial Neural Network, Fuzzy C-Means, Support Vector Machine, the Naive Bayes classifiers, and also the AJCC pTNM Staging Nomogram which is commonly used by clinicians. A comparison of the optimal Receiver Operating Characteristic (ROC) points that were identified using these approaches, revealed that the neuro-fuzzy system, at its optimal point, returns the largest Area Under the ROC Curve (AUC), with a low number of false positives (FPR = 0.274, TPR = 0.789, AUC = 0.812). The proposed approach is also an improvement over the AJCC pTNM Staging Nomogram (FPR = 0.032, TPR = 0.197, AUC = 0.582)

Rapid Screening for Entry Inhibitors of Highly Pathogenic Viruses under Low-Level Biocontainment

Emerging viruses including Nipah, Hendra, Lujo, and Junin viruses have enormous potential to spread rapidly. Nipah virus, after emerging as a zoonosis, has also evolved the capacity for human-to-human transmission. Most of the diseases caused by these pathogens are untreatable and require high biocontainment conditions. Universal methods for rapidly identifying and screening candidate antivirals are urgently needed. We have developed a modular antiviral platform strategy that relies on simple bioinformatic and genetic information about each pathogen. Central to this platform is the use of envelope glycoprotein cDNAs to establish multi-cycle replication systems under BSL2 conditions for viral pathogens that normally require BSL3 and BSL4 facilities. We generated monoclonal antibodies against Nipah G by cDNA immunization in rats, and we showed that these antibodies neutralize both Nipah and Hendra live viruses. We then used these effective Henipavirus inhibitors to validate our screening strategy. Our proposed strategy should contribute to the response capability for emerging infectious diseases, providing a way to initiate antiviral development immediately upon identifying novel viruses