Methods in molecular biology
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Duchenne muscular dystrophy (DMD) is a congenital X-linked disease caused by mutations in the gene encoding the dystrophin protein, which is required for myofiber integrity. Exon skipping therapy is an emerging strategy for restoring the open reading frame of the dystrophin gene to produce functional protein in DMD patients by skipping single or multiple exons. ⋯ Our laboratory previously reported that disrupting the splicing acceptor site in exon 45 by plasmid delivery of the CRISPR-Cas9 system in iPS cells, derived from a DMD patient lacking exon 44, successfully restored dystrophin protein expression in differentiated myoblasts. Herein, we describe an optimized methodology to prepare myoblasts differentiated from iPS cells by mRNA transfection of the CRISPR-Cas9 system to skip exon 45 in myoblasts, and evaluate the restored dystrophin by RT-PCR and Western blotting.
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Spinal muscular atrophy (SMA) is one of the most common genetic causes of infantile death arising due to mutations in the SMN1 gene and the subsequent loss of motor neurons. With the discovery of the intronic splicing silencer N1 (ISS-N1) as a potential target for antisense therapy, several antisense oligonucleotides (ASOs) are being developed to include exon 7 in the final mRNA transcript of the SMN2 gene and thereby increasing the production of spinal motor neuron (SMN) proteins. Nusinersen (spinraza), a modified 2'-O-methoxyethyl (MOE) antisense oligonucleotide is the first drug to be approved by Food and Drug Agency (FDA) in December of 2016. Here we briefly review the pharmacological relevance of the drug, clinical trials, toxicity, and future directions following the approval of nusinersen.
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Fulfilling the promises of precision medicine will depend on our ability to create patient-specific treatment regimens. Therefore, being able to translate genomic sequencing into predicting how a patient will respond to a given drug is critical. In this chapter, we review common bioinformatics approaches that aim to use sequencing data to predict sample-specific drug susceptibility. ⋯ Those additional drug properties can aid in gaining higher accuracy for the identification of drug target and mechanism of action. We then progress to discuss using these targets in combination with disease-specific expression patterns, known pathways, and genetic interaction networks to aid drug choice. Finally, we conclude this chapter with a general overview of machine learning methods that can integrate multiple pieces of sequencing data along with prior drug or biological knowledge to drastically improve response prediction.
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Spinal muscular atrophy (SMA) is an autosomal recessive disorder caused by a mutation in SMN1 that stops production of SMN (survival of motor neuron) protein. Insufficient levels of SMN results in the loss of motor neurons, which causes muscle weakness, respiratory distress, and paralysis. A nearly identical gene (SMN2) contains a C-to-T transition which excludes exon 7 from 90% of the mature mRNA transcripts, leading to unstable proteins which are targeted for degradation. ⋯ Nusinersen (Spinraza), the first FDA-approved antisense oligonucleotide drug targeting SMA, was designed based on this concept and clinical studies have demonstrated a dramatic improvement in patients. Novel chemistries including phosphorodiamidate morpholino oligomers (PMOs) and locked nucleic acids (LNAs), as well as peptide conjugates such as Pip that facilitate accurate targeting to the central nervous system, are explored to increase the efficiency of exon 7 inclusion in the appropriate tissues to ameliorate the SMA phenotype. Due to the rapid advancement of treatments for SMA following the discovery of ISS-N1, the future of SMA treatment is highly promising.
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Advances in molecular biology and genetics have been used to elucidate the fundamental genetic mechanisms underlying central nervous system (CNS) diseases, yet disease-modifying therapies are currently unavailable for most CNS conditions. Antisense oligonucleotides (ASOs) are synthetic single stranded chains of nucleic acids that bind to a specific sequence on ribonucleic acid (RNA) and regulate posttranscriptional gene expression. Decreased gene expression with ASOs might be able to reduce production of the disease-causing protein underlying dominantly inherited neurodegenerative disorders. ⋯ A deep and wide-ranging understanding of the basic, preclinical, clinical, and epidemiologic components of drug development will improve the likelihood of success. This includes characterizing the natural history of the disease, including evolution of biomarkers indexing the underlying pathology; using predictive preclinical models to assess the putative gain-of-function of mutant Htt protein and any loss-of-function of the wild-type protein; characterizing toxicokinetic and pharmacodynamic effects of ASOs in predictive animal models; developing sensitive and reliable biomarkers to monitor target engagement and effects on pathology that translate from animal models to patients with HD; establishing a drug delivery method that ensures reliable distribution to relevant CNS tissue; and designing clinical trials that move expeditiously from proof of concept to proof of efficacy. This review focuses on the translational science techniques that allow for efficient and informed development of an ASO for the treatment of HD.