Methods in molecular biology
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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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Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.
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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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Increasingly, patient models of disease are being utilized to facilitate precision medicine approaches through molecular characterization or direct chemotherapeutic testing. Organoids, 3-dimensional (3D) cultures of neoplastic cells derived from primary tumor specimens, represent an ideal platform for these types of studies because benchtop protocols previously developed for 2-dimensional cell lines can be adapted for use. These protocols include directly testing the survival of these organoid cultures when exposed to clinically relevant chemotherapeutic agents, a process we have called pharmacotyping. ⋯ While our protocol has been developed for use with patient-derived pancreatic ductal adenocarcinoma organoids, with minor modifications to the dissociation and medium conditions, this protocol could be adapted for use with a wide range of organoid cultures. We further describe our standard ATP-based assay to determine cellular survival. This protocol can be scaled for use in high-throughput assays.
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During the past 10 years, antisense oligonucleotide-mediated exon skipping and splice modulation have proven to be powerful tools for correction of mRNA splicing in genetic diseases. In 2016, the US Food and Drug Administration (FDA)-approved Exondys 51 (eteplirsen) and Spinraza (nusinersen), the first exon skipping and exon inclusion drugs, to treat patients with Duchenne muscular dystrophy (DMD) and spinal muscular atrophy (SMA), respectively. The exon skipping of DMD mRNA aims to restore the disrupted reading frame using antisense oligonucleotides (AONs), allowing the production of truncated but partly functional dystrophin proteins, and slow down the progression of the disease. ⋯ The selection of target sites, the length of AONs, the AON chemistry, and the melting temperature versus the RNA strand play important roles. A cocktail of AONs can be employed to skip multiples exons. In this chapter, we discuss the design of effective AONs for exon skipping.