Methods in molecular biology
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Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder due to the lack of dystrophin production. The disease is characterized by muscle wasting, with the most common causes of death being respiratory failure or heart failure. ⋯ Researchers have previously relied on high-performance liquid chromatography (HPLC) or liquid chromatography-mass spectrometry (LC/MS) methods for detecting PPMO uptake, but an enzyme-linked immunosorbent assay (ELISA) has been shown to have greater sensitivity. Here, we present methodologies to determine the uptake efficiency of a PPMO into the heart and efficacy of exon 51 skipping by a PPMO injected retro-orbitally into a humanized DMD mouse model via ELISA and RT-PCR, respectively.
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Pathological assessment of tissue is the gold standard for diagnosis and staging of neoplasia and provides key prognostic information for clinical management. Proper macroscopic assessment and cut-up technique is essential to ensure that the overall assessment is correct and reproducible. Endoscopic mucosal resection is a technique used for removing early neoplastic glandular lesions of the esophagus at the level of submucosa. Here, we describe the macroscopic assessment and dissection techniques used for the routine handling of endoscopic mucosal resection specimens in the clinical laboratory.
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Liquid biopsy of cancers is an area of increasing interest in medical practice for the surveillance, management, and potential detection of malignant cells, using minimally invasive collection of body fluids. A liquid biopsy is particularly useful for metastatic cancers, which may be difficult to be sampled by core biopsy, due to difficulty of access or an occult location. Access to DNA shed from esophageal adenocarcinoma can enable the detection of mutations confirming the presence of malignant cells or the evolution of clonal lines with altered treatment response profiles. In this chapter, we detail a method for the isolation of cell-free DNA from blood plasma and DNA associated with exosomes in blood from patients with esophageal adenocarcinoma.
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The diversity and huge omics data take biology and biomedicine research and application into a big data era, just like that popular in human society a decade ago. They are opening a new challenge from horizontal data ensemble (e.g., the similar types of data collected from different labs or companies) to vertical data ensemble (e.g., the different types of data collected for a group of person with match information), which requires the integrative analysis in biology and biomedicine and also asks for emergent development of data integration to address the great changes from previous population-guided to newly individual-guided investigations. Data integration is an effective concept to solve the complex problem or understand the complicate system. ⋯ Current integration approaches on biological data have two modes: one is "bottom-up integration" mode with follow-up manual integration, and the other one is "top-down integration" mode with follow-up in silico integration. This paper will firstly summarize the combinatory analysis approaches to give candidate protocol on biological experiment design for effectively integrative study on genomics and then survey the data fusion approaches to give helpful instruction on computational model development for biological significance detection, which have also provided newly data resources and analysis tools to support the precision medicine dependent on the big biomedical data. Finally, the problems and future directions are highlighted for integrative analysis of omics big data.
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Somatic copy-number alterations are commonly found in cancer and play key roles in activating oncogenes and deactivating tumor suppressor genes. Digital polymerase chain reaction is an effective way to detect the changes in copy number. In esophageal adenocarcinoma, detection of somatic copy-number alterations could predict the prognosis of patients as well as the response to therapy. This chapter will review the methods involved in digital polymerase chain reaction for the research or potential clinical applications in esophageal adenocarcinoma.