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Angiogenesis: An Improved In Vitro Biological System and Automated Image-Based Workflow to Aid Identification and Characterization of Angiogenesis and Angiogenic Modulators

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ASSAY AND DRUG DEVELOPMENT TECHNOLOGIES
卷 6, 期 5, 页码 693-710

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MARY ANN LIEBERT, INC
DOI: 10.1089/adt.2008.146

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Angiogenesis is a general term describing formation of new tube-like microvessel sprouts that are the size of capillary blood vessels. Angiogenesis is fundamental in key stages of embryonic development, organ formation, and wound repair and is also involved in the development and progression of a variety of pathological conditions, including cancer (tumor growth and metastasis), cardiovascular disease, diabetic retinopathy, age-related macular degeneration, atherosclerosis, and rheumatoid arthritis. Because of its diverse roles in key physiological and pathological processes, angiogenesis is an important area of medical research, with a considerable number of angiogenic and anti-angiogenic drugs currently undergoing clinical trials. Cost-effective and efficient screening for potential lead compounds is therefore of prime importance. However, screening methodologies vary in their physiological relevance depending on how faithfully critical aspects of angiogenesis are represented. Cell-based in vitro angiogenesis assays are important tools for screening, which in many cases rely on imaging microscopy to ascertain drug effects. Unfortunately, such screens can be hampered by poorly defined biology, slow image acquisition by manual or semiautomated hardware, and slow data analysis by non-dedicated software. This article describes use of a 96-well microplate in vitro angiogenesis screening system as part of an integrated workflow, comprising (1) setting up the biology in a three-dimensional physiologically relevant system, (2) acquiring a series of image slices (stacks) using an automated z-stage instrument, (3) collapsing the image stack series into sets of two-dimensional images, (4) segmenting objects of interest, and (5) analyzing the segmentation patterns in order to obtain statistically relevant data.

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