Title
Angiogenesis: An improved in vitro biological system and automated image-based workflow to aid identification and characterization of angiogenesis and angiogenic modulators
Author
Santos, A.F.
Zaltsman, A.B.
Martin, R.C.
Kuzmin, A.
Alexandrov, Y.
Roquemore, E.P.
Jessop, R.A.
Erck, M.G.M.V.
Verheijen, J.H.
TNO Kwaliteit van Leven
Publication year
2008
Abstract
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. © Mary Ann Liebert, Inc. 2008.
Subject
angiogenesis modulator
bevacizumab
suramin
angiogenesis
article
automation
controlled study
human
human cell
image analysis
in vitro study
instrumentation
Angiogenesis Modulating Agents
Antibodies, Monoclonal
Automation
Cells, Cultured
Dose-Response Relationship, Drug
Drug Evaluation, Preclinical
Fibrinogen
Fluorescent Dyes
Humans
Image Processing, Computer-Assisted
Immunohistochemistry
Neovascularization, Pathologic
Neovascularization, Physiologic
Suramin
Tissue Fixation
Tumor Necrosis Factor-alpha
Vascular Endothelial Growth Factor A
To reference this document use:
http://resolver.tudelft.nl/uuid:5d915a47-649a-4232-a62b-948a6ce93475
DOI
https://doi.org/10.1089/adt.2008.146
TNO identifier
241038
ISSN
1540-658X
Source
Assay and Drug Development Technologies, 6 (5), 693-710
Document type
article