A3 Kirjan tai muun kokoomateoksen osa
Quantitative Phenotypic Image Analysis of Three-Dimensional Organotypic Cultures

Julkaisun tekijät: Malin Åkerfelt, Mervi Toriseva, Matthias Nees
Julkaisuvuosi: 2017
Kirjan nimi *: 3D Cell Culture
Sarjan nimi: Methods in Molecular Biology
Volyymi: 1612
ISBN: 978-1-4939-7019-3
eISBN: 978-1-4939-7021-6


Glandular epithelial cells differentiate into three-dimensional (3D)
multicellular or acinar structures, particularly when embedded in
laminin-rich extracellular matrix (ECM). The spectrum of different
multicellular morphologies formed in 3D is a reliable indicator for the
differentiation potential of normal, non-transformed cells compared to
different stages of malignant progression. Motile cancer cells may
actively invade the matrix, utilizing epithelial, mesenchymal, or mixed
modes of motility. Dynamic phenotypic changes involved in 3D tumor cell
invasion are also very sensitive to small-molecule inhibitors that,
e.g., target the actin cytoskeleton. Our strategy is to recapitulate the
formation and the histology of complex solid cancer tissues in vitro,
based on cell culture technologies that promote the intrinsic
differentiation potential of normal and transformed epithelial cells,
and also including stromal fibroblasts and other key components of the
tumor microenvironment. We have developed a streamlined stand-alone
software solution that supports the detailed quantitative phenotypic
analysis of organotypic 3D cultures. This approach utilizes the power of
automated image analysis as a phenotypic readout in cell-based assays.
AMIDA (Automated Morphometric Image Data Analysis) allows quantitative
measurements of a large number of multicellular structures, which can
form a multitude of different organoid shapes, sizes, and textures
according to their capacity to engage in epithelial differentiation
programs or not. At the far end of this spectrum of tumor-relevant
differentiation properties, there are highly invasive tumor cells or
multicellular structures that may rapidly invade the surrounding ECM,
but fail to form higher-order epithelial tissue structures. Furthermore,
this system allows us to monitor dynamic changes that can result from
the extraordinary plasticity of tumor cells, e.g.,
epithelial-to-mesenchymal transition in live cell settings. Furthermore,
AMIDA supports an automated workflow, and can be combined with quality
control and statistical tools for data interpretation and visualization.
Our approach supports the growing needs for user-friendly,
straightforward solutions that facilitate cell-based organotypic 3D
assays in basic research, drug discovery, and target validation.

Last updated on 2019-29-01 at 16:48