Abstract

This work is based on the hypothesis that shape of the cell on substrate is determined by the active mechanical properties of the cytoskeleton. Since invasive cancer cells are believed to have altered mechanical properties compared with non-invasive cells, it follows that changes in shape of cancer cells may correlate with the acquisition of invasive capacity. We try to understand whether there is a correlation between cancer cell shape and its phenotypic state. To proceed, we first need to capture cell shape and quantify it. Cells were cultured on glass substrates and then were fixed and stained for actin cytoskeleton. Images were processed to eliminate background noise. In order to quantitatively describe cell's shape, we chose a set of Zernike moments, which are widely used in image recognition and are calculated from a set of orthogonal basis function. Since we are dealing with high dimensional data we used principal component analysis (PCA) to examine changes in cell shape. We also used a machine learning neural network classifier to distinguish between different cell populations. We use paired osteosarcoma cancer lines which consist of a parental line that rarely undergoes metastasis and a line derived from parental line that almost always does. Comparing shape changes of invasive cancer line versus their paired low invasive cancer line gives insight to correlation between cell shape and invasiveness. To understand cytoskeletal mechanism behind this relation we perturbed cytoskeleton with different pharmaceutical drugs which each targets different element of the cytoskeleton and looked at the patterns of drug effect on cell shape. We also characterize shape changes of normal cells during their genetic step-wise transformation to cancer cells. [1]S. M. Lyons et. al. Biology Open 2016, 5, 289-299. [2]E.Alizadeh et. al. Integrative Biology, 2016, http://dx.doi.org/10.1039/C6IB00100A.

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