A MATLAB Tool to Quantify Colony Size Distributions In Vitro and In Vivo
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Embargo until
2021-05-01
Date
2018-05-09
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Johns Hopkins University
Abstract
Ninety percent of cancer-related deaths are due to metastasis, hence improved methods to understand and model metastasis are required. Current methods of analyzing metastatic events in experimental animal models do not provide information on colony size distributions, and suffer from the inability to segment micrometastases. Obtaining quantitative metrics in vivo would be particularly useful in settings involving fluorescent cells, which are becoming increasingly widespread for in vitro and in vivo applications, and are important tools in identifying roles of specific proteins or genes in the metastatic cascade. Quantification of metastatic colony size distributions would also find applications in investigating clonal competition in genetically heterogenous tumors and visualizing genetic exchange between cancer cells. Furthermore, there are a limited number of mathematical models that describe metastasis (as opposed to several that focus on tumor growth).
We have developed an image-processing based method, designed using MATLAB that effectively obtains quantitative data from fluorescent cell colonies both in vitro and in vivo. The method is sensitive enough to segment lung micrometastases consisting of only 4-5 cells, which makes it suitable for mathematical modelling of cancer metastasis. The lower detection limit (compared to bioluminescence imaging or computational tomography, which are often used to validate mathematical models), higher resolution and speed of our method would assist in obtaining quantitative data for the purpose of modelling.
Our methodology can also be applied to in vitro systems as well. While clonogenic assays are often used to obtain growth potential, the assay described in this work provides confluence, colony size distributions, colony-forming potential and synergistic/ co-culture effects in fluorescently labelled cells. Also, the method provides distributions of immunostained proteins of interest between heterogenous cell populations, for instance the proliferation marker ki67. The method is fast and accurate even for densely spaced colonies, and we plan to release the MATLAB scripts as freeware for general use.
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Keywords
MATLAB, Cancer Metastasis, Colony Size Distribution