Abstract 2018: Systems biology modeling of cellular radiosensitivity: A heterogeneity signature in the clonogenic assay
Authors: Yoonseok Kam, Katarzyna A. Rejniak, Haiyan Zhao, Veronica Estrella, Alexander R. Anderson, Vito Quaranta, Javier F. Torres-Roca
Journal: Cancer Research (2010)

Abstract The clonogenic cell survival assay has been used to determine intrinsic cellular radiosensitivity in vitro. The cellular model based on this assay has clinical implication in predicting tumor response to clinical radiotherapy. However, the SF2 (survival fraction at 2Gy) value as determined from the whole cell population represents its averaged radiosensitivity, whilst we have shown that the cultured tumor cell populations include colonies of varying sizes, cell numbers and growth rates. Here we propose a novel systems biological approach to build an integrative model predicting cellular radiosensitivity that combines SF2 clonogenic assay experimentation, high-content screening and image analysis together with a quantitative bio-mathematical study. By using the live cell imaging of several lung cancer cell lines cultured in normal growing condition, we found that they are characterized by a high level of intrinsic heterogeneity with respect to multiple parameters. On the contrary, AALE, a non-transformed immortalized lung epithelial cell line appeared to be relatively homogenous. The cluster analysis of individual cellular colonies showed distinct “signature” patterns of heterogeneity between control and irradiated cells. In order to determine such a dynamic response to irradiation, the use of integrative models combining experimentation with high-throughput and high content analysis methods is highly desired. In this study, we integrated the 96-well plate-based SF2 assay with an automated image analysis using Cell ProfilerTM (Broad Institute, MA). All samples were stained for both, the whole cells and their nuclei, and the individual well images were captured and analyzed. The measured parameters include SF2 value (colony numbers per well) from an automated colony identification, a colony tightness index (cell density in a colony), and colony growth rate (cell numbers in a colony). We have also developed new algorithms to complement those implemented in Cell ProfilerTM since the default algorithms were not able to identify some highly dispersed colonies. We used our integrative model to analyze four lung cancer cell lines located at different positions on the radiosensitivity spectrum in vitro together with AALE. They showed some common phenotypic shifts after irradiation, such as reduction in growth rate and cell density. However, the responding patterns of each subpopulation and the range of heterogeneity varied depending on the cell line. The systems biological high-throughput approach proposed in this study is designed to provide information on multiple parameters measured simultaneously from the SF2 assay outcome. We expect that this protocol will be a platform for determining more refined radiosensitivity predictions with a strong clinical implication. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2018.