Abstract 4626: Quantifying erlotinib response variability in EGFR-addicted cells.
Authors: Peter L. Frick, Darren R. Tyson, Shawn P. Garbett, Carlos F. Lopez, Zach W. Jones, Vito Quaranta
Journal: Cancer Research (2013)

Abstract Patients with activating epidermal growth factor receptor (EGFR) mutations display drastic initial responses to erlotinib, but tumor reduction and progression-free survival vary widely. An open question is whether response variation derives, in part, from tumor heterogeneity, i.e., differential composition of cells responding to erlotinib with distinct cell fates (death, division, or quiescence). Conventional assays obscure response heterogeneity by taking average measurements of cell populations. To address this question we developed high-throughput live-cell imaging assays that quantify both subpopulation growth dynamics and cell-to-cell fate variability in response to drug. The Dynamic Colony Growth Assay (DCGA) tracks simultaneously the erlotinib response of hundreds of single-cell-derived colonies from within a cell population. In the PC9 lung cancer cell line (widely used to model oncogene addiction, exon19del EGFR) the DCGA reveals that individual colonies span a wide range of erlotinib response, from continued cell division to massive apoptosis. Plotting net growth rates of 207 colonies shows that PC9 parental is comprised of a normally-distributed aggregate of individual single colonies responding to erlotinib with steady-state growth rates from positive to negative. Notably, the positive-growth colonies lie in the tail of this response distribution, suggesting they do not originate from rare genetic variants or cancer stem cells but, rather, are part of a continuous response distribution that is an attribute of parental PC9. To determine whether isolated PC9 colonies maintain unique rate responses, we expanded random-sampled single cells (without erlotinib selection) into 7 discrete sublines (DS), which remain highly sensitive to erlotinib (IC50 ∼50nM). In each DS, erlotinib induced an initial non-linear growth period (72h) followed by a distinct steady-state growth rate that predicts the long-term (10d) response. DS steady-state growth rates were resolved into individual cell fate composition by Fractional Proliferation Assays (FPA). As expected from random selection, the growth rates of treated DS clustered around the median of the DCGA rate distribution, missing the most extreme, less frequent erlotinib responses. Isolating the greatest variance in erlotinib response should facilitate identification of molecular mechanisms underlying drug response variation. Therefore, we isolated 96 new DS and selected the two with highest (DS-B03) and lowest (DS-C03) erlotinib steady state growth rate. We are currently measuring the activity of hundreds of proteins in these two DS by Microwestern Arrays to discover protein signatures and/or mechanistic models that quantitatively link FPA-resolved cell fates to underlying signaling network events. Thus tumor response variability and recurrence may be explained by a continuous distribution of erlotinib response at the level of single cells within a tumor. Citation Format: Peter L. Frick, Darren R. Tyson, Shawn P. Garbett, Carlos F. Lopez, Zach W. Jones, Vito Quaranta. Quantifying erlotinib response variability in EGFR-addicted cells. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4626. doi:10.1158/1538-7445.AM2013-4626