Abstract 4912: A network model of circulating tumor cell dynamics: Uncovering the mechanism of metastasis

Abstract

Abstract Background: Hematogenous metastasis is a poorly understood process that accounts for the lion's share of cancer death. We hypothesize that this process can be explained by circulating tumor cells (CTCs). We endeavor to deconvolute this complex process by means of a mathematical model of CTC population dynamics within the human vascular system. Methods: We have represented the human vasculature as a network with organs represented as nodes and vascular connections as directed edges and written a system of Ordinary Differential Equations to model the dynamics of circulating tumor cells (CTCs) as they populate the body from a source tumor. We have introduced several novel concepts such as a ‘filtration fraction’ which represents the fraction of CTCs that arrest in a given organ, the ‘shedding rate’ which represents the rate at which a primary tumor sheds CTCs into the vasculature and a ‘clearance rate’ which represents the combined effects of CTC apoptosis and immune clearance. Experimental parametrization of this model is accomplished through a clinical trial at The Scripps Institute during which we measure CTC concentrations at each of the most highly connected nodes at several time points before and after definitive surgery for – to include the portal vein, the superior vena cava, peripheral venous and peripheral arterial blood. Results: Initial exploration of the model using clinical data for validation has shown that certain tumor types follow flow driven patterns of metastasis while others seem to ignore the logical spread (e.g. prostate cancer spreading to the bone does not follow the flow directed network while sarcoma to the lungs does). Reasons for this dichotomy are as of yet unknown, though we suspect that both CTC heterogeneity and some form of biological signaling response are at play. We will utilize our theoretical model to investigate this dichotomy by explicitly incorporating CTC heterogeneity and by making specific biological, phenotypic observations of CTCs from different points in the network. Conclusion: We present the first network based, filter and flow model of CTC dynamics. The act of building the theoretical model and comparing it to clinical data alone has inspired several biological hypotheses and we look forward to testing more specific questions through clinical studies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4912. doi:10.1158/1538-7445.AM2011-4912