Abstract
AbstractUncontrolled cell proliferation is the key feature of tumours. Because experimental measures provide only a partial view to the underlying proliferative processes, such as cell cycling, cell quiescence and cell death, mathematical modelling aims to provide a unifying view of the data with a quantitative description of the contributing basic processes. Modelling approaches to proliferation of cell populations can be divided in two main categories: those based on first order transitions between successive compartments and those including a structure of the cells’ life cycle. Here we challenge basic models belonging to the two categories to fit time course data sets, from our laboratory experience, obtained observing the proliferative phenomenon with different experimental techniques in a cancer cell line. We disclose the limitations of too simple models. At the minimal complexity level accounting for all available data the two approaches converge and suggest similar scenarios for the underlying proliferation process, in both untreated conditions and after treatment.
Publisher
Cold Spring Harbor Laboratory