Abstract:
Cancer is characterized by unregulated growth of certain cells in the body, often
leading to a rapid growth of tumors in vital organs. Various treatments have been proposed and
given to cancer patients, including combinations of radiation, chemotherapy, and
immunotherapy, with varying rates of success. Characterization of the disease (and the search
for a cure) is made more challenging by the observed heterogeneous behavior and variability of
growth rates of cells, particularly cells forming tumors in various stages of development.
Heterogeneity refers to apparently dissimilar traits and behavior of individual cells or cell
subpopulations, despite originating from a common tumor or parental line. In the last
several decades, developments in mathematical biology, together with increasing availability
of sophisticated laboratory equipment (aided by powerful computers) has provided a
framework for the quantification and study of cell traits, including variability. We review
some recent work on heterogeneity and growth variability in the context of mathematical
models proposed. In the models presented, variance in cell proliferation rate distribution
signals heterogeneity, so that mechanisms tuning variance are considerations for treatment
strategies. We look into previous work and studies on sources of variability and stochasticity,
and some numerical approaches are discussed, in order to deal with huge gene networks
implicated in the complex process of cell division, proliferation and heterogeneity.
