EN
Development of resistance limits efficiency of
present anticancer therapies and preventing it remains a
big challenge in cancer research. It is accepted, at the intuitive
level, that resistance emerges as a consequence of
the heterogeneity of cancer cells at the molecular, genetic
and cellular levels. Produced by many sources, tumor
heterogeneity is extremely complex time dependent statistical
characteristics which may be quantified by measures
defined in many different ways, most of them coming
from statistical mechanics. In this paper, we apply the
Markovian framework to relate population heterogeneity
to the statistics of the environment. As, from an evolutionary
viewpoint, therapy corresponds to a purposeful modi-
fication of the cells’ fitness landscape, we assume that understanding
general relationship between the spatiotemporal
statistics of a tumor microenvironment and intratumor
heterogeneity will allow to conceive the therapy as
an inverse problem and to solve it by optimization techniques.
To account for the inherent stochasticity of biological
processes at cellular scale, the generalized distancebased
concept was applied to express distances between
probabilistically described cell states and environmental
conditions, respectively.