Practically, all chemotherapeutic agents lead to drug resistance. Clinically,
it is a challenge to determine whether resistance arises prior to, or as a
result of, cancer therapy. Further, a number of different intracellular and
microenvironmental factors have been correlated with the emergence of drug
resistance. With the goal of better understanding drug resistance and its
connection with the tumor microenvironment, we have developed a hybrid
discrete-continuous mathematical model. In this model, cancer cells described
through a particle-spring approach respond to dynamically changing oxygen and
DNA damaging drug concentrations described through partial differential
equations. We thoroughly explored the behavior of our self-calibrated model
under the following common conditions: a fixed layout of the vasculature, an
identical initial configuration of cancer cells, the same mechanism of drug
action, and one mechanism of cellular response to the drug. We considered one
set of simulations in which drug resistance existed prior to the start of
treatment, and another set in which drug resistance is acquired in response to
treatment. This allows us to compare how both kinds of resistance influence the
spatial and temporal dynamics of the developing tumor, and its clonal
diversity. We show that both pre-existing and acquired resistance can give rise
to three biologically distinct parameter regimes: successful tumor eradication,
reduced effectiveness of drug during the course of treatment (resistance), and
complete treatment failure