Attack of the Clones: Understanding the kinetics of resistance to cancer
treatment
James Yates, MMath, PhD, Principal Scientist, AstraZeneca, Cambridge UK
Wednesday Sep 18, 2019, 12:00 to 1:00 pm EDT
Register for free at
https://register.gotowebinar.com/register/4098877494283132684
Abstract:
Despite survival gains that have been made with targeted anti-cancer medicines,
patients ultimately relapse due to drug resistant disease. It is widely
understood that this is due to the presence of drug resistant cells present in
the tumour - a concept acknowledged since the 1970s. Acquired genetic lability
is required for cancer cells to express a phenotype that can escape both
normal, homeostatically controlled, tissue turnover as well as evade immune
surveillance. Therefore, it is no surprise that some cancer cells will gain
further advantage via drug resistance. The onset of this resistance will
dictate the time to progression and ultimately death. It would therefore be
beneficial to anticipate the evolution of resistance in treated tumours to
inform the optimal treatment regimen, optimal sequence of treatments,
combination strategies and to prioritise mutations to target with new medicines.
In this talk current knowledge of resistance kinetics in the clinic based upon
observations and model-based analyses will be reviewed. The question of whether
drug resistance is innate or acquired on treatment will be discussed as well as
evidence for both processes. Using models of resistance kinetics, the
relationship between resistant disease, PFS and OS can be demonstrated. These
models can also be used to understand the optimal regimen to control resistant
disease. However, an ongoing challenge is how to interrogate clinical data that
represent the "patient journey" through multiple lines of therapy. This is
important so that the influence treatment history has on the duration of
response to subsequent treatment options can be understood.
Moving back to animal models of cancer, a review of modelling of xenografted
tumour experiments reveals that similar resistance kinetics are observed. This
suggests that modelling assumptions of the relative fitness of drug resistant
vs sensitive cells can be tested along with modelling the impact of spatially
constrained solid tumour growth. An example of using in vitro data for
different NSCLC EGFR driven mutants to predict clonal selection in vivo will be
used to demonstrate these concepts. Thus, these nonclinical in vitro and in
vivo systems, coupled with mathematical modelling, could prove to be useful
tools for investigating clonal evolution.