Computer Model Challenges Breast Cancer Treatment Strategy

Abstract

The breast cancer treatment failure rate remains unacceptably high. The current breast cancer treatment paradigm, based primarily on Gompertzian kinetics and animal models, advocates short-course, intensive chemotherapy subsequent to tumor debulking, citing drug resistance and host toxicity as the primary reasons for treatment failure. To better understand treatment failure, we have studied breast cancer from the perspective of computer modeling. Our results demonstrate breast cancers grow in an irregular fashion; this differs from the Gompertzian mode of animal models and thus challenges the validity of the current paradigm. Clinical and laboratory data support the concept of irregular growth rather than the common claim that human tumors grow in a Gompertzian fashion. Treatment failure mechanisms for breast cancer appear to differ from those for animal models, and thus treatments optimize on animal models may not be optimal for breast cancer. A failure mechanism consistent with our results involves temporarily dormant tumor cells in anatomical or pharmacological sanctuary, which eventually result in aggressive metastatic disease.