Research ArticleCancer

Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer

Science Translational Medicine  24 Feb 2016:
Vol. 8, Issue 327, pp. 327ra24
DOI: 10.1126/scitranslmed.aad7842

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Evolution of cancer therapy

The standard approach to treating cancer is giving patients the maximum tolerated amount of chemotherapy with the goal of doing the maximum possible damage to the tumor without killing the patient. This method is relatively effective, but it also causes major toxicities. Now, Enriquez-Navas et al. have demonstrated a different approach for ensuring efficacy of chemotherapy and minimizing toxicity. The authors used an evolutionary approach, where the dose of chemotherapy is guided by the tumor’s response to the previous dose, allowing a gradual withdrawal of the drug if the tumor continues to respond. This method proved quite effective for paclitaxel treatment in two different mouse models and warrants further evaluation in additional models as well as human trials.


Conventional cancer treatment strategies assume that maximum patient benefit is achieved through maximum killing of tumor cells. However, by eliminating the therapy-sensitive population, this strategy accelerates emergence of resistant clones that proliferate unopposed by competitors—an evolutionary phenomenon termed “competitive release.” We present an evolution-guided treatment strategy designed to maintain a stable population of chemosensitive cells that limit proliferation of resistant clones by exploiting the fitness cost of the resistant phenotype. We treated MDA-MB-231/luc triple-negative and MCF7 estrogen receptor–positive (ER+) breast cancers growing orthotopically in a mouse mammary fat pad with paclitaxel, using algorithms linked to tumor response monitored by magnetic resonance imaging. We found that initial control required more intensive therapy with regular application of drug to deflect the exponential tumor growth curve onto a plateau. Dose-skipping algorithms during this phase were less successful than variable dosing algorithms. However, once initial tumor control was achieved, it was maintained with progressively smaller drug doses. In 60 to 80% of animals, continued decline in tumor size permitted intervals as long as several weeks in which no treatment was necessary. Magnetic resonance images and histological analysis of tumors controlled by adaptive therapy demonstrated increased vascular density and less necrosis, suggesting that vascular normalization resulting from enforced stabilization of tumor volume may contribute to ongoing tumor control with lower drug doses. Our study demonstrates that an evolution-based therapeutic strategy using an available chemotherapeutic drug and conventional clinical imaging can prolong the progression-free survival in different preclinical models of breast cancer.

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