Evolutionary approaches to prolong progression-free survival in breast cancer.
Evolutionary approaches to prolong progression-free survival in breast cancer.
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DOI：
10.1158/0008-5472.can-12-2235
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发表时间：
2012-12-15
期刊：
影响因子：
11.2
通讯作者：
Gatenby RA
中科院分区：
文献类型：
--
作者：
Silva AS;Kam Y;Khin ZP;Minton SE;Gillies RJ;Gatenby RA
许多癌症通过上调从细胞质输出药物的膜外排泵来适应化疗药物，但这种反应是以能量为代价的。在乳腺癌患者中，这些泵在治疗前的肿瘤中表达较低，但在治疗后增加。虽然治疗抗性的演变几乎是不可避免的，但抗性克隆的增殖不是，这表明适应性治疗的策略。化疗耐药细胞必须消耗多余的资源来维持耐药机制，因此适应性治疗策略明确旨在维持稳定的治疗敏感细胞群体，以通过肿瘤内竞争抑制耐药表型的生长。我们采用体外实验参数化的计算模型来说明这种方法的有效性。在这里，我们表明，低剂量的维拉帕米和2-脱氧葡萄糖，以加重耐药的成本和减少能源生产，分别可以抑制体内耐药克隆的增殖。与标准高剂量密度治疗相比，我们开发的新治疗在肿瘤模型中的进展时间增加了2至10倍。我们的研究结果挑战了现有的最大剂量治疗的有缺陷的范例，这是一种不可避免地产生耐药性的策略，可以通过我们描述的适应性治疗策略来避免。
Many cancers adapt to chemotherapeutic agents by upregulating membrane efflux pumps that export drugs from the cytoplasm, but this response comes at an energetic cost. In breast cancer patients, expression of these pumps is low in tumors before therapy but increases after treatment. While the evolution of therapeutic resistance is virtually inevitable, proliferation of resistant clones is not, suggesting strategies of adaptive therapy. Chemoresistant cells must consume excess resources to maintain resistance mechanisms, so adaptive therapy strategies explicitly aim to maintain a stable population of therapy-sensitive cells to suppress growth of resistant phenotypes through intratumoral competition. We employed computational models parameterized by in vitro experiments to illustrate the efficacy of such approaches. Here we show that low doses of verapamil and 2-deoxyglucose, to accentuate the cost of resistance and to decrease energy production, respectively, could suppress the proliferation of drug-resistant clones in vivo. Compared to standard high dose density treatment, the novel treatment we developed achieved a 2- to 10-fold increase in time to progression in tumor models. Our findings challenge the existing flawed paradigm of maximum dose treatment, a strategy that inevitably produces drug resistance which can be avoided by the adaptive therapy strategies we describe.