Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
Trinity Biosciences Institute, Trinity College, Dublin, Ireland.
Cancer Res. 2020 Dec 1;80(23):5147-5154. doi: 10.1158/0008-5472.CAN-19-3981. Epub 2020 Sep 15.
Deaths from cancer are mostly due to metastatic disease that becomes resistant to therapy. A mainstay treatment for many cancers is chemotherapy, for which the dosing strategy is primarily limited by patient toxicity. While this MTD approach builds upon the intuitively appealing principle that maximum therapeutic benefit is achieved by killing the largest possible number of cancer cells, there is increasing evidence that moderation might allow host-specific features to contribute to success. We believe that a "Goldilocks Window" of submaximal chemotherapy will yield improved overall outcomes. This window combines the complex interplay of cancer cell death, immune activity, emergence of chemoresistance, and metastatic dissemination. These multiple activities driven by chemotherapy have tradeoffs that depend on the specific agents used as well as their dosing levels and schedule. Here we present evidence supporting the idea that MTD may not always be the best approach and offer suggestions toward a more personalized treatment regime that integrates insights into patient-specific eco-evolutionary dynamics.
癌症导致的死亡主要归因于转移性疾病，这种疾病对治疗具有抗药性。化疗是治疗许多癌症的主要手段，其给药策略主要受患者毒性的限制。虽然这种最大耐受剂量（MTD）方法基于一个直观的吸引力原则，即通过杀死尽可能多的癌细胞来获得最大的治疗效果，但越来越多的证据表明，适度可能会使宿主特异性特征有助于取得成功。我们相信，亚最大剂量化疗的“金发姑娘区间”将带来更好的总体结果。这个区间结合了癌细胞死亡、免疫活性、化疗耐药性的出现和转移扩散的复杂相互作用。这些由化疗驱动的多种活动存在权衡，这取决于所用的特定药物以及其剂量水平和方案。在这里，我们提供了支持这样一种观点的证据，即最大耐受剂量（MTD）可能并不总是最佳方法，并为更个性化的治疗方案提供了建议，该方案将整合对患者特定生态进化动态的见解。
