Thurber Greg M, Schmidt Michael M, Wittrup K Dane
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Trends Pharmacol Sci. 2008 Feb;29(2):57-61. doi: 10.1016/j.tips.2007.11.004. Epub 2008 Jan 7.
The development of antibody therapies for cancer is increasing rapidly, primarily owing to their specificity. Antibody distribution in tumors is often extremely uneven, however, leading to some malignant cells being exposed to saturating concentrations of antibody, whereas others are completely untargeted. This is detrimental because large regions of cells escape therapy, whereas other regions might be exposed to suboptimal concentrations that promote a selection of resistant mutants. The distribution of antibody depends on a variety of factors, including dose, affinity, antigens per cell and molecular size. Because these parameters are often known or easily estimated, a quick calculation based on simple modeling considerations can predict the uniformity of targeting within a tumor. Such analyses should enable experimental researchers to identify in a straightforward way the limitations in achieving evenly distributed antibody, and design and test improved antibody therapeutics more rationally.
癌症抗体疗法的发展正在迅速增加，这主要归功于它们的特异性。然而，抗体在肿瘤中的分布往往极不均匀，导致一些恶性细胞暴露于饱和浓度的抗体中，而其他细胞则完全未被靶向。这是有害的，因为大量细胞区域逃避了治疗，而其他区域可能暴露于促进耐药突变体选择的次优浓度。抗体的分布取决于多种因素，包括剂量、亲和力、每个细胞的抗原和分子大小。由于这些参数通常是已知的或易于估计的，基于简单建模考虑的快速计算可以预测肿瘤内靶向的均匀性。此类分析应能使实验研究人员以直接的方式识别在实现抗体均匀分布方面的局限性，并更合理地设计和测试改进的抗体疗法。
