Dynamics of multi-modal anti-angiogenic, anti-vascular, and cytotoxic therapies: Potential for significant clinical impact

物理学和数学在医学中的应用是跨学科研究中发展最快的领域之一。数学建模可以提供一个定量的框架来详细讨论复杂生物系统的所有组成部分之间的相互作用，以及测试各种治疗干预措施。新的计算技术和数学模型的结合，以实验和临床数据为基础，从而为生物医学研究提供了一个强大的新工具。确定影响癌性肿瘤治疗反应的主要因素一直是一个长期关注的问题，与临床肿瘤学相关。虽然传统的细胞毒性治疗，如放疗和化疗，有助于癌症控制的重大进展，但在许多肿瘤部位仍有显着的进一步改善空间。新的分子靶向治疗，如肿瘤血管生成（从预先存在的血管形成血管）的抑制剂，有可能补充传统治疗。目前只有极少的临床前或临床证据可用于决定如何最佳地组合联合收割机抗血管生成和细胞毒性疗法。我们的工作假设是，基于肿瘤的血管、间质和细胞区室之间的相互作用的现有和新型生物物理模型的数学建模，以及对这些相互作用对向癌细胞输送营养的影响，可以指导抗血管生成疗法与现有细胞毒性疗法的合理排序。该项目将围绕数学模型开发和改进的动态过程，使用来自动物组织学和成像研究的数据，以及来自宫颈癌和其他肿瘤患者正在进行的临床研究的患者数据。

The application of physics and mathematics to medicine is one of the most rapidly growing areas of interdisciplinary research. Mathematical modeling can provide a quantitative framework to discuss, in detail, the interaction between all components of complex biological systems, as well as to test various therapeutic interventions. The combination of novel computational techniques and mathematical models, grounded in experimental and clinical data, thus provides a powerful new tool in biomedical research. The identification of major factors that influence treatment response in cancerous tumors has been a problem of long-standing interest and relevance to clinical oncology. While conventional cytotoxic treatments like radiotherapy and chemotherapy have contributed to major advancement in cancer control, there remains significant room for further improvement in many tumor sites. Novel molecularly-targeted treatments, like inhibitors of tumor angiogenesis (the formation of blood vessels from pre-existing vessels), have the potential to complement conventional treatments. There is currently minimal pre-clinical or clinical evidence on which to base decisions about how to optimally combine anti-angiogenic and cytotoxic therapies. Our working hypothesis is that mathematical modeling based on existing and novel biophysical models of the interactions between the vascular, interstitial and cellular compartments of a tumor, and the impact on these interactions on nutrient delivery to cancer cells, can guide the rationale sequencing of anti-angiogenic therapies with existing cytotoxic treatments. The project will revolve around a dynamic process of mathematical model development and refinement, using data derived from histologic and imaging studies in animals, and patient data from ongoing clinical studies in patients with cervix cancer and other tumors.