Project 1 - Evolutionary and ecological dynamics of tumor-host interactions

摘要-项目1 癌症是一个复杂的动态系统，其中跨尺度的转变是非线性的。每一次转型， 表达某种基因产物的决定，是由细胞的内容和历史决定的， 微环境信号。因此，癌症是一个开放的系统，因为癌症是在沟通， 当地的环境，可以被操纵。这些微环境选择特定的细胞 表型，因此，细胞的常驻分支通常不均匀地分布在亚区域内 在一些实施方案中，肿瘤细胞可以是单个肿瘤的细胞（“栖息地”）;其可以通过体内和离体成像来定义。在第一个PSOC期间， 我们研究了微环境因素（pH、缺氧）对癌变本身的影响。在此我们 改变我们的轨迹，与整个PSOC合作，调查治疗上可行的后果 微环境的异质性。具体来说，我们将研究：目标1，肿瘤氧合，这可以是 目标2，代谢异质性和肿瘤酸性， 可以通过特定的代谢抑制剂和缓冲疗法来靶向。具体来说，我们将遵循承诺， 研究其对免疫疗法影响的初步数据;以及，作为对项目2中新试验的回应， 目的3将检查剥夺治疗对肿瘤间质相互作用的影响。因为这些 动态是复杂的和非线性的，我们将部署特定于应用程序的数学模型， 通过与Bench-to-Beside Core集成开发。这些模型和实验 在该基金资助的过程中，它们将不断得到改进，目标是开发新的方法 基于进化动力学，可以交给项目2，并整合到新的临床试验中。

Abstract - Project 1 Cancer is a complex, dynamical system wherein transitions across scales are non-linear. Each transition, such as the decision to express a certain gene product, is governed by a cells' content and history in response to local microenvironmental signals. Hence, cancer is an open system, as the cancer is in communication with the local environment, which can be manipulated. These microenvironments select for specific cellular phenotypes and hence, resident clades of cells are often heterogeneously distributed within sub-regions (“habitats”) of individual tumors; which can be defined by in-vivo and ex-vivo imaging. In the first PSOC period, we investigated the impact of microenvironmental factors (pH, hypoxia) on carcinogenesis itself. Herein, we change our trajectory, in concert with the entire PSOC, to investigate therapeutically actionable consequences of microenvironmental heterogeneity. Specifically, we will investigate: Aim 1, tumor oxygenation, which can be targeted with specific hypoxia-activated pro-drugs; Aim 2, metabolic heterogeneity and tumor acidity, which can be targeted by specific metabolic inhibitors and buffer therapies. Specifically we will follow promising preliminary data to investigate their impact on immune therapies; and, in response to a new trial in Project 2, Aim 3 will examine the effect of hormone-deprivation therapies on tumor-stromal interactions. Because these dynamics are complex and non-linear, we will deploy application-specific mathematical models that are developed through integration with the Bench-to-Beside Core. These models and the experiments that inform them will be iteratively improved over the course of this grant with the goal of developing novel approaches based on Evolutionary Dynamics, which can be handed off to Project 2, and integrated into novel clinical trials.