Modeling causes and consequences of the evolution of cell motility in neoplasms

描述（申请人提供）：细胞运动是良性肿瘤向侵袭转移的关键因素。因此，了解1)细胞运动如何影响空间结构和2)先前静止的肿瘤细胞如何获得运动的癌症表型是很重要的。目前的方法无法检测人体内肿瘤细胞的运动。此外，很难开发干预措施来阻止细胞运动，因为选择细胞运动进化的压力知之甚少。在这里，我们使用基于主体的建模和采用生态和进化理论的技术（如系统地理分析）来生成基于活组织检查的遗传和表观遗传数据来估计运动细胞存在的方法。我们还将在计算机上测试局部资源枯竭是否可以促进细胞运动的进化。我们的第一个目标是开发统计技术来检测模拟组织中无条件运动和条件运动细胞的存在。然后，我们将使用这个框架来测试各种活检程序在转移发生之前检测运动细胞的能力。我们将使用结直肠肿瘤和巴雷特食管的数据来测试我们估计细胞运动的技术。我们的最终目标是探索导致细胞运动性进化的选择压力，特别是局部资源微环境的退化如何导致运动性的进化和出现。我们还将测试旨在减少促进细胞运动的选择性和环境压力的拟议干预措施的可行性。目标1和目标2的成功完成将产生活检方案，以便在转移发生之前早期检测细胞运动。我们的最终目标将产生新的干预假设，可以减少对运动细胞的选择，从而降低转移的风险。这些项目将有助于检测恶性肿瘤的前体，减少肿瘤发展到侵袭和转移的可能性。在组织中移动的细胞的出现是癌症在我们全身定植和良性肿瘤转化为恶性肿瘤的必要前兆。在这里，我们创建了计算模拟，使我们能够研究良性肿瘤中细胞运动产生的空间和遗传模式，以及肿瘤中细胞运动的进化力选择。这些模拟的结果应该能够开发出更有效的方法来早期发现癌症和防止恶性肿瘤演变的创新干预措施。

DESCRIPTION (provided by applicant): Cell motility is a key factor in progression from a benign neoplasm to invasion and metastasis. It is therefore important to understand 1) how cell motility affects spatial structure and 2) how previously sedentary neoplastic cells acquire the cancer phenotype of motility. Current methods cannot detect neoplastic cell motility in vivo in humans. Further, it has been difficult to develop interventions to prevent cell motility, because the pressures that select for the evolution of cell motility are poorly understood. Here, we use agent-based modeling and techniques adopted from ecological and evolutionary theory (such as phylogeographic analysis) to generate methods for estimating the presence of motile cells based on genetic and epigenetic data from biopsies. We will also test in silico whether local resource depletion can promote the evolution of cell motility. Our first aim is to develop statistical techniques for detecting the presence of unconditionally motile and conditionally motile cells in simulated tissues. We will then use this framework to test the power of various biopsy procedures to detect motile cells before metastasis has occurred. We will use data from colorectal neoplasms and Barrett's esophagus to test our techniques for estimating cell motility. Our final aim is to explore the selective pressures leading to the evolution of cell motility, in particular how degradation of local resource microenvironments leads to the evolution and emergence of motility. We will also test the viability of proposed interventions targeted towards reducing the selective and environmental pressures that promote cell motility. The successful completion of aims 1 and 2 will generate biopsy protocols to enable the early detection of cell motility before metastasis has occurred. Our final aim will generate hypotheses for novel interventions that can reduce selection for motile cells and thereby reduce the risk of metastasis. These projects will contribute to the goals of detecting precursors of malignancy and reducing the likelihood that a neoplasm will progress to invasion and metastasis. The emergence of cells that move through tissues is a necessary precursor to the colonization of cancer throughout our bodies and the transformation of a benign tumor into a malignant tumor. Here we create computational simulations that enable us to study the spatial and genetic patterns generated by the movement of cells in a benign tumor, as well as the evolutionary forces selection for cell movement in the tumor. The results of these simulations should enable the development of more effective methods for the early detection of cancer and innovative interventions that prevent the evolution of malignancy.