Project 1: Analysis of cell autonomous mechanisms of phenotypic switching in invasive cancer models

项目总结/摘要：项目1 表型可塑性可以赋予同基因细胞群体多种共存的表型。背景下 在癌症中，两种表型对侵袭性癌症的进展具有特别的影响， “高增殖-低迁移”（“增殖”或P-表型）和“低增殖-高迁移” （攻击性或A-表型）。所谓的“生长或消失”模型表明，细胞可以在这些细胞之间切换。 相对稳定的表型状态，转换率是遗传和环境的函数， 变化从增殖表型状态到迁移表型状态的转换（P-A转换）的速率增加， 向更具侵袭性（并最终转移性）的癌症进展的信号。目前，信号 对P-A转换背后的调节网络了解甚少。在这个项目中，我们建议 使用一种新的方法来研究这种开关的高定量细节，使我们能够将两者分开 基于细胞竞争性迁移的表型，其中基因可以在激酶组或基因组上沉默， 大规模该RACE测定将使用特别侵袭性癌症的原代细胞和细胞系进行 类型：多形性胶质母细胞瘤和高度恶性黑色素瘤。我们的初步数据表明， 多种激酶的表达可以增强或抑制黑素瘤细胞迁移。此外，委员会认为， 更快，更具侵略性的细胞被发现具有多种信号传导途径的差异富集， 增殖较慢的细胞对信号传导和遗传扰动的综合分析表明， 侵袭性表型是一种复杂状态，不仅具有不同增殖和迁移 特征，但也有不同的分化和代谢状态，与以往的临床 意见。除了预期的分子参与者外，我们还发现了新的潜在调节剂， 开发了一种新的，基于合成生物学的方法来识别可以靶向这些化合物的化合物， 监管部门这些和其他发现使我们提出了一个旨在描绘的研究计划， 数学和计算建模，以及作为小区自治基础的网络的验证（即， 假设没有小区-小区通信）P-A切换。我们进一步假设， 开关可能受到环境因素波动频率的影响， 增殖表型，包括临床常用药物。人口核算模型 将使用癌细胞和，作为模型， 合成修饰的酵母细胞。我们预计，这一项目将导致更多的了解， 侵袭性肿瘤扩散估计占人类癌症死亡的90%以上。该项目将 第二个项目的补充，重点是细胞非自主机制促进或抑制 癌细胞侵袭

PROJECT SUMMARY/ABSTRACT: Project 1 Phenotypic plasticity can endow isogenic cell populations with multiple co-existing phenotypes. In the context of cancer, two phenotypes that can be of particular consequence to progression of aggressive cancers are `high proliferation-low migration' (“Proliferative” or P-phenotype) and `low proliferation-high migration' (Aggressive or A-phenotype). The so-called `grow or go' model suggests that cells can switch between these relatively stable phenotypic states, with the rates of transition being functions of the genetic and environmental changes. The increasing rate of switching from proliferative to migratory phenotypic states (the P-A switch) can signal progression to the more invasive (and ultimately metastatic) cancer progression. Currently, the signaling and regulatory networks underlying the P-A switch are poorly understood. In this project, we propose to investigate this switch in high quantitative detail using a novel approach allowing us to separate the two phenotypes based on competitive migration of cells in which genes can be silenced on the kinome- or genome- wide scale. This RACE assay will be performed with primary cells and cell lines of particularly invasive cancer types: glioblastoma multiforme and high grade melanoma. Our preliminary data suggest that the silencing of expression of a wide range of kinases can either enhance or suppress melanoma cell migration. Furthermore, faster, more aggressive cells were found to have differential enrichment of a variety of signaling pathways vs. the proliferative, slower cells. The combined analysis of the signaling and genetic perturbations suggested that the aggressive phenotype is a complex state that not only has different proliferation and migration characteristics, but also has different differentiation and metabolic states, in agreement with previous clinical observations. In addition to the expected molecular players, we identified novel potential regulators, and developed a novel, synthetic biology-based method to identify chemical compounds that can target these regulators. These and other findings led us to propose a program of research aimed at delineation, mathematical and computational modeling, and validation of the networks underlying cell-autonomous (i.e., assuming no cell-cell communication) P-A switching. We further hypothesized that the dynamics of the P-A switching can be influenced by the frequency of fluctuations of environmental factors that can suppress the proliferative phenotype, including drugs commonly used in the clinic. The model accounting for the population dynamics underlying this switching behavior will be trained using both cancer cells and, as a model, synthetically modified yeast cells. We anticipate that this project will lead to an increased understanding of invasive tumor spread estimated to account to more than 90% of deaths in human cancers. This project will be complemented by the second project focused on cell-non-autonomous mechanisms promoting or inhibiting cancer cell invasion.