Using microfluidic single cell culture to characterize cancer cell asymmetric division

摘要 癌症是否遵循分层（线性）或随机（随机）分化模型具有关键的临床意义。 影响，但仍然存在很大争议。分层模型反映了正常干细胞生物学， 癌症干细胞样细胞（CSC）遵循既定的不对称分裂模式， 后代在这个模型中，只有CSC可以引发复发性疾病。在随机模型中，任何给定的肿瘤细胞 可以不对称分裂产生肿瘤的其他细胞并引发复发性疾病。的关键 决定分化模式的特征是不对称分裂潜力。然而 原代人癌细胞的不对称分裂潜力由于缺乏 技术.我们假设癌细胞将遵循分级分化途径，但很少 发生随机的去分化事件，允许一些细胞获得CSC状态。我们进一步假设 调节癌细胞不对称分裂的因素，无论是分层的还是随机的， 影响癌症生长并代表治疗靶点。为了解决技术缺陷，我们建议 SA 1：开发具有选择性活细胞的高通量单细胞微流控培养装置 检索高度平行、紧凑的1024微孔设计将允许有效的单细胞捕获、生长和微生物学特性。 本发明的目的在于表征原代人癌细胞的不对称分裂。自动化数据分析和选择 单细胞检索能力将允许对常见的和 罕见事件为了验证这项重要的新技术，我们将使用卵巢癌作为模型系统。 我们建议：SA 2：直接询问原发性卵巢癌的不对称分裂潜力 细胞我们的初步数据表明，卵巢癌遵循分级分化模型， （~1/3000）推定的随机“去分化”事件，其中祖细胞产生推定的CSC。我们 将扩大我们对不对称分裂潜力的研究，以评估患者间的变异性，并确定 环境胁迫对脱分化率的影响。重要的是，使用选择性细胞修复， 评价单细胞来源的生物学特性（化疗耐药性、肿瘤起始能力） 在不对称分裂之后，以确认分化和去分化的生物学意义， 事件最后，我们提出了SA 3：确定癌细胞分化的调节因子和癌细胞分化的驱动因子。 去分化与SA 2中的功能研究平行，来自不对称的母细胞和子细胞， 分离分裂，并通过单细胞qRT-PCR评估不同干细胞相关基因的表达。 然后将评估母细胞和子细胞之间差异表达的因子对细胞周期的影响。 CSC生长和分化。为了确定罕见的去分化事件的分子驱动因素，我们将 进行RNASeq，比较来自分级分化与随机去分化的克隆 事件然后将在体外和体内证实去分化的推定分子驱动因素。

ABSTRACT Whether cancer follows a hierarchical (linear) or stochastic (random) model of differentiation has critical clinical implications, yet remains highly controversial. The hierarchical model mirrors normal stem cell biology with cancer stem-like cells (CSC) following an established pattern of asymmetric divisions to give rise to distinct progeny. In this model only CSC can initiate recurrent disease. In the stochastic model, any given tumor cell can asymmetrically divide to give rise to the other cells of the tumor and initiate recurrent disease. The key to determining the pattern of differentiation is characterizing asymmetric division potential. However the asymmetric division potential of primary human cancer cells has not been directly interrogated due to a lack of technology. We hypothesize that cancer cells will follow a hierarchical differentiation pathway, but rare stochastic dedifferentiation events occur allowing some cells to obtain a CSC state. We further hypothesize that factors regulating the asymmetric division of cancer cells, both hierarchical and stochastic, will significantly impact cancer growth and represent therapeutic targets. To address the technology deficiency, we propose SA1: To develop a high-throughput single-cell microfluidic culture device with selective live-cell retrieval. A highly parallel, compact, 1024 microwell design will allow efficient single cell capture, growth, and characterization of asymmetric division of primary human cancer cells. Automated data analysis and selective single-cell retrieval capacity will allow for high-throughput functional and molecular analysis of common and rare events. In order to validate this important new technology we will use ovarian cancer as a model system. We propose: SA2: To directly interrogate the asymmetric division potential of primary ovarian cancer cells. Our preliminary data indicates that ovarian cancer follows a hierarchical differentiation model with rare (~1/3000) putative stochastic ‘dedifferentiation’ events wherein a progenitor cell gives rise to putative CSC. We will expand our studies of the asymmetric division potential to assess inter-patient variability and determine the impact of environmental stresses on dedifferentiation rates. Critically, using selective cell retrieval we can evaluate the biologic characteristics (chemotherapy resistance, tumor initiation capacity) of single cells derived following an asymmetric division to confirm the biologic implications of differentiation and dedifferentiation events. Finally, we propose SA3: To identify regulators of cancer cell differentiation and drivers of dedifferentiation. In parallel to the functional studies in SA2, mother and daughter cells from asymmetric divisions will be isolated and expression of distinct stem cell related genes assessed via single cell qRT-PCR. Factors differentially expressed between mother and daughter cells will then be evaluated for their impact on CSC growth and differentiation. To identify molecular drivers of the rare dedifferentiation events, we will perform RNASeq comparing clones derived from hierarchical differentiation vs. stochastic dedifferentiation events. Putative molecular drivers of dedifferentiation will then be confirmed both in vitro and in vivo.