Endogenous Heterogeneity of Signaling Pathways in Cancer

癌症被经典地建模为一种恶性转化，癌基因或肿瘤抑制基因的基因突变驱动着不受控制的细胞生长。然而，这些基因表达水平的表观遗传甚至随机内源性变化可能足以扰乱增殖和凋亡途径，并推动肿瘤的发生。因此，可能存在癌症，其起源和维持源于正常途径的非遗传扰动。 在这个项目中，我们关注慢性淋巴细胞性白血病(CLL)，这是一种淋巴增殖性疾病，其特征是成熟B淋巴细胞的克隆性扩张停滞在细胞周期的G0/G1期。到目前为止，还没有已知的突变赋予信号调节因子显性正向或显性负活性，这可能是CLL中B细胞抵抗凋亡和促进增殖的原因。信号成分的差异表达(如CDS和ZAP70的上调)被用来预测CLL患者的临床前景，但对它们与生长失调和疾病进展的相关性了解有限。 本研究的目的是研究在慢性淋巴细胞性白血病中维持增殖和凋亡的B细胞信号的异质性。为此，我们将介绍一个系统生物学平台，该平台将B细胞信号(在抗原、细胞因子或其他因素激活下)的理论建模与单个原代细胞的实验测量相结合。更具体地说，我们计划依靠B细胞的自然异质性(在CLL患者或健康人中)，绘制出CLL疾病状态的变异性。我们将开发一个理论生化模型，以确定B细胞信号中的关键信号调节因子。我们还将应用一种新的实验方法，在单细胞水平上将B细胞的反应性与这些关键信号调节因子的表达水平联系起来。最终，我们的目标是引入群体中单个细胞的多变量参数(从标记到功能反应)，以更好地表征CLL表型，并提供考虑到CLL B细胞的变异性的新的治疗方法。

Cancer is classically modeled as a malignant transformation with genetic mutation of oncogenes or tumor suppressor genes driving uncontrolled cellular growth. However, epigenetic or even stochastic endogenous variations in the expression levels of these genes may be sufficient to disregulate proliferation and apoptosis pathways, and drive tumorigenesis. Thus, there may exist cancers whose origin and maintenance stem from non-genetic perturbations of normal pathways. In this project, we focus on Chronic Lymphocytic Leukemia (CLL), a lymphoproliferative disease characterized by the clonal expansion of mature B lymphocytes arrested in the G0/G1 phase of the cell cycle. To date, there is no known mutation conferring dominant-positive or dominant negative activities to signaling regulators that would account for the resistance to apoptosis and enhanced proliferation of B cells in CLL. Differential expression of signaling components (e.g. upregulation of CDS and ZAP70) is used to predict clinical prospects for CLL patients, but there is limited understanding of their relevance to the growth dysregulation and disease progression. The goal of this research project is to study the heterogeneity of B cell signaling sustaining proliferation and apoptosis in CLL. For that purpose, we will introduce a systems biology platform that combines theoretical modeling of B cell signaling (under activation by antigens, cytokines or others) with experimental measurements on single primary cells. More specifically, we plan to rely on the natural heterogeneity of B cells (in CLL patients or in healthy individuals), to map out the variability of CLL disease states. We will develop a theoretical biochemical model, to identify key signaling regulators in B cell signaling. We will also apply a new experimental methodology to correlate, at the single cell level, B cell responsiveness with expression levels of these key signaling regulators. Ultimately, we aim at introducing multivariate parameters of individual cells within a population (from markers to functional response) to better characterize CLL phenotypes and offer new therapeutic approaches taking into account the variability in CLL B cells.