Modelling the Growth of the MIC Niche at the System Level

描述(由申请人提供)：目标是开发连贯的实验方案和预测性数学模型，以了解骨髓瘤起始细胞(MICs，也称为骨髓瘤干细胞)和骨髓基质细胞(BMSCs，也称为骨髓源性间充质干细胞)之间的生物力学相互作用，从而调控MIC的进化。为此，我们将研究肿瘤干细胞利基(微环境)的生物物理特性和信号通路，最终目标是开发多发性骨髓瘤肿瘤生长模型，以预测针对这些利基的新治疗策略。尽管多发性骨髓瘤(MM)患者可以通过现有的治疗药物在最初达到完全缓解，但大多数MM患者最终会发展为复发疾病。研究表明，在这些患者中存在一小部分具有克隆形成潜力和高耐药性的MIC。我们的初步研究得出以下假设：1)MICS分泌高浓度的SDF1，激活SDF1/CXCR4信号通路，导致BMSCs生物力学表型的改变；2)改变的BMSC力学性能有助于MICS的命运(增殖和存活)，从而使MM.CXCR4(G蛋白偶联受体)的生长成为肌动蛋白/肌球蛋白依赖的细胞骨架信号过程的控制点，从而调节细胞和细胞膜的力学。本研究的目的是更全面地描述SDF1/CXCR4信号通路对骨髓瘤BMSCs的力学特性的影响，并通过新的数学模型模拟和预测这种变化对MIC命运的影响。为了研究肿瘤-间质细胞-细胞间的相互作用在多发性骨髓瘤发生中的作用，提出了一个预测性的3D多尺度试剂模型(ABM)。它包括：(A)细胞内水平：骨髓瘤起始细胞(MICs)和MM相关的BMSCs的细胞内信号通路特征可能在细胞间水平主导生物力学诱导的MM癌细胞表型，在组织水平上主导肿瘤的发展和疾病预后。(B)细胞间相互作用：细胞间相互作用是连接MIC和BMSC细胞内特性与MIC、BMSC和祖细胞(PC)和MM的细胞内生物力学表型转换的枢轴链。(C)组织水平：MIC、PC和MM在组织水平分泌的细胞因子将调节MIC的增殖和分化。为了实现我们的目标， 1)通过研究CXCR4/SDF1通路的修饰是否改变BMSCs的生物力学特性，以及这些改变是否影响MICs的增殖和存活，建立MICs和BMSCs的调控信号通路系统。2)建立MIC谱系模型，通过建立定量的细胞和细胞因子分析方法，利用定义良好的生物学系统来测量不同类型细胞和分泌刺激/抑制细胞因子的数量。3)结合细胞内的生物力学信号通路和细胞间的相互作用，利用基于主体的模型(ABM)建立3D MM生长预测模型。所建立的模型系统将为我们提供一个关键的工具，以了解我们如何操纵生物力学相互作用来干扰MIC的发展，从而导致骨髓瘤的治愈。

DESCRIPTION (provided by applicant): The goal is to develop coherent experimental protocols and predictive mathematical models for understanding the biomechanical interaction between myeloma-initiating cells (MICs, also known as myeloma stem cells) and bone marrow stromal cells (BMSCs, also known as bone marrow derived mesenchymal stem cells) regulating the MIC evolution. To do so, we will study the biophysical properties and signaling pathways of cancer stem cell niches (microenvironments) with the ultimate goal of developing MM cancer growth models to predict new therapeutic strategies targeting the niches. Even though multiple myeloma (MM) patients may reach a complete remission initially with therapeutic agents currently available, most MM patients eventually developed relapsed disease. Studies have suggested the presence of a small population of MICs in these patients that possess clonogenic potential and high resistance to drugs. Our preliminary studies lead to the hypotheses: 1) that MICs secret a high concentration of SDF1 which activates the SDF1/CXCR4 signaling pathway, leading to the changes in biomechanical phenotype of BMSCs and consequently, 2) that the altered BMSC mechanical properties contribute to the fate (proliferation and survival) of MICs, and thus the growth of MM. CXCR4, a G-protein coupled receptor, constitutes a control point for actin/myosin-dependent cytoskeletal signaling processes and thus regulates cell and membrane mechanics. The goals of the proposed study are to more fully characterize how the mechanical properties of myeloma BMSCs are influenced by the SDF1/CXCR4 signaling pathway, and to model and predict the impact of such changes on MIC fate by novel mathematic models. A predictive 3D multi-scale agent-based model (ABM) is proposed to investigate the role of cancer - stroma cell-to-cell interactions in multi-myeloma tumorigenesis. It includes: (a) Intracellular level: The intracellular signaling pathway features of myeloma initiating cells (MICs) and MM associated BMSCs may dominate biomechanically induced MM cancer cell phenotypes at intercellular level, cancer development and disease prognosis in the tissue level. (b) Intercellula level: Cell-to-cell interactions are the pivot chain linking intracellular level features of MIC an BMSC to intracellular biomechanical phenotype switch of MIC, BMSC, and progenitor cells (PCs) and MM. And (c) Tissue level: The cytokines secreted from MIC, PC and MM in the tissue level will regulate the proliferation and differentiation of MICs. In order to implement our goals, we set the specific aims: 1) Establish signaling pathway system using Modulated Factor Graph in regulating MICs and BMSCs by evaluating if modifying the CXCR4/SDF1 pathway changes the biomechanical properties of BMSCs and if these changes influence the proliferation and survival of MICs. 2) Establish MIC lineage model by developing quantitative cellular and cytokine assays to measure the amounts of different types of cells and secretary stimulatory/inhibitory cytokines using the well defined biological system. 3) Establish the predictive 3D MM growth model using Agent-based Model (ABM) by incorporating the biomechanical signaling pathways at intracellular level and the cell-cell interactions at intercellular level. The modeling system established will provide us a critical tool to see how we can manipulate the biomechanical interaction to interrupt the MIC development, which leads to the cure of myelomas.