Engineered microenvironments as biomimetic culture platforms for studying the role of brain extracellular matrix in acquisition of resistance to EGFR inhibition across multiple biological scales

 描述：有大量证据表明，大脑中独特的细胞外环境，含有很少的纤维蛋白和大量的透明质酸(HA)，是导致被归类为多形性胶质母细胞瘤(GBM)的脑肿瘤具有特征性侵袭性和对常规治疗耐药的原因。然而，肿瘤细胞与细胞外基质(ECM)之间的特异性相互作用及其与肿瘤生理学的关系在很大程度上还不清楚。总体而言，这些机制很难阐明，很大程度上是因为缺乏可以在体外受控环境下研究的生理可翻译模型。为了满足这一需求，我们提出了一种基于生物材料的方法来创建原代GBM细胞的三维(3D)培养，以准确地表示复杂的体内微环境并保存临床肿瘤的生理学。这些培养平台允许以前所未有的精度独立、正交地控制多个微环境参数(模数、多肽含量、HA含量)。通过将这种方法与微环境参数和转录因子(TF)活性的动态测量相结合，我们建议在多个生物学水平上研究GBM微环境与耐药性之间的关系。特别是，我们的目标是确定特定的细胞-细胞外基质相互作用作为潜在的临床靶点，其干扰抑制获得耐药的表皮生长因子受体(EGFR)抑制剂。本申请的目的1)描述一项计划，以1)充分描述临床GBM的生化和生物物理情况，以及2)识别传递这些微环境线索的特定细胞-ECM相互作用，诱导GBM细胞对EGFR抑制剂的治疗表现出较差的反应。为了确定特定的相互作用，患者来源的GBM细胞将在基于HA的3D水凝胶中培养，这代表了一种受控的实验系统，在该系统中，HA浓度、可用整合素结合肽的密度和特性以及机械模数可以精确地变化，并区分它们的独立影响。同时，Aim 2描述了使用高通量方法动态监测活的3D培养中的TF活性的细胞内对EGFR抑制的反应。由于大脑中独特的细胞外基质是耐药的主要媒介，Aim 1中概述的模拟大脑的水凝胶平台将为进行这些研究提供理想的培养环境。这些实验将表征当非耐药的GBM细胞首次暴露于EGFR抑制剂时发生的复杂转录事件，并实时定量测量对这些处理的渐进反应，包括获得耐药性。总之，这些研究提供了一个很有希望的机会 在多个生物学水平(即，目标1中的细胞表面-ECM界面和目标2中的转铁蛋白与细胞核中的基因启动子结合)确定新的药物靶点以辅助治疗EGFR抑制。考虑到GBM肿瘤内细胞的显著异质性，以及这些细胞可能采用的获得化疗药物耐药性的各种机制[46，47，50，51]，从系统水平了解所涉及的信号网络将是该领域为GBM治疗寻找有效药理靶点的宝贵财富。

 DESCRIPTION: There is a large body of evidence that suggests that the unique extracellular environment in the brain, which contains few fibrous proteins and high amounts of hyaluronic acid (HA), is responsible for the characteristic aggressiveness and resistance to conventional treatments observed in brain tumors categorized as glioblastoma mulitforme (GBM). However the specific interactions between tumor cells and the extracellular matrix (ECM) and their relationship to tumor physiology are largely unknown. In general, these mechanisms have been challenging to elucidate, in large part because of the lack of physiologically translatable models that can be studied in controlled context ex vivo. To fulfill this need, we propose a biomaterials-based approach to create three-dimensional (3D) cultures of primary GBM cells that accurately represent the complex, in vivo microenvironment and preserve physiology of clinical tumors. These culture platforms permit independent, orthogonal control of multiple micro environmental parameters (modulus, peptide content, HA content) with unprecedented precision. By combining this approach with dynamic measurements of micro environmental parameters and transcription factor (TF) activity, we propose to investigate the relationships between the GBM microenvironment and drug resistance on multiple biological levels. In particular, we aim to identify specific cell-ECM interactions as potential clinical targets whose disruption inhibits acquisition of resistance epidermal growth factor receptor (EGFR) inhibitors. Aim 1 of this application describes a plan to 1) fully characterize the biochemical and biophysical landscape in clinical GBM and 2) identify specific cell-ECM interactions that relay these microenvironment cues, inducing GBM cells to exhibit poor response to treatment with EGFR inhibitors. To identify specific interactions, patient- derived GBM cells will be cultured within 3D, HA-based hydrogels, which represent a controlled experimental system where HA concentration, density and identity of available integrin-binding peptides, and mechanical modulus can be precisely varied and their independent effects distinguished. In parallel, Aim 2 describes studies in which the intracellular response to the EGFR inhibition using a high-throughput approach to dynamically monitor TF activity in live, 3D cultures. As the unique ECM in the brain is a major mediator of drug resistance, the brain-mimetic hydrogel platforms outlined in Aim 1 will provide an ideal culture environment in which to perform these studies. These experiments will characterize the complex transcriptional events that occur when non-resistance GBM cells are first exposed to EGFR inhibitors and quantitative measure the progressive response to these treatments, including acquisition of resistance, in real-time. Together, these studies provide a promising opportunity to identify new pharmacological targets for adjunct treatments to EGFR inhibition at multiple biological levels (i.e., cell surface-ECM interface in Aim 1 and TF binding to gene promoters in the nucleus in Aim 2). Given the significant heterogeneity of cells within GBM tumors and the variety of mechanisms that these cells may adopt to gain resistance to chemotherapeutic drugs [46,47,50,51], a systems-level understanding of the signaling networks involved would be a valuable asset to the field for identifying potent pharmacological targets for GBM treatment.