UNS: Developing Quantitative Models of SHP2-Mediated Signaling regulation in Glioma for Rational Identification of Improved Therapeutic Approaches.

1511853马修J.多形性胶质母细胞瘤(GBM)是最常见的脑癌，平均生存期仅14个月。在这个项目中，将收集大量的数据集，以探索当蛋白酪氨酸磷酸酶SHP2处于正常或降低水平时，GBM细胞对不同疗法的反应。许多信号蛋白的激活状态将被并行测量。这些数据将被用来生成一个计算模型，以预测抑制哪些可药物蛋白，以对抗GBM肿瘤中促进肿瘤生长和治疗耐药的SHP2调节方面。模型预测将首先在细胞培养中进行测试，最终在GBM的小鼠模型中进行验证。这种方法以前没有被用来研究基底膜，并将利用对SHP2如何影响基底膜肿瘤行为的新理解。这项研究预计将产生重要的新见解，最终可能被用来改善美国每年14,000名被诊断为GBM的患者的临床结果。这项工作还将验证所提出的方法，将关于非药物蛋白功能的信息转化为立即可操作的治疗策略。多形性胶质母细胞瘤(GBM)是大脑最常见的恶性肿瘤。基底膜肿瘤对化疗、放射和肿瘤原激活酶的靶向抑制物具有耐药性，迫切需要新的治疗方法。来自首席调查员(PI)实验室的数据显示，蛋白酪氨酸磷酸酶SHP2控制GBM细胞信号的方式，可能被用来设计改进的GBM治疗方法。然而，数据也表明，这并不是一帆风顺的，因为SHP2同时对增殖和生存信号起着积极和消极的调节作用。最终的结果是，SHP2的表达同时促进了细胞的增殖，但也促进了GBM细胞系对某些疗法的死亡，这两种作用似乎相互冲突。此外，SHP2在GBM细胞和肿瘤中调控的信号转导过程尚未完全确定。因此，前进的道路不是简单地抑制SHP2及其所有功能，而是系统地评估在GBM中受SHP2调控的信号通路，并将这些通路的功能与感兴趣的GBM表型进行定量映射。最终，这一方法将确定SHP2调节的信号网络中的信号通路的子集，其选择性抑制将减缓GBM肿瘤的生长并增强对治疗的反应。在这项研究中，将使用偏最小二乘回归(PLSR)计算建模方法来将受SHP2调控的多变量信号事件映射到特定的GBM细胞和肿瘤表型。PLSR足够稳健，能够捕捉到初步数据揭示的趋势的复杂性和对细胞上下文的依赖。PLSR已经被成功地用于分析其他细胞系统中的信号/表型关系，但从未被用于合理地识别目前不可药物蛋白下游的有用的可药物信号节点的子集，例如在GBM或其他癌症中的SHP2。最终，该项目将确定一组新的胶质母细胞瘤治疗靶点，对SHP2在胶质母细胞瘤中的作用产生实质性的新的生物学理解，并验证一种通用的拟议方法，以绕过直接以已知在疾病中重要的特定蛋白为治疗靶点可能存在的限制。该项目还包括一套综合的教育目标，通过利用PI现有的教育计划以及与高中生和科学教育机构的联系努力，接触到来自不同背景的学生。该奖项由CBET部门的生物技术和生化工程项目获得，由分子和细胞生物学部门的系统和合成生物学项目共同资助。

1511853Lazzara, Matthew J. Glioblastoma multiforme (GBM) is the most common cancer of the brain, with an average survival time of just 14 months. In this project a large data set will be collected to probe how GBM cells respond to different therapeutics when the protein tyrosine phosphatase SHP2 is present at normal or reduced levels. Activation states of numerous signaling proteins will be measured in parallel. These data will be used to generate a computational model to predict which druggable proteins to inhibit in order to antagonize the aspects of SHP2 regulation in GBM tumors that promote tumor growth and therapeutic resistance. Model predictions will be tested first in cell culture and ultimately in mouse models of GBM. This approach has not been employed previously to study GBM and will leverage the new understanding of how SHP2 impacts GBM tumor behaviors. The research is anticipated to generate important new insights that may eventually be leveraged to improve clinical outcomes for the 14,000 patients diagnosed with GBM in the U.S. each year. The work will also validate the proposed approach to translate information on the function of a non-druggable protein into immediately actionable therapeutic strategies.Glioblastoma multiforme (GBM) is the most common malignancy of the brain. GBM tumors are resistant to chemotherapy, radiation, and targeted inhibitors of oncogenic kinases, and new therapeutic approaches are desperately needed. Data from the lab of the Principal Investigator (PI) show that the protein tyrosine phosphatase SHP2 controls GBM cell signaling in ways that could potentially be leveraged to design improved therapeutic approaches for GBM. However, the data also suggest this will not be straightforward because SHP2 simultaneously exerts positive and negative regulatory effects over proliferation and survival signaling. The net effect is that SHP2 expression simultaneously drives cellular proliferation but also promotes death in response to certain therapeutics in GBM cell lines, effects which may seem to conflict with each other. Moreover, the signaling processes regulated by SHP2 in GBM cells and tumors have not yet been fully identified. Thus, the path forward is not simply to inhibit SHP2 and all its functions broadly, but rather to systematically evaluate the signaling pathways regulated by SHP2 in GBM and to quantitatively map the functions of those pathways to GBM phenotypes of interest. Ultimately, this approach will identify a subset of signaling pathways in the SHP2-regulated signaling network whose selective inhibition will slow GBM tumor growth and augment response to therapeutics. In this research, a partial least squares regression (PLSR) computational modeling approach will be used to map multivariate signaling events regulated by SHP2 to specific GBM cell and tumor phenotypes of interest. PLSR is robust enough to capture the complexity and cell context-dependence of the trends revealed by the preliminary data. PLSR has been successfully utilized to dissect signaling/phenotype relationships in other cellular systems but has never been applied to rationally identify a subset of useful druggable signaling nodes downstream of a presently non-druggable protein such as SHP2 in GBM or other cancers. Ultimately, this project will identify a new set of therapeutic targets in glioblastoma, produce substantial new biological understanding about the role of SHP2 in glioblastoma, and validate a general proposed method for circumventing limitations that may exist for directly therapeutically targeting a specific protein known to be important in disease. The project also includes a set of integrated educational objectives to reach students from diverse backgrounds by leveraging the PI's existing educational programs and outreach efforts with high school students and science educational facilities.This award by the Biotechnology and Biochemical Engineering Program of the CBET Division is co-funded by the Systems and Synthetic Biology Program of the Division of Molecular and Cellular Biology.