Noncanonical signaling and Emergent Trastuzumab Resistance in Breast Cancer

描述(由申请人提供)：由于我们无法推断信号网络的功能电路，从而阻碍了对分子靶向治疗耐药的理解，该信号网络受到分子靶向药物在不同种类的癌细胞群体中的干扰。因此，迫切需要为预测预后的工具创造知识基础，以推断癌细胞如何解释肿瘤微环境中存在的生化线索。我们的长期目标是通过设计新的治疗方法来克服从头开始和后天对分子靶向治疗的耐药性，从而改善癌症的临床结果。因此，这项拟议的研究与NIH的使命相关，因为它发展了基础知识，可能有助于减轻人类癌症的负担。这项应用的总体目标是验证这样一种预测，即信令网络元素之间的蛋白质表达的变化将信息流重新定向到信令网络的新分支。我们的中心假设是，已报道的乳腺癌细胞中蛋白质表达的差异改变了信号网络分支之间的细胞内信息流，从而改变了基因表达(即功能拓扑)。我们计划检验我们的中心假设，并通过追求以下具体目标来实现这一应用的总体目标：1)建立信号网络的功能拓扑取决于蛋白质表达的差异。我们的方法将是使用一系列合成信号模型来检验这一假设，这些模型使用表位标记蛋白质创建，这些蛋白质充当网络节点并在表达上发生变化。我们将评估蛋白质-蛋白质相互作用的程度是否随着基础蛋白质表达水平的不同而变化，以及新的分支是否赋予信号网络新的功能。这项拟议研究的基本原理是，确定信号蛋白表达的变化如何改变细胞的信号网络可能会导致对分子靶向治疗耐药性的更好理解，并改善对乳腺癌患者的管理。这项拟议的研究预计将产生以下预期结果。首先，这个项目将验证一个计算框架，用于解释信号蛋白的表达模式如何调节细胞对分子靶向抗癌药物的反应。创造新技术以促进对生物途径的全面研究是美国国立卫生研究院的一项路线图倡议。其次，拟议的研究将促进基于模型的推理、癌症生物学、蛋白质组学和分子生物学之间的多学科研究环境--一个未来研究团队和NIH路线图倡议的例子。预期结果将产生重要的积极影响，因为它们侧重于创造必要的知识和专门知识，以开发个性化医疗的预测工具，以改善癌症的临床管理，最初的重点是乳腺癌。 公共卫生相关性：拟议的多学科研究是了解癌细胞处理信息的变化如何影响乳腺癌患者对曲妥珠单抗的临床反应的重要一步。这项拟议的研究预计将对公众健康产生重要的积极影响，因为拟议的方法将使乳腺癌患者能够改进治疗方法，克服从头开始并获得对曲妥珠单抗的耐药性。

DESCRIPTION (provided by applicant): Understanding the basis for resistance to molecular targeted therapies is hindered by our inability to infer the functional circuitry of the signaling network that is perturbed by a molecular targeted drug within a heterogeneous population of cancer cells. Thus, there is an urgent need to create the intellectual foundation for prognostic tools to infer how cancer cells interpret biochemical cues present in the tumor microenvironment. Our long-term goal is to improve the clinical outcomes for cancer by designing novel treatments to surmount de novo and acquired resistance to molecularly targeted therapies. Thus, the proposed research is relevant to NIH's mission by developing fundamental knowledge that will potentially help to reduce the burdens of human cancer. The overall objective of this application is to validate a prediction that alterations in protein expression among elements of a signaling network redirect the flow of information down novel branches of a signaling network. Our central hypothesis is that the reported variation in protein expression among breast cancer cells alters the flow of intracellular information among branches of a signaling network that alters gene expression (i.e., the functional topology). We plan to test our central hypothesis and accomplish the overall objective of this application by pursuing the following specific aim: 1) Establish that the functional topology of signaling networks depends on differences in protein expression. Our approach will be to test the hypothesis using a series of synthetic signaling models, created using epitope-tagged proteins that function as network nodes and vary in their expression. We will assess whether the extent of protein-protein interaction varies with basal protein expression level and whether a new branch imparts new functionality to the signaling network. The rationale that underlies the proposed research is that identifying how changes in expression of signaling proteins alter a cell's signaling network may lead to an improved understanding of resistance to molecular targeted therapies and to improved management of breast cancer patients. This proposed research is projected to yield the following expected outcomes. First, this project will validate a computational framework for interpreting how expression patterns of signaling proteins modulate cellular response to molecular targeted cancer drugs. Creating new technologies to facilitate comprehensive study of biological pathways is a NIH Roadmap Initiative. Second, the proposed research will promote a multi-disciplinary research environment at the interface between model-based inference, cancer biology, proteomics, and molecular biology - an example of a research team of the future and a NIH Roadmap Initiative. The expected outcomes will have an important positive impact because they focus creating the knowledge and expertise necessary for developing the predictive tools of personalized medicine to improve the clinical management of cancer with an initial emphasis on breast cancer. PUBLIC HEALTH RELEVANCE: The proposed multi-disciplinary studies are an important step towards understanding how alterations in how cancer cells process information may influence clinical response to trastuzumab in breast cancer patients. The proposed research is expected to have an important positive impact on public health, because the approach proposed will enable improved therapies that surmount de novo and acquired resistance to trastuzumab in breast cancer patients.