Identifying Survivors of HSP90 Inhibitor Treatment In Breast Cancer by Mass Cytometry

通过质谱流式细胞术鉴定乳腺癌 HSP90 抑制剂治疗的幸存者

• 批准号: 9229417
• 负责人: Melissa Ellen Ko
• 金额: $ 3.7万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-21 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9229417
• 关键词: Address; Affect; Apoptosis; Apoptotic; Breast Cancer Cell; Breast Cancer Treatment; Breast Cancer cell line; Cell Fraction; Cells; Cessation of life; Clinical; Clinical Trials; Combined Modality Therapy; Computer Simulation; Computing Methodologies; Cytometry; Data; Down-Regulation; Drug Exposure; Drug resistance; Exposure to; Gene Activation; Gene Expression; Genes; Genetic; Goals; HSP 90 inhibition; Heat-Shock Proteins 90; Image Analysis; Individual; Intervention; Measures; Mediating; Methodology; Methods; Modeling; Molecular; Molecular Chaperones; Mutation; Nature; Oncogenic; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacotherapy; Population; Process; Proteins; Regimen; Regulation; Reporter Genes; Research; Research Project Grants; Resistance; Resolution; Role; Signal Pathway; Signal Transduction; Signaling Molecule; Signaling Protein; Site; Solid Neoplasm; Source; Survivors; System; Systems Biology; TNFSF10 gene; Testing; Therapeutic; Time; Validation; Work; abstracting; base; cancer cell; cancer subtypes; cancer therapy; cell killing; combinatorial; drug efficacy; effective intervention; effective therapy; falls; gene therapy; genetic resistance; inhibitor/antagonist; insight; killings; malignant breast neoplasm; molecular drug target; new therapeutic target; non-genetic; prevent; resistance mechanism; response; success; targeted treatment; treatment strategy; triple-negative invasive breast carcinoma; tumorigenesis

Project Summary/Abstract Loss of activity of the heat shock protein 90 (HSP90) chaperone leads to simultaneous loss of signaling proteins from many oncogenic pathways, ultimately leading to apoptosis in cancer cells. Inhibitors of HSP90 have been proposed for clinical use in a variety of solid tumors, in particular triple-negative breast cancer (TNBC), a cancer subtype that has proven difficult to treat with other targeted molecular drugs. However, HSP90 inhibitors have struggled to demonstrate efficacy in clinical trials, in part due to non-genetic resistance where signaling in survival pathways is reactivated and cells overcome loss of HSP90 activity. A major question remains as to whether this non-genetic resistance is a cell state induced by exposure to drug or one selected from pre-existing cell states. I hypothesize that HSP90 inhibition causes signaling network changes in a subset of cancer cells that allows them to maintain pro-survival signaling activity. Comprehensively measuring the signaling network in cells responding heterogeneously to drug exposure requires a systems- based approach with single-cell resolution. Mass cytometry enables us to measure up to 45 markers in individual cells in a high-throughput manner. To elucidate the mechanism for resistance to HSP90 inhibition in TNBC, I propose to quantify signaling activity in breast cancer cell lines treated with HSP90 inhibitors with mass cytometry. However, one major challenge to studying the process of drug response is that cells are destroyed during mass cytometry analysis so the same cells cannot be followed over time. To overcome this challenge, we have developed a computational method to trace the trajectories of cells responding to drug treatment in silico from high-dimensional single-cell data. My goal is to apply this computational method to dissect the mechanisms underlying resistance to HSP90 inhibitors, identifying specific signaling features unique to TNBC cells that go on to survive HSP90 inhibition. These candidate features will then be validated using pharmacological or genetic interventions to demonstrate their role in regulating resistance to HSP90 inhibition. The results of this analysis will identify strategies for effective use of HSP90 inhibitors by finding inhibitors that synergize with HSP90 inhibition to maximize death in breast cancer cells. The source of signaling activity that distinguishes HSP90 inhibitor-resistant cells will then be investigated by determining which genes are exclusively expressed in surviving cells. Then to further address whether drug resistance is induced or selected in these populations, I will interrogate the role of timing of activation of these genes in regulating survival. Moreover, I will test how varying the timing of interventions against candidate proteins or genes affects the size of the fraction of cells that are HSP90 inhibitor-resistant. We believe this work may give insight into more successful combinatorial therapeutic strategies for HSP90 inhibitors by identifying new synergistic interventions and effective drug regimens.

项目摘要/摘要 热休克蛋白90（HSP90）伴侣的活性损失导致同时失去信号传导 来自许多致癌途径的蛋白质，最终导​​致癌细胞凋亡。 HSP90的抑制剂 已经提出了用于多种实体瘤的临床用途，特别是三阴性乳腺癌 （TNBC），一种癌症亚型，被证明很难用其他靶向分子药物治疗。然而， HSP90抑制剂一直在努力在临床试验中表现出功效，部分原因是非遗传抗性 在生存途径中信号传导被重新激活，并且细胞克服了HSP90活性的丧失。专业 问题仍然是这种非遗传抗性是暴露于药物还是一种细胞状态 从预先存在的细胞状态中选择。我假设HSP90抑制会导致信号网络的变化 癌细胞的一部分，使它们能够维持临床信号传导活性。全面 测量对药物暴露异质反应的细胞中的信号网络需要系统 - 基于单细胞分辨率的方法。质量细胞仪使我们能够测量多达45个标记 单个细胞以高通量方式。阐明在HSP90抑制中的抗性机制 TNBC，我建议用HSP90抑制剂处理的乳腺癌细胞系中的信号传导活性 质量细胞仪。但是，研究药物反应过程的一个主要挑战是细胞是 在质量细胞仪分析过程中被破坏，因此随着时间的推移无法遵循相同的细胞。克服这一点 挑战，我们开发了一种计算方法来追踪对药物响应的细胞的轨迹 高维单细胞数据中的硅处理。我的目标是将此计算方法应用于 剖析对HSP90抑制剂的抗性的机制，确定特定的信号传导特征 TNBC细胞的独有，可在HSP90抑制中生存。这些候选功能将被验证 使用药理或遗传干预措施来证明其在调节对HSP90抗性的作用 抑制。该分析的结果将通过查找有效使用HSP90抑制剂的策略 与HSP90抑制协同以最大化乳腺癌细胞死亡的抑制剂。的来源 然后，将研究区分HSP90抑制剂细胞的信号传导活性，然后通过确定 哪些基因在幸存的细胞中仅表达。然后进一步解决耐药性是否是 在这些人群中诱导或选择，我将询问这些基因激活时间的作用 调节生存。此外，我将测试针对候选蛋白质的干预时机的变化或 基因会影响HSP90抑制剂的细胞分数的大小。我们相信这项工作可能会给 通过确定新的抑制剂，深入了解HSP90抑制剂的更成功的组合治疗策略 协同干预和有效的药物方案。