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.

项目总结/摘要 热休克蛋白90（HSP 90）伴侣蛋白活性的丧失导致信号传导的同时丧失 蛋白质从许多致癌途径，最终导致癌细胞凋亡。HSP 90抑制剂 已被提出用于多种实体瘤，特别是三阴性乳腺癌的临床应用 （TNBC），这是一种已被证明难以用其他靶向分子药物治疗的癌症亚型。然而，在这方面， HSP 90抑制剂在临床试验中很难证明有效性，部分原因是非遗传性耐药性 其中存活途径中的信号传导被重新激活，并且细胞克服了HSP 90活性的丧失。一个主要 问题仍然是这种非遗传抗性是暴露于药物诱导的细胞状态还是 从预先存在的细胞状态中选择。我假设HSP 90抑制引起了细胞内信号网络的变化， 癌细胞的一个子集，使它们能够保持促生存信号活性。全面 测量对药物暴露不均匀反应的细胞中的信号网络需要一个系统- 基于单细胞分辨率的方法。质谱细胞仪使我们能够测量多达45个标记物， 以高通量的方式分离单个细胞。为了阐明HSP 90抑制抵抗的机制， TNBC，我建议量化用HSP 90抑制剂处理的乳腺癌细胞系中的信号传导活性， 质谱细胞仪然而，研究药物反应过程的一个主要挑战是， 在大量细胞计数分析期间被破坏，因此不能随时间跟踪相同的细胞。为了克服这个 挑战，我们已经开发出一种计算方法来追踪细胞对药物反应的轨迹， 从高维单细胞数据中进行计算机处理。我的目标是将这种计算方法应用于 剖析HSP 90抑制剂耐药的潜在机制，识别特定的信号特征 这是TNBC细胞所特有的，其继续在HSP 90抑制中存活。然后将验证这些候选要素 使用药理学或遗传干预来证明它们在调节对HSP 90的抗性中的作用 抑制作用这项分析的结果将通过发现有效使用HSP 90抑制剂的策略， 抑制剂与HSP 90抑制协同作用，使乳腺癌细胞死亡最大化。的来源 然后将通过确定区分HSP 90抑制剂耐药细胞的信号传导活性来研究 这些基因只在存活的细胞中表达。为了进一步研究耐药性是否是 在这些群体中诱导或选择，我将询问这些基因激活的时间在以下方面的作用： 调节生存。此外，我将测试如何改变对候选蛋白质或 基因影响HSP 90受体抗性细胞部分的大小。我们相信这项工作可以给 通过鉴定新的HSP 90抑制剂，深入了解更成功的HSP 90抑制剂组合治疗策略 协同干预和有效的药物治疗方案。