Stress response networks in cancer: systematic mapping and therapeutic potential

癌症中的应激反应网络：系统绘图和治疗潜力

• 批准号: 9117472
• 负责人: Martin Kampmann
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9117472
• 关键词: Allografting; Antineoplastic Agents; Biological Markers; Bortezomib; CREBBP gene; Cancer Biology; Cancer Patient; Cancer cell line; Cause of Death; Cell Line; Cells; Cellular Stress Response; Chromosome Mapping; Clinical; Clinical Trials; Collaborations; Combined Modality Therapy; Complex; Development; Dexamethasone; Drug Combinations; Drug Interactions; Drug Targeting; Drug resistance; Foundations; Genes; Genetic; Genetic Predisposition to Disease; Genomic Instability; Goals; Growth; Health; Hematopoietic Neoplasms; Human; Hypersensitivity; Individual; Lethal Genes; MCL1 gene; Malignant Neoplasms; Mammalian Cell; Maps; Measures; Messenger RNA; Multiple Myeloma; Mutation; Nutrient; Oxygen; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacotherapy; Phenotype; Postdoctoral Fellow; Proteasome Inhibitor; Proteins; Proteome; Publishing; RNA Interference; Relapse; Research; Research Activity; Resistance; Resistance development; Role; Sampling; Scientist; Stress; Technology; Testing; Therapeutic; Tissue Banking; Tissue Banks; Training; Training Activity; Translations; United States; Work; Xenograft Model; anticancer research; base; biological adaptation to stress; cancer cell; career; clinically relevant; combinatorial; drug sensitivity; endoplasmic reticulum stress; gene function; gene interaction; improved; in vivo; inhibitor/antagonist; innovation; insight; knock-down; mouse model; new combination therapies; new technology; novel; novel therapeutic intervention; patient stratification; pre-clinical; prognostic of survival; programs; protein folding; relapse patients; response; skills; targeted treatment; tumor

DESCRIPTION (provided by applicant): Cancer cells survive and thrive under extremely stressful conditions, such as inadequate supply of oxygen and nutrients, genomic instability and proteome imbalances. My central hypothesis is that many cancer cells adapt stress response pathways and become uniquely dependent on them. Individual stress response factors have been characterized and some are currently being investigated as drug targets in cancer. However, we lack a systematic description of the complex, redundant organization of individual factors in a stress response net- work. Understanding this network would enable us to characterize cancer-specific adaptations and vulnerabilities that can be exploited for targeted therapies. To gain this depth of insight, new systematic approaches are called for. As a postdoc in the Weissman lab, I have co-developed a technology platform for systematic map- ping of genetic interactions in mammalian cells. Genetic interactions measure how the phenotype of one mutation is modified by a second mutation. A strong synergistic effect of inactivating two genes simultaneously is referred to as "synthetic lethality". Synthetic lethal genes are ideal targets of effective combination therapies that pre-empt drug resistance. Systematic genetic interaction maps reveal gene functions and cellular path- ways. My long-term goal is to use innovative systematic approaches to understand the complexity of stress network adaptations in cancer and exploit their therapeutic potential. This application focuses on multiple myeloma (MM) as a paradigm. MM cells are characterized by constitutive activation of a stress response, the un- folded protein response. Despite recent advances in MM drug therapy, nearly all patients develop resistance and relapse. The development of better combination therapies for MM is thus an unmet clinical need. In preliminary studies with our platform in MM cell lines, we identified novel genetic vulnerabilities in the stress response network. Expression levels of several of these genes are prognostic of survival in MM and other cancer patients. The overall objective of this application is to determine interactions between these and other vulnerabilities in MM, and to validate the therapeutic potential of targeting these synergistic vulnerabilities in MM and other cancers. I propose the following specific aims: (1) Characterize stress-related and intrinsic vulnerabilities in multiple myeloma and other blood cancer cells (2) Test the role of stress-related genes in determining drug sensitivity and resistance in patient cells (3) Validate the therapeutic potential of targeting the stress response network in multiple myeloma mouse models. This project will provide the basis to test new combination therapies and biomarkers for MM in clinical trials, and pave the way for broad application of our genetic interaction mapping approach to a wide variety of cancers. Through the proposed research and training activities, I will acquire the necessary skills to launch my career as an independent scientist, and lay the foundation of my research program, in which I plan to use innovative approaches to elucidate cancer biology and identify new therapeutic strategies to improve human health.

描述（由申请人提供）：癌细胞在极度紧张的条件下生存和茁壮成长，例如氧气和营养供应不足，基因组不稳定和蛋白质组失衡。我的主要假设是，许多癌细胞适应应激反应途径，并变得独特地依赖于它们。个体应激反应因子已被表征，其中一些正在作为癌症的药物靶点进行研究。然而，我们缺乏对应激反应网络中个体因素的复杂、冗余组织的系统描述。了解这个网络将使我们能够描述癌症的特异性适应和脆弱性，这些适应和脆弱性可以用于靶向治疗。为了获得这种深度的洞察力，需要新的系统方法。作为魏斯曼实验室的博士后，我与人合作开发了一个技术平台，用于系统地绘制哺乳动物细胞中的遗传相互作用。遗传相互作用衡量的是一个突变的表型如何被另一个突变所改变。同时灭活两个基因的强大协同效应被称为“合成致死率”。合成致死基因是预防耐药性的有效联合治疗的理想目标。系统的遗传相互作用图谱揭示了基因功能和细胞通路。我的长期目标是使用创新的系统方法来了解癌症中压力网络适应的复杂性，并开发其治疗潜力。本应用以多发性骨髓瘤（MM）为例。MM细胞的特征是组成性激活应激反应，即未折叠蛋白反应。尽管最近MM药物治疗取得了进展，但几乎所有患者都会出现耐药性和复发。因此，开发更好的MM联合疗法是一个未满足的临床需求。在用我们的平台对MM细胞系进行的初步研究中，我们发现了应激反应网络中新的遗传脆弱性。其中一些基因的表达水平是MM和其他癌症患者生存的预后因素。本应用程序的总体目标是确定MM中这些和其他脆弱性之间的相互作用，并验证针对MM和其他癌症中这些协同脆弱性的治疗潜力。我提出以下具体目标：(1)表征多发性骨髓瘤和其他血癌细胞的压力相关和内在脆弱性(2)测试压力相关基因在决定患者细胞药物敏感性和耐药性中的作用(3)验证针对多发性骨髓瘤小鼠模型的应激反应网络的治疗潜力。该项目将为在临床试验中测试MM的新联合疗法和生物标志物提供基础，并为将我们的基因相互作用定位方法广泛应用于各种癌症铺平道路。通过拟议的研究和培训活动，我将获得作为一名独立科学家开始职业生涯所需的技能，并为我的研究计划奠定基础，在我的研究计划中，我计划使用创新的方法来阐明癌症生物学，并确定新的治疗策略，以改善人类健康。