Oncogenic mechanisms, molecular stratification and therapeutic targets of brain tumors

脑肿瘤的致癌机制、分子分层和治疗靶点

• 批准号: 10493186
• 负责人: Antonio Iavarone
• 金额: $ 12.52万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2022-09-26
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10493186
• 关键词: Biological; Brain Neoplasms; Cancer Model; Cancer Patient; Cells; Classification; Clinical Research; Computer Analysis; Dependence; Development; Dissection; Gene Proteins; Genomics; Glioblastoma; Goals; Human; Individual; Investigation; Laboratories; Malignant Glioma; Malignant Neoplasms; Modeling; Molecular; Motion; Oncogenes; Oncogenic; Outcome; Pathogenesis; Pathway interactions; Patients; Phenotype; Plant Roots; Proteomics; Research; Resistance; Route; Solid Neoplasm; Stratification; Subgroup; Testing; Therapeutic; Tissues; Treatment Failure; Universities; Validation; Work; base; cancer genome; cancer heterogeneity; computerized tools; design; drug sensitivity; high throughput technology; in vitro Model; in vivo; innovation; neoplastic cell; new technology; new therapeutic target; novel; operation; personalized therapeutic; programs; targeted treatment; therapeutic target; tool; transcriptomics; tumor

Abstract The work to be pursued in this application will continue and expand the program pioneered by Dr. Iavarone to combine innovative computational tools and state-of-the-art experimental cancer models in vitro and in vivo to identify homogeneous subgroups of cancer patients in order to dissect the pathogenesis of cancer and design tailored and fully validated personalized therapeutic approaches. The application is focused on glioblastoma multiforme, one of the most lethal forms of human cancer. The investigation of glioblastoma has represented a long-standing effort of Dr. Iavarone’s laboratory, which in recent work has produced novel targeted therapeutic opportunities currently being tested in clinical studies. The proposal will also benefit from the organizational contexts recently set in motion by the large network operations coordinated by the PI. The research plan is articulated around the development of a novel and integrated computational-experimental framework for: i) the identification of homogeneous groups of tumors sharing activation of the same biological pathways; ii) the study of cancer heterogeneity at the single cell level to accurately inform tumor classifications; iii) the therapeutic prediction emerging from the identification of driver modules and synthetic lethal relationships of malignant glioma. We will develop and apply novel technologies for high-throughput transcriptomic and proteomic analysis of individual cells within malignant glioma tissues. These approaches, which we have pioneered in our laboratory at Columbia University during the last few years, will serve as the basis for the multifaceted computational analysis that will extract genes and proteins responsible for the phenotypic state of individual cells. Experimental validations will be selectively applied to the novel and most exciting molecular pathways and will be performed by our laboratory that has an array of experimental tools and sequence-annotated patient-derived models to pursue each individual question. As for the selection of oncogene-dependent and independent vulnerabilities identified by our previous work, the ability of our studies to identify novel driver phenotypes and master regulators of individual tumor cells will be geared towards routing the new mechanisms into pathway-based synthetic lethality that will inform specific drug sensitivities. The successful outcome of this proposal is an integrated computational-experimental pipeline that will be able to mechanistically identify the determinants of tumor genomes and phenotypes of solid tumors. This information will be of invaluable significance to decipher evolving tumor dependencies and provide the most accurate therapeutic predictions.

抽象的 在本申请中要进行的工作将继续并扩大Iavarone博士开创的计划 在体外和体内结合创新的计算工具和最先进的实验性癌症模型 确定癌症患者的均质亚组，以剖析癌症和设计的发病机理 量身定制和完全验证的个性化治疗方法。该应用集中于胶质母细胞瘤 多形，人类癌症最致命的形式之一。胶质母细胞瘤的投资代表了 Iavarone博士实验室的长期努力，该实验室在最近的工作中产生了新颖的目标治疗 目前在临床研究中测试的机会。该提案也将从组织中受益 上下文最近由PI协调的大型网络操作进行了运动。研究计划是 围绕一个新颖而综合的计算实验框架的开发阐明：i） 鉴定同一生物学途径激活肿瘤的均匀群体； ii）研究 单细胞水平的癌症异质性，以准确告知肿瘤分类； iii）治疗性 从驱动器模块的识别和恶性肿瘤的综合致死关系中得出的预测 神经胶质瘤。我们将开发并应用新技术进行高通量转录组和蛋白质组学分析 恶性神经胶质瘤组织中的单个细胞。这些方法，我们在实验室中率先开创了 在过去的几年中，哥伦比亚大学将作为多方面计算的基础 分析将提取负责单个细胞表型状态的基因和蛋白质。实验 验证将选择性地应用于新颖，最令人兴奋的分子途径，并将进行 通过我们的实验室，具有一系列实验工具和序列注销的患者衍生模型 追求每个问题。至于选择与癌基因依赖和独立的漏洞 通过我们以前的工作确定，我们的研究能力识别新型驱动器表型和主调节器 单个肿瘤细胞的旨在将新机制路由到基于途径的合成 致死性，将为特定的药物敏感性提供依据。该提案的成功结果是一体 计算实验管道将能够机械识别肿瘤的决定剂 实体瘤的基因组和表型。这些信息对于破译的不断发展将具有无价的意义 肿瘤依赖性并提供最准确的治疗预测。