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 本申请中要开展的工作将继续并将 Iavarone 博士开创的计划扩展到 结合创新的计算工具和最先进的体外和体内实验癌症模型 识别癌症患者的同质亚组，以剖析癌症的发病机制并进行设计 量身定制且经过充分验证的个性化治疗方法。该应用专注于胶质母细胞瘤 多形性，人类最致命的癌症之一。胶质母细胞瘤的研究代表了 Iavarone 博士实验室的长期努力，在最近的工作中产生了新型靶向治疗药物 目前正在临床研究中测试机会。该提案还将受益于组织 最近由 PI 协调的大型网络操作启动了环境。研究计划是 围绕开发一种新颖的综合计算实验框架进行阐述：i） 鉴定共享相同生物途径激活的同质肿瘤组； 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 从驱动模块的识别和恶性细胞的综合致死关系中得出的预测 神经胶质瘤。我们将开发和应用高通量转录组和蛋白质组分析的新技术 恶性神经胶质瘤组织内的单个细胞。这些方法是我们在实验室首创的 过去几年在哥伦比亚大学的研究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。实验性的 验证将有选择地应用于新颖且最令人兴奋的分子途径，并将进行 我们的实验室拥有一系列实验工具和序列注释的患者衍生模型 追求每个单独的问题。关于癌基因依赖性和独立性漏洞的选择 通过我们之前的工作确定，我们的研究有能力识别新的驱动表型和主调节因子 单个肿瘤细胞的研究将致力于将新机制转化为基于途径的合成 致死率将告知特定药物的敏感性。该提案的成功成果是综合 能够机械地识别肿瘤决定因素的计算实验管道 实体瘤的基因组和表型。这些信息对于破译进化论具有不可估量的意义 肿瘤依赖性并提供最准确的治疗预测。