Evolution and targeting of the functional states of glioblastoma

胶质母细胞瘤功能状态的进化和靶向

基本信息

批准号：
10467181
负责人：
Antonio Iavarone
金额：
$ 25.65万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2022-09-05
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10467181
关键词：
Address Adult Aftercare Alkylating Agents Automobile Driving Bar Codes Basic Science Biological Markers Cancer Patient Cells Classification Clinic Clinical Clinical Data Clinical Research Communities DNA-dependent protein kinase Data Dependence Diagnosis Disease Elements Evolution Excision Exhibits Experimental Models Favorable Clinical Outcome Gene Mutation Genetic Genetic Variation Genomics Genotype Glioblastoma Glioma Grant Heritability Human In Vitro Individual Inter-tumoral heterogeneity Intervention Knowledge Laboratories Lesion Link Malignant Neoplasms Metabolic Mitochondria Modeling Multiomic Data Neurons Nodal Operative Surgical Procedures Organoids Outcome Oxidative Phosphorylation Pathogenesis Pathway interactions Patients Pharmacology Pharmacotherapy Phosphorylation Inhibition Preclinical Testing Prognosis Protein Kinase Proteomics Radiation Radiation therapy Recurrence Reporting Research Resistance Resources Reverse engineering Signal Transduction Stratification Subgroup Testing Therapeutic Therapeutic Intervention Translating Tumor Biology Validation Work addiction base cancer cell cancer proteomics cohort computerized tools experimental study genomic data improved in vitro Model in vivo inhibitor innovation metabolomics mouse model neoplastic cell novel novel strategies patient subsets phosphoproteomics pre-clinical pressure progenitor prognostic programs rational design reconstruction single cell analysis single-cell RNA sequencing success targeted treatment temozolomide therapeutic evaluation therapeutic target tool transcriptomics tumor tumor microenvironment

项目摘要

Project Summary The application is focused on glioblastoma multiforme (GBM), one of the most lethal forms of human cancer for which the massive knowledge generated by genomic data has provided little therapeutic improvement. One key element in the success of clinical studies for cancer patients is the selection of homogeneous groups of patients harboring tumors that share identifiable functional vulnerabilities rather than general biomarkers. In GBM, the lack of a functional classifier has hindered the targeting of fundamental cancer-driving mechanisms in well- defined patient subgroups, leading to discouraging results. The proposal is founded on a novel classification of GBM that we have recently proposed. Different from previously established marker-based classification, the new classifier is centered on functional activities of cancer cells that we identified by single cell transcriptomic analysis. The classifier was validated in several cohorts of bulk primary GBM and includes four subtypes, two linked to neurodevelopmental programs, neuronal and proliferative-progenitor, and two characterized by divergent metabolic activities, mitochondrial and glycolytic-plurimetabolic. Notably, the mitochondrial subtype is endowed with a distinct sensitivity to oxidative phosphorylation inhibition and is associated with a better survival, while the glycolytic-plurimetabolic subtype is characterized by redundant metabolic activities. Our preliminary analysis revealed that each functional GBM subtype is association with biologically coherent proteomic and phosphoproteomic features. In this application we will combine innovative computational tools and state-of-the- art experimental models in vitro and in vivo to study the impact of functional cell states of GBM in therapy resistance. We built the research plan with the following aims: i) examine and target the plasticity of the neurodevelopmental glioma states under therapy pressure and the cross-talk with signals from the microenvironment; ii) determine how mitochondrial cells adjust to therapy pressure when treated with mitochondrial inhibitors and the mechanism of induced resistance; iii) retrieve therapeutic intervention points from proteomic data focusing on DNA-PK and PKCd, two protein kinases active selectively in the proliferative/progenitor and glycolytic/plurimetabolic subtypes of GBM, respectively. Experimental validations will be applied to these nodal factors and will be performed by our laboratories, which in the course of many years have generated and perfected the array of experimental tools including sequence-annotated patient-derived models to pursue each question. By integrating novel computational and experimental platforms to study the evolution of distinct GBM subtypes, the proposal is conceptually and technically innovative. The successful outcome of this proposal will be the delivery of key information to decipher evolving tumor dependencies under treatment and accurate therapeutic strategies specifically tailored to distinct subgroups of GBM patients.

项目概要该应用的重点是多形性胶质母细胞瘤 (GBM)，这是人类最致命的癌症形式之一基因组数据产生的大量知识并没有提供多少治疗改进。一键癌症患者临床研究成功的要素是选择同质患者组隐藏的肿瘤具有可识别的功能缺陷，而不是一般的生物标志物。在 GBM 中，缺乏功能分类器阻碍了针对良好的基本癌症驱动机制的定位定义的患者亚组，导致令人沮丧的结果。该提案基于一种新颖的分类我们最近提出的GBM。与之前建立的基于标记的分类不同，新的分类器以我们通过单细胞转录组学鉴定的癌细胞的功能活动为中心分析。该分类器在多个原发性 GBM 队列中进行了验证，包括四种亚型、两种亚型与神经发育程序、神经元和增殖祖细胞有关，其中两个特征是不同的代谢活动，线粒体和糖酵解多代谢。值得注意的是，线粒体亚型是对氧化磷酸化抑制具有明显的敏感性，并且与更好的生存相关，而糖酵解多代谢亚型的特点是代谢活动多余。我们的初步分析表明，每个功能性 GBM 亚型都与生物相干的蛋白质组学和相关性相关。磷酸化蛋白质组学特征。在此应用程序中，我们将结合创新的计算工具和最先进的体外和体内艺术实验模型，研究 GBM 功能细胞状态对治疗的影响反抗。我们制定研究计划的目的如下：i）检查并瞄准可塑性神经发育神经胶质瘤在治疗压力和与信号的串扰下的状态微环境； ii) 确定线粒体细胞在接受治疗时如何调整以适应治疗压力线粒体抑制剂及其诱导耐药机制； iii) 检索治疗干预点来自专注于 DNA-PK 和 PKCd 的蛋白质组数据，这两种蛋白激酶在 GBM 的增殖/祖细胞和糖酵解/多代谢亚型，分别。实验验证将应用于这些节点因素，并将由我们的实验室进行，多年来已经生成并完善了一系列实验工具，包括序列注释的患者衍生的模型来解决每个问题。通过整合新颖的计算和实验平台来研究该提案在概念和技术上都具有创新性。成功者该提案的结果将是提供关键信息，以破译不断变化的肿瘤依赖性专门针对 GBM 患者不同亚组的治疗和准确的治疗策略。