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：
10651751
负责人：
Antonio Iavarone
金额：
$ 39.36万
依托单位：
UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
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 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10651751
关键词：
Address Adult Aftercare Alkylating Agents Automobile Driving Bar Codes Basic Science Biological Markers Cancer Patient Cells Classification Clinic Clinical Clinical Research Combined Modality Therapy Communities DNA-dependent protein kinase Data Dependence Diagnosis Disease Elements Endowment 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 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 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 pharmacologic 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.

项目摘要该应用集中在多形胶质母细胞瘤（GBM）上，这是人类癌的最致命形式之一基因组数据产生的大量知识几乎没有得到治疗的改进。一个钥匙癌症患者临床研究成功的元素是选择同质患者组的元素具有具有可识别功能漏洞的肿瘤，而不是一般的生物标志物。在GBM中缺乏功能分类器阻碍了良好的癌症驱动机制的靶向定义的患者亚组，导致灰心的结果。该提案建立在一个新颖的分类基础上我们最近提出的GBM。与以前建立的基于标记的分类不同，新的分类器以癌细胞的功能活性为中心，我们通过单细胞转录组鉴定分析。分类器在几个批量主要GBM中进行了验证，包括四个亚型，两个与神经发育程序，神经元和增生性促进剂有关，两个以不同的代谢活性，线粒体和糖酵解溶剂替代谢。值得注意的是，线粒体亚型是具有对氧化磷酸化抑制的明显敏感性，并且与更好的生存有关而糖酵解 - 差异代谢亚型的特征是多余的代谢活性。我们的初步分析表明，每个功能性GBM亚型都与生物学相干蛋白质组学和磷酸蛋白质组学特征。在此应用中，我们将结合创新的计算工具和最新体外和体内的艺术实验模型研究GBM功能细胞态在治疗中的影响反抗。我们以以下目的构建了研究计划：i）检查和针对的可塑性在治疗压力下的神经发育胶质瘤状态和带有来自微环境； ii）确定用线粒体细胞在治疗时如何适应治疗压力线粒体抑制剂和诱导抗性的机制； iii）检索治疗干预点从关注DNA-PK和PKCD的蛋白质组学数据中，有选择性地活跃于 GBM的增生/祖细胞和糖酵解/多溶质的亚型。实验验证将应用于这些淋巴结因素，并将由我们的实验室执行，在很多年的过程中已经生成并完善了一系列实验工具，包括序列注销的患者衍生追求每个问题的模型。通过整合新的计算和实验平台来研究该提案在概念和技术上是创新的。成功该提案的结果将是传递关键信息以破译肿瘤依赖性不断发展专门针对GBM患者的不同亚组量身定制的治疗和准确的治疗策略。