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Genetic evolution of glioblastomas during radiation and temozolomide therapy

放疗和替莫唑胺治疗期间胶质母细胞瘤的遗传进化

基本信息

批准号：
9262911
负责人：
RAMEEN BEROUKHIM
金额：
$ 68.94万
依托单位：
DANA-FARBER CANCER INST
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2020-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9262911
关键词：
Address Adult Aftercare Alkylating Agents Automobile Driving Biological Assay Biological Models Biometry Biopsy CHEK2 gene Cell Fraction Cell Line Cells Clinical Clinical Data Clinical Trials Clonal Evolution DNA sequencing Data Data Analyses Development Diagnostic Epidermal Growth Factor Receptor Erlotinib Event Evolution Exhibits Exons Genetic Genetic Heterogeneity Genome Genomics Glioblastoma Heterogeneity Human Imatinib In Vitro Individual Institution Lung Malignant - descriptor Malignant Neoplasms Mediator of activation protein Methods Minor Modeling Mutation PDGFRA gene Pathway interactions Patients Pharmaceutical Preparations Point Mutation Population Primary Brain Neoplasms Primary Neoplasm Radiation Radiation therapy Recurrence Recurrent tumor Resistance Resistance development Resolution Sampling Structure TP53 gene Testing Therapeutic Time Tissues Treatment Efficacy United States Xenograft Model Xenograft procedure chemoradiation chemotherapy deep sequencing effective therapy exome sequencing experimental study genetic evolution genetic profiling improved in vivo individual patient innovation new therapeutic target novel novel strategies novel therapeutic intervention oncology outcome prediction predictive marker prevent profiles in patients public health relevance radiation effect radiation response radioresistant resistance mechanism single cell sequencing small molecule standard of care targeted treatment temozolomide therapeutic target tool treatment effect treatment strategy tumor tumor heterogeneity

项目摘要

DESCRIPTION (provided by applicant): Glioblastomas (GBMs) are genomically well characterized, yet heterogeneous, and exhibit profound resistance to all existing treatment strategies. The most effective therapeutics are radiation therapy (RT) and the alkylating agent temozolomide (TMZ), but progression typically occurs within months after initiating these treatments. The mechanisms underlying this profound resistance remain unknown, but genetic heterogeneity is likely a major contributor, as has been shown in other cancers. Unfortunately, little is known about how GBM genomes evolve with treatment. This information would be useful to guide development of strategies to avoid the development of resistance and to identify optimal therapeutic approaches in the recurrent setting. We hypothesize that somatic genetic profiles of GBMs that recur after treatment with RT and TMZ differ substantially from pre-treatment GBMs, and that the differences point to mechanisms by which GBMs resist these treatments. To test this, we propose to identify and functionally validate recurrent genetic changes associated with resistance using innovative genomic analysis tools and patient derived model systems. Our collaborative consortium has collected an unprecedented number of paired pre- and post-treatment human tumors (>200). We have also created more than 100 patient derived GBM models that will be treated to test for the emergence of recurrent resistance drivers. Preliminary data from both patient samples and models indicate substantial tumor evolution occurs during treatment and identify TP53, CHEK2 and other rational targets as candidate mediators of resistance. Collective analysis of the data will be used to address two Aims. In Aim 1, we will test the hypothesis that treatment with radiation and temozolomide leads to consistent genetic changes in human tumors using whole exome sequencing of paired pre- and post-treatment tumor samples to determine large-scale changes in population structures and single cell sequencing to evaluate the effects of these treatments on microheterogeneity. In Aim 2, we will test the hypothesis that genetic changes identified in post-treatment GBMs functionally contribute to RT and TMZ resistance in GBM using patient derived cell lines (PDCL) and patient derived xenografts (PDX). We will determine the effects of radiation and temozolomide on these models and their genomic hierarchies using deep sequencing and test the effects of candidate drivers of resistance both in vitro and in vivo. We will determine whether resistant clones exist prior to treatment or are stochastically induced using an innovative single cell barcoding approach to determine whether the evolution of clonal substructures is consistent across replicate experiments. These studies will create a comprehensive understanding of genetic evolution during standard-of-care therapy for GBM. They will inform diagnostic approaches for assignment of targeted therapeutics in the recurrent setting and identify genetic changes driving resistance. Therapeutic targeting of these novel resistance drivers could represent a rational approach to substantially improve our existing standard of care for GBM patients.

描述(由申请人提供)：胶质母细胞瘤(GBM)具有良好的基因组特征，但具有异质性，并对所有现有的治疗策略表现出深刻的抵抗力。最有效的治疗方法是放射治疗(RT)和烷化剂替莫唑胺(TMZ)，但进展通常发生在开始这些治疗后的几个月内。这种深刻耐药性背后的机制尚不清楚，但遗传异质性可能是一个主要因素，就像在其他癌症中所显示的那样。不幸的是，人们对GBM基因组是如何随着治疗而进化的知之甚少。这些信息将有助于指导制定策略，以避免耐药性的发展，并在复发的情况下确定最佳治疗方法。我们假设，在RT和TMZ治疗后复发的GBM的体细胞遗传学特征与治疗前的GBM有很大的不同，并且这种差异指向GBM抵抗这些治疗的机制。为了测试这一点，我们建议使用创新的基因组分析工具和患者衍生的模型系统来识别和功能验证与耐药性相关的反复发生的基因变化。我们的合作联盟已经收集了空前数量的治疗前和治疗后配对的人类肿瘤(&gt；200)。我们还创建了100多个患者来源的GBM模型，这些模型将接受治疗，以测试复发耐药驱动因素的出现。来自患者样本和模型的初步数据表明，在治疗过程中发生了实质性的肿瘤演变，并将TP53、CHEK2和其他合理的靶点确定为耐药的候选介质。对数据的集体分析将用于实现两个目标。在目标1中，我们将通过对治疗前和治疗后的肿瘤样本进行全外显子测序来确定群体结构的大规模变化，并通过单细胞测序来评估这些治疗对微观异质性的影响，来检验放射治疗和替莫唑胺治疗导致人类肿瘤中一致的基因变化的假设。在目标2中，我们将使用患者来源的细胞系(PDCL)和患者来源的异种移植物(PDX)来验证这一假设，即在治疗后的GBM中发现的基因变化在功能上与GBM的RT和TMZ耐药有关。我们将使用深度测序来确定辐射和替莫唑胺对这些模型及其基因组层次的影响，并在体外和体内测试候选耐药驱动因素的影响。我们将确定是否抗性克隆在治疗前存在，或使用创新的单细胞条形码方法随机诱导，以确定克隆亚结构的进化在重复实验中是否一致。这些研究将对GBM标准护理治疗过程中的遗传进化有一个全面的了解。他们将为复发环境中分配靶向治疗药物的诊断方法提供信息，并确定驱动耐药性的基因变化。对这些新型耐药驱动因素的治疗靶向可能代表着一种合理的方法，可以显著提高我们现有的对GBM患者的护理标准。