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（由适用提供）：胶质母细胞瘤（GBMS）在遗传上表征，但异质，并且对所有现有治疗策略都具有深远的抵抗力。最有效的疗法是放射疗法（RT）和烷基化剂替莫唑胺（TMZ），但进展通常发生在启动这些治疗后的几个月内。这种深刻抗药性的基础机制仍然未知，但是遗传异质性可能是主要贡献者，正如其他癌症所示。不幸的是，对于GBM基因组如何随着治疗的发展而言，知之甚少。该信息对于指导策略的制定将很有用，以避免抵抗的发展并确定在复发环境中的最佳治疗方法。我们假设用RT和TMZ处理后与治疗前GBM不同的GBM的体细胞遗传特征，并且差异指向GBMS抵抗这些治疗方法的机制。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并在功能上验证与阻力相关的复发遗传变化。我们的合作联盟已收集了史无前例的配对前和治疗后的人类肿瘤（> 200）。我们还创建了100多个患者衍生的GBM模型，这些模型将经过处理以测试复发驱动因素的出现。来自患者样品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进化，并确定TP53，CHEK2和其他合理靶标作为抗药性候选者。数据的集体分析将用于解决两个目标。在AIM 1中，我们将测试以下假设：使用配对前和治疗后肿瘤样品的整个外显子组测序对人类肿瘤的遗传变化一致，从而确定人群结构和单细胞测序的大规模变化，以评估这些处理对微生物学性的影响。在AIM 2中，我们将测试以下假设：使用患者衍生的细胞系（PDCL）和患者衍生的异种移植物（PDX），在处理后GBMS中鉴定在功能上有助于GBM的RT和TMZ抗性的遗传变化。我们将使用深层测序确定辐射和替莫洛唑胺对这些模型及其基因组层次结构的影响，并测试体外和体内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，以确定在重复实验中克隆的子结构的演化是否一致。这些研究将在GBM的护理标准疗法期间对遗传进化有一个全面的了解。他们将在复发环境中为诊断方法提供诊断方法，以分配目标治疗，并确定驱动抗药性的遗传变化。这些新型抗性驱动因素的治疗靶向可能代表了一种合理的方法，可以实质上改善我们为GBM患者现有的护理标准。