TOWARDS A REFINED MOLECULAR RECURSIVE PARTITIONING ANALYSIS MODEL FOR GLIOBLASTOM

建立精细的胶质母细胞分子递归分区分析模型

• 批准号: 7944134
• 负责人: KENNETH D ALDAPE
• 金额: $ 102万
• 依托单位: AMERICAN COLLEGE OF RADIOLOGY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7944134
• 关键词: Adjuvant; Adult; Asia; Biological; Biological Markers; Brain Neoplasms; Cancer Center; Categories; Classification; Clinical; Clinical Research; Clinical Trials; Clinical Trials Cooperative Group; Collection; Communities; Comprehensive Cancer Center; Data; Data Set; Databases; Development; Diagnosis; Dose; Eligibility Determination; Enrollment; Epigenetic Process; Europe; Functional disorder; Funding Mechanisms; Future; Genes; Genetic; Glioblastoma; Glioma; Gold; Grant; Heterogeneity; Human; Individual; Institution; International; Investigational Therapies; Joints; Laboratories; MGMT gene; Malignant - descriptor; Malignant Glioma; Malignant Neoplasms; Malignant neoplasm of brain; Messenger RNA; Methodology; Methods; Methylation; Microarray Analysis; Mining; Modeling; Molecular; Molecular Genetics; Newly Diagnosed; North America; Ohio; Outcome; Pathway interactions; Patients; Pattern; Phase; Pre-Clinical Model; Prognostic Marker; Proteins; Radiation; Radiation Oncology; Radiation Therapy Oncology Group; Resistance; Resources; Risk; Sampling; Serum; Signal Pathway; Signal Transduction; Specimen; Stratification; Survivors; System; Time; Tissue Banking; Tissue Banks; Tissues; Translational Research; United States National Institutes of Health; Universities; Update; Urine; base; biobank; chemotherapy; improved; neuropathology; oncology; patient population; phase 3 study; professor; prognostic; radiation resistance; temozolomide; tumor; tumor progression

DESCRIPTION (provided by applicant): Glioblastomas (GBMs) remain among the most devastating of all known human tumors, with median survival times remaining around 12-15 months from initial diagnosis. The introduction of temozolomide chemotherapy, when used concurrently and adjuvantly with radiation, has been shown to significantly improve median survival times and increase the percentage of longer-term GBM survivors. The Radiation Therapy Oncology Group (RTOG), which is one of the largest and most established cooperative groups in oncology, has developed a recursive partitioning analysis (RPA) model for malignant glioma patients, using primarily clinical and demographic variables to stratify malignant glioma patients into one of six distinct prognostic classification groups. The RTOG RPA has long been considered the international "gold standard" as a prognostic model for GBM patients. However, since the original RTOG RPA was developed in the 1990's, two major developments have transpired. First, there has been a rapid advancement in the understanding of the molecular, genetic, and epigenetic mechanisms underlying the pathophysiology and the observed treatment resistance of GBMs, with single institution and limited cooperative group data suggesting that a subset of these biomarkers could serve as useful prognostic markers in GBM. Second, there has been a shift in the adjuvant treatment paradigm of GBMs away from radiation alone (when the original RTOG RPA model was developed) to radiation combined with concurrent and adjuvant temozolomide. Therefore, given these two paradigm shifts, it becomes essential to refine and/or redevelop an RTOG RPA model that is updated along these lines. It is our hypothesis that inclusion of these promising biomarkers will serve to significantly refine the existing RTOG RPA classification model to establish distinct prognostic groups of GBM patients treated in the TMZ era, based on a combination of molecular and clinical variables. The revised RTOG RPA resulting from the proposed effort may be universally used to determine patient eligibility in future clinical trials, as well as to provide guidance with regards to future directions for molecularly-based targeted therapies for GBM patients. The revised RTOG RPA model can be used to establish the "gold standard" expected outcomes for various the prognostic groups of GBM against which the results from clinical trials involving investigational therapies can be compared, much like its decade's old RTOG RPA predecessor model. Therefore, this proposed endeavor is of the utmost importance and relevance for this patient population and will be universally utilized in the international brain tumor community. With regards to methodology, this proposal represents a joint effort between the RTOG and the laboratories of Arnab Chakravarti, MD, Chair and Professor of Radiation Oncology at the Arthur G. James Comprehensive Cancer Center of the Ohio State University and Kenneth Aldape, MD, Professor of Neuropathology at the MD Anderson Cancer Center. Drs. Chakravarti and Aldape are Chair and Co-Chair of the RTOG Brain Tumor Translational Research Group, respectively. Our strategy will be to utilize biorepository specimens from the recently completed RTOG 0525 to accomplish our stated objectives. RTOG 0525 was a Phase III Study conducted in North America, Europe, and Asia comparing dose-dense versus standard dose TMZ when combined with radiation for newly-diagnosed GBM. Tissue blocks were prospectively collected on each and every one of the 1173 GBM patients enrolled on this RTOG study, which have been made available for our NIH challenge grant effort. We will revise the existing RTOG RPA classification model to include not only clinical/demographic variables, but also key molecular, genetic, and epigenetic variables. To this end, we shall validate key signal transduction biomarkers, genetic, and epigenetic markers that have been previously shown to be of prognostic value in smaller GBM studies by our group and others. This data will be combined with the clinical and demographic data previously found to be of importance in the previous RTOG RPA model to generate a revised RPA classification model pertinent to TMZ-treated GBM patients and one that is refined to include molecular, genetic, and epigenetic data of significance.

描述（由申请人提供）：胶质母细胞瘤（GBM）仍然是所有已知人类肿瘤中最具破坏性的肿瘤之一，从最初诊断开始，中位生存时间约为12-15个月。替莫唑胺化疗的引入，当与放疗同时使用时，已被证明可显着改善中位生存时间，并增加长期GBM存活者的百分比。放射治疗肿瘤学小组（RTOG）是肿瘤学领域最大、最成熟的合作小组之一，它已经开发了一种针对恶性神经胶质瘤患者的递归划分分析（RPA）模型，主要使用临床和人口统计学变量将恶性神经胶质瘤患者分层为六个不同的预后分类组之一。RTOG RPA长期以来被认为是GBM患者预后模型的国际“金标准”。然而，自从最初的RTOG RPA在20世纪90年代开发以来，已经发生了两个主要的发展。首先，在理解GBM的病理生理学和观察到的治疗抗性的分子、遗传和表观遗传机制方面取得了快速进展，单个机构和有限的合作组数据表明这些生物标志物的子集可以作为GBM中有用的预后标志物。其次，GBM的辅助治疗模式从单独放疗（当开发原始RTOG RPA模型时）转变为放疗联合同时和辅助替莫唑胺。因此，考虑到这两种模式的转变，有必要完善和/或重新开发一个RTOG RPA模型，该模型将沿着这些路线进行更新。我们的假设是，纳入这些有前途的生物标志物将有助于显着完善现有的RTOG RPA分类模型，以建立不同的预后组的GBM患者在TMZ时代，基于分子和临床变量的组合。修订后的RTOG RPA可以普遍用于确定未来临床试验中的患者资格，并为GBM患者的分子靶向治疗提供指导。修订后的RTOG RPA模型可用于为GBM的各种预后组建立“金标准”预期结果，可以将涉及研究性治疗的临床试验结果与之进行比较，就像其十年前的RTOG RPA前身模型一样。因此，这项提议的奋进对于该患者人群具有极其重要的意义和相关性，并将在国际脑肿瘤界普遍使用。 关于方法学，该提案代表了RTOG与亚瑟G.俄亥俄州州立大学的詹姆斯综合癌症中心和医学博士肯尼斯·阿尔达普，医学博士，医学博士安德森癌症中心的神经病理学教授。Chakravarti博士和Aldape博士分别是RTOG脑肿瘤转化研究小组的主席和联合主席。我们的策略是利用最近完成的RTOG 0525中的生物保藏标本来实现我们的既定目标。RTOG 0525是一项在北美、欧洲和亚洲进行的III期研究，比较了剂量密集型TMZ与标准剂量TMZ联合放射治疗新诊断的GBM。前瞻性地收集了1173例参加RTOG研究的GBM患者的每一个组织块，这些组织块已用于我们的NIH挑战资助计划。我们将修改现有的RTOG RPA分类模型，不仅包括临床/人口统计学变量，还包括关键的分子，遗传和表观遗传变量。为此，我们将验证关键的信号转导生物标志物，遗传和表观遗传标记物，这些标记物先前已被证明在我们小组和其他人的较小GBM研究中具有预后价值。该数据将与先前发现在先前RTOG RPA模型中具有重要性的临床和人口统计学数据相结合，以生成与TMZ治疗的GBM患者相关的修订的RPA分类模型，并且该模型经过改进以包括具有意义的分子、遗传和表观遗传数据。