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: 7853814
• 负责人: KENNETH D ALDAPE
• 金额: $ 103.65万
• 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 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7853814
• 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; Phase III Clinical Trials; 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; 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（GBMS）仍然是所有已知人类肿瘤中最具破坏性的，中位生存时间在初次诊断后仍有12-15个月左右。当同时和舒适地与辐射一起使用时，替莫唑胺化疗的引入已被证明可显着改善中位生存时间并增加长期GBM幸存者的百分比。放射疗法肿瘤学组（RTOG）是肿瘤学中最大，最成熟的合作组之一，它为恶性神经胶质瘤患者开发了一种递归分区分析（RPA）模型，主要使用临床和人口统计学变量将恶性肿瘤患者分解为六个独特的预后分类组中的一个。长期以来，RTOG RPA一直被认为是国际“黄金标准”作为GBM患者的预后模型。但是，由于最初的RTOG RPA是在1990年代开发的，因此已经进行了两个重大发展。首先，在理解病理生理学和观察到的GBMS耐药性的分子，遗传和表观遗传机制方面，已经有了迅速的进步，具有单个机构和有限的合作组数据，这表明这些生物标志物的子集可以用作GBM中有用的预后标记。其次，GBMS的辅助处理范式从单独的辐射（开发原始RTOG RPA模型）转移到了辐射与并发和辅助替莫唑胺相结合。因此，鉴于这两个范式变化，精炼和/或重建沿这些线路更新的RTOG RPA模型至关重要。我们的假设是，包括这些有希望的生物标志物将有助于明显地完善现有的RTOG RPA分类模型，以建立在TMZ时代治疗的GBM患者的不同预后组，基于分子和临床变量的结合。拟议的努力产生的修订后的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患者的分子基于分子的靶向疗法提供指导。修订后的RTOG RPA模型可用于建立各种GBM预后组的“金标准”预期结果，可以将涉及研究疗法的临床试验的结果进行比较，就像其十年的旧RTOG RTOG RPA RPA的先前模型一样。因此，这项拟议的努力对该患者人群至关重要，并且将普遍使用在国际脑肿瘤界。 关于方法论，该提案代表了RTOG与医学博士Arnab Chakravarti的实验室之间的共同努力，俄亥俄州立大学Arthur G. James综合癌症中心的辐射肿瘤学教授与MD和M.D anderson癌症中心神经病理学教授Kenneth Aldape的Arthur G. James综合癌症中心。博士。 Chakravarti和Aldape分别是RTOG脑肿瘤转化研究小组的主席和联合主席。我们的策略将是利用来自最近完成的RTOG 0525的生物座标本来实现我们既定的目标。 RTOG 0525是一项在北美，欧洲和亚洲进行的III期研究，当与新诊断的GBM的辐射结合使用时，比较了剂量密度与标准剂量TMZ。在此RTOG研究的1173名GBM患者中，每一个都可以预期收集组织块，这些研究已用于我们的NIH挑战赠款工作。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，还包括关键分子，遗传和表观遗传变量。为此，我们将验证我们的小组和其他人在较小的GBM研究中验证以前已证明在较小的GBM研究中已证明其预后价值的钥匙信号转导生物标志物，遗传和表观遗传标记。该数据将与先前发现的临床和人口统计数据相结合，在先前的RTOG RPA模型中很重要，以生成与TMZ处理的GBM患者有关的修订后的RPA分类模型，其中包括分子，遗传和表观遗传数据的意义。