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 (GBM) 仍然是所有已知人类肿瘤中最具破坏性的一种，从初次诊断起中位生存时间约为 12-15 个月。替莫唑胺化疗与放疗同时辅助使用时，已被证明可以显着改善中位生存时间并增加长期 GBM 幸存者的百分比。放射治疗肿瘤学组 (RTOG) 是肿瘤学领域最大、最成熟的合作组之一，它开发了一种针对恶性神经胶质瘤患者的递归分区分析 (RPA) 模型，主要使用临床和人口统计学变量将恶性神经胶质瘤患者分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 20 世纪 90 年代开发出最初的 RTOG RPA 以来，已经发生了两项重大进展。首先，对 GBM 病理生理学和观察到的治疗耐药性背后的分子、遗传和表观遗传机制的理解取得了快速进展，单一机构和有限的合作组数据表明，这些生物标志物的一部分可以作为 GBM 的有用预后标志物。其次，GBM 的辅助治疗范式已经从单独放疗（当开发最初的 RTOG RPA 模型时）转向放疗联合同步和辅助替莫唑胺。因此，考虑到这两种范式转变，有必要完善和/或重新开发沿着这些思路更新的 RTOG RPA 模型。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，以根据分子和临床变量的组合，建立 TMZ 时代治疗的 GBM 患者的不同预后组。由拟议工作产生的修订后的 RTOG RPA 可普遍用于确定未来临床试验中患者的资格，并为 GBM 患者基于分子的靶向治疗的未来方向提供指导。修订后的 RTOG RPA 模型可用于为 GBM 的各个预后组建立“黄金标准”预期结果，可以将涉及研究性治疗的临床试验的结果进行比较，就像其十年前的旧 RTOG RPA 前身模型一样。因此，这项提议的努力对于该患者群体具有极其重要的意义和相关性，并将在国际脑肿瘤界得到普遍利用。 在方法方面，该提案代表了 RTOG 与俄亥俄州立大学 Arthur G. James 综合癌症中心放射肿瘤学主席兼教授 Arnab Chakravarti 医学博士和 MD 安德森癌症中心神经病理学教授 Kenneth Aldape 医学博士实验室之间的共同努力。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。我们的策略是利用最近完成的 RTOG 0525 中的生物样本库标本来实现我们既定的目标。 RTOG 0525 是在北美、欧洲和亚洲进行的一项 III 期研究，比较了剂量密集型 TMZ 与标准剂量 TMZ 联合放疗治疗新诊断 GBM 的效果。前瞻性地收集了参与这项 RTOG 研究的 1173 名 GBM 患者的每一位组织块，这些组织块已用于我们的 NIH 挑战拨款工作。我们将修改现有的 RTOG RPA 分类模型，使其不仅包括临床/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、遗传和表观遗传标志物，这些标志物先前在我们小组和其他人的小型 GBM 研究中已被证明具有预后价值。该数据将与之前发现在之前的 RTOG RPA 模型中重要的临床和人口统计数据相结合，生成与 TMZ 治疗的 GBM 患者相关的修订版 RPA 分类模型，并且该模型经过细化​​以包括重要的分子、遗传和表观遗传数据。