Center for Precision Medicine in Leukemia (CPML)

白血病精准医学中心 (CPML)

• 批准号: 9543196
• 负责人: Mignon Lee-Cheun Loh
• 金额: $ 9.63万
• 依托单位: ST. JUDE CHILDREN'S RESEARCH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9543196
• 关键词: Acute Lymphocytic Leukemia; Address; Adult; Adult Acute Lymphocytic Leukemia; Adverse drug effect; Adverse effects; Asthma; Autoimmune Process; Bioinformatics; Biometry; Biostatistics Core; Bone necrosis; Cells; Child; Childhood; Childhood Acute Lymphocytic Leukemia; Clinical; Clinical Pharmacology; Clinical Trials; Collaborations; Common Neoplasm; Complement; Computational Biology; Coupled; DNA; Data; Data Analyses; Deposition; Diagnosis; Diagnostic; Disease; Drug resistance; Enrollment; Ensure; Epigenetic Process; Foundations; Genetic; Genome; Genomics; Glucocorticoids; Goals; Hepatotoxicity; Inflammatory; Inherited; International; Intervention; Knowledge; Laboratories; Leadership; Life; Malignant Neoplasms; Methods; Methotrexate; Modeling; Molecular; Neuropathy; Non-Malignant; Outcome; Pancreatitis; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacogenomics; Pharmacotherapy; Phenotype; Publications; Quality of life; Regimen; Relapse; Research; Research Personnel; Residual Neoplasm; Sampling; Somatic Cell; Source; Standardization; System; Testing; Tissues; Toxic effect; Translating; Translations; Treatment Failure; Treatment-related toxicity; Variant; acquired drug resistance; antileukemic agent; chemotherapy; clinical diagnostics; curative treatments; drug sensitivity; epigenomics; genome-wide; genomic data; genomic variation; human genomics; interpatient variability; leukemia; multidisciplinary; neoplastic cell; non-genetic; non-genomic; novel therapeutics; outcome forecast; precision medicine; prevent; prognostic; programs; prospective; public health relevance; response; stem; success; synergism; thiopurine; transcriptomics; treatment response; tumor

 DESCRIPTION (provided by applicant): Building on our success as world leaders in acute lymphoblastic leukemia (ALL) and as leaders in the Pharmacogenomics Research Network (PGRN), we have formed a Center for Precision Medicine in Leukemia. Our goal is to identify the mechanisms underlying interpatient variability in response to antileukemia medications. We will integrate state-of-the-art genomic, transcriptomic, and epigenomic interrogation of somatic cell ALL tumor cells, host germline DNA variation, and comprehensive assessment of treatment variables and non-genetic features in children and adults with ALL, coupled with laboratory mechanistic studies, to identify sources and mechanisms of interpatient variation in response. Many ALL medications are also used to treat other pediatric and adult cancers and also nonmalignant diseases: for example, glucocorticoids, methotrexate, and thiopurines are commonly used for nonmalignant diseases such as asthma, autoimmune, and inflammatory diseases, and so ALL can serve as a model for how to optimize use of therapy that will have broad implications beyond ALL. Our investigators include leaders in adult and childhood ALL, pharmacogenomics, human genomics, clinical pharmacology, computational biology, bioinformatics, and biostatistics. We have three major aims, addressed in three highly integrated projects (all of which capitalize on front-line ALL clinical trials) and three Center cores. In Proect 1, we will define the landscape of genome variation among ALL subtypes and identify the inherited and somatically acquired genomic variation, along with other clinical features, that are associated with ALL treatment response in patients. In Project 2, we will identify the genome variation associated with de novo and acquired drug resistance in primary ALL cells from patients at diagnosis and at relapse, and will elucidate mechanisms by which genomic variation influences drug resistance and treatment response. In Project 3, we will identify genomic variation associated with specific serious adverse effects of antileukemic agents (osteonecrosis, hepatotoxicity, pancreatitis, and neuropathy), establishing mechanisms and testing interventions for the phenotype of osteonecrosis. Synergies in the Center stem from the substantial overlap in patients and genomic data among the three projects; the complementary expertise and prior collaborations among investigators; the leadership of our Administrative Core with extensive ties to existing pharmacogenomic, genomic, and clinical cancer networks; and uniform approaches to data analysis, management, integration, and deposition provided by our Cores. Our Center's overarching aim is to use the knowledge gained from the research in the three projects to build a comprehensive precision medicine approach to minimize relapse while also minimizing adverse effects. This Center will allow us to engage additional adult ALL and genomics collaborators, accelerate progress in the discovery and translation of genomics into more effective and less toxic treatments, and provide a paradigm for other diseases for the integration of genomic methods and knowledge into precision medicine.

 描述（由申请人提供）：基于我们作为急性淋巴细胞白血病 (ALL) 领域的世界领导者和药物基因组学研究网络 (PGRN) 领导者的成功，我们成立了白血病精准医学中心。我们的目标是确定患者抗白血病药物反应差异的潜在机制。我们将整合最先进的体细胞ALL肿瘤细胞的基因组学、转录组学和表观基因组学研究、宿主种系DNA变异、对患有ALL的儿童和成人的治疗变量和非遗传特征的综合评估，再加上实验室机制研究，以确定患者间反应变异的来源和机制。许多 ALL 药物还用于治疗其他儿童和成人癌症以及非恶性疾病：例如，糖皮质激素、甲氨蝶呤和硫嘌呤通常用于治疗哮喘、自身免疫性疾病和炎症性疾病等非恶性疾病，因此 ALL 可以作为如何优化治疗使用的模型，这将在 ALL 之外产生广泛的影响。我们的研究人员包括成人和儿童 ALL、药物基因组学、人类基因组学、临床药理学、计算生物学、生物信息学和生物统计学领域的领导者。我们有三个主要目标，通过三个高度集成的项目（所有这些项目都利用一线 ALL 临床试验）和三个中心核心来实现。在项目 1 中，我们将定义 ALL 亚型之间的基因组变异概况，并确定遗传性和体细胞获得性基因组变异，以及与患者 ALL 治疗反应相关的其他临床特征。在项目 2 中，我们将鉴定与诊断时和复发时患者的原代 ALL 细胞中与新生和获得性耐药相关的基因组变异，并将阐明基因组变异影响耐药性和治疗反应的机制。在项目3中，我们将确定与抗白血病药物的特定严重不良反应（骨坏死、肝毒性、胰腺炎和神经病变）相关的基因组变异，建立骨坏死表型的机制并测试干预措施。该中心的协同效应源于三个项目之间患者和基因组数据的大量重叠；研究人员之间互补的专业知识和先前的合作；我们的行政核心的领导力与现有的药物基因组学、基因组学和临床癌症网络有着广泛的联系；我们的核心提供统一的数据分析、管理、集成和存储方法。我们中心的总体目标是利用从三个项目的研究中获得的知识来建立全面的精准医学方法，以最大限度地减少复发，同时也最大限度地减少不良反应。该中心将使我们能够吸引更多的成人 ALL 和基因组学合作者，加速基因组学的发现和转化为更有效、毒性更小的治疗方法的进展，并为其他疾病提供一个范例，将基因组方法和知识整合到精准医学中。