Genome Characterization Unit

基因组表征单位

• 批准号: 10703412
• 负责人: Stacey Gabriel
• 金额: $ 69.39万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10703412
• 关键词: Acceleration; Adult; Age; Back; Behavioral Research; Behavioral Sciences; Biological Assay; Blood; Cancer Center; Caring; Child; Childhood; Clinical; Clinical Data; Clinical Research; Clinical Trials; Collaborations; Communities; Computational Biology; Computer Analysis; Consent; Dana-Farber Cancer Institute; Data; Data Analytics; Data Files; Data Reporting; Data Science; Databases; Development; Diagnostic Procedure; Failure; Family; Funding; Genome; Genomics; Goals; Infrastructure; Leadership; Malignant Neoplasms; Medical Records; Minority; Molecular; Morbidity - disease rate; National Human Genome Research Institute; Participant; Patient Participation; Patient Recruitments; Patients; Prevention strategy; Process; RNA; Reporting; Research; Rural; Saliva; Sampling; Smooth Muscle; Specimen; Survival Rate; The Cancer Genome Atlas; Time; Tissue Sample; Translational Research; Tumor Tissue; analytical tool; anticancer research; bone; cancer genome; cancer genomics; cell free DNA; childhood sarcoma; clinical database; clinically relevant; computerized data processing; data de-identification; exome sequencing; experience; genome sequencing; genomic data; genomic platform; improved; leiomyosarcoma; literacy; member; novel; osteosarcoma; patient engagement; programs; rare cancer; sarcoma; shared database; targeted treatment; tool; transcriptome; treatment strategy; tumor; tumor DNA; web site; whole genome

Osteosarcoma (OS) and leiomyosarcoma (LMS) are exceedingly rare cancers, both subtypes of sarcoma, that arise in bone and smooth muscle respectively. There has been a failure to improve survival rates or decrease treatment-related morbidity in OS/LMS due to insufficient characterization of the genomic landscape, resulting in a lack of targeted therapeutic approaches, diagnostic methods, and preventive strategies. There is an urgent need for a large, shared database of clinical and genomic data in OS and LMS. Yet, because of the rarity of these tumor types as well as other challenges in patient recruitment and the genomic characterization of these tumors, to date it has been difficult to generate this data. The overarching goal of this proposal is to engage adult and pediatric participants with OS and LMS as partners to generate a shared database of clinical, genomic, molecular, and patient-reported data. This should accelerate discoveries that drive novel treatment strategies, new clinical trials, and new standards of care. The Count Me In PE-CGS U2C Research Center will leverage our experience in patient engagement, genome characterization, computational analysis, and behavioral research to create and launch two patient-partnered projects to generate this clinicogenomic data. We will build two websites with patients in the OS and LMS communities—the Osteosarcoma Project (OSproject) and the Leiomyosarcoma Project (LMSproject)—and consent 3,000 patients over the course of the study. We will collect medical records, patient-reported data, archival tumor tissue samples, and saliva and blood for genomic analysis. We will generate clinically annotated genomic data from at least 750 tumor specimens, 500 circulating tumor DNA specimens, and corresponding germline specimens and share the de-identified data widely. At the same time, we will study and optimize the approach to patient engagement in cancer research, particularly among rural and minority participants and participants across a range of literacy levels, ages, and stages in development. To accomplish these goals, we will build on a well-established interdisciplinary team from the Broad Institute and Dana-Farber Cancer Institute with members who have pioneered these approaches. Our leadership (Wagle, Janeway) and Units are comprised of experts in patient-partnered cancer research (Wagle, Painter), sarcoma clinical and translational research (Janeway, George, Crompton, Raut), genome characterization, analysis, and clinical interpretation (Gabriel, Getz, Van Allen, Wagle, Janeway), computational biology/data science (Getz, Van Allen, Philippakis), and behavioral science (Mack, Rebbeck). Our Center will uncover the key clinicogenomic features of OS/LMS, integrate them into a single comprehensive database with a goal of accelerating research and improving the lives of these patients. In doing so, we also aim to present a general approach to patient-partnered research that can be disseminated broadly and applied to other tumors types and patient communities.

骨肉瘤 (OS) 和平滑肌肉瘤 (LMS) 是极其罕见的癌症，都是肉瘤的亚型， 分别出现在骨和平滑肌中。未能提高存活率或降低存活率 由于基因组景观表征不足，导致 OS/LMS 中与治疗相关的发病率，导致 缺乏有针对性的治疗方法、诊断方法和预防策略。有紧急情况 OS 和 LMS 中需要一个大型、共享的临床和基因组数据数据库。但由于其稀缺性 这些肿瘤类型以及患者招募和这些肿瘤的基因组特征方面的其他挑战 肿瘤，迄今为止很难生成这些数据。该提案的总体目标是让 成人和儿科参与者与 OS 和 LMS 作为合作伙伴，生成临床、 基因组、分子和患者报告的数据。这应该会加速推动新疗法的发现 策略、新的临床试验和新的护理标准。 Count Me In PE-CGS U2C 研究中心将 利用我们在患者参与、基因组表征、计算分析和 行为研究创建并启动两个患者合作项目来产生这一临床基因组学 数据。我们将与 OS 和 LMS 社区的患者建立两个网站——骨肉瘤项目 (OSproject) 和平滑肌肉瘤项目 (LMSproject)——并在项目过程中征得 3,000 名患者同意 学习。我们将收集医疗记录、患者报告的数据、档案肿瘤组织样本以及唾液和血液 用于基因组分析。我们将从至少 750 个肿瘤样本中生成临床注释的基因组数据， 500份循环肿瘤DNA标本，以及相应的种系标本并共享去识别化数据 广泛。同时，我们将研究和优化患者参与癌症研究的方法， 特别是在农村和少数民族参与者以及不同识字水平、年龄和年龄的参与者中 发展阶段。为了实现这些目标，我们将建立一支完善的跨学科团队 Broad Institute 和 Dana-Farber Cancer Institute 的成员都是这些方法的先驱。我们的 领导层（Wagle、Janeway）和各单位由患者合作癌症研究领域的专家（Wagle、 Painter）、肉瘤临床和转化研究（Janeway、George、Crompton、Raut）、基因组 表征、分析和临床解释（Gabriel、Getz、Van Allen、Wagle、Janeway）， 计算生物学/数据科学（Getz、Van Allen、Philippakis）和行为科学（Mack、Rebbeck）。 我们的中心将揭示 OS/LMS 的关键临床基因组学特征，并将它们整合到一个综合的 数据库的目标是加速研究并改善这些患者的生活。在此过程中，我们还 旨在提出一种可以广泛传播和应用的患者合作研究的通用方法 其他肿瘤类型和患者群体。