Count Me In: Partnering with patients to define the clinical and genomic landscape of rare aggressive sarcomas in children and adults

骨肉瘤（OS）和平滑肌肉瘤（LMS）是非常罕见的癌症，都是肉瘤的亚型， 分别出现在骨骼和平滑肌中。一直未能提高存活率或减少 由于基因组图谱表征不足，OS/LMS中的治疗相关发病率， 缺乏有针对性的治疗方法、诊断方法和预防策略。目前迫切 需要在OS和LMS中建立一个大型的临床和基因组数据共享数据库。然而，由于罕见的 这些肿瘤类型以及患者招募和这些肿瘤的基因组表征中的其他挑战， 肿瘤，到目前为止，很难产生这些数据。本提案的总体目标是， 以OS和LMS为合作伙伴的成人和儿科参与者， 基因组、分子和患者报告的数据。这将加速推动新疗法的发现 新的临床试验和新的护理标准。Count Me In PE-CGS U2 C研究中心 利用我们在患者参与、基因组表征、计算分析和 行为研究，以创建和启动两个患者合作项目，以产生这种临床基因组学 数据我们将建立两个网站与病人在OS和LMS社区-骨肉瘤项目 （OSproject）和平滑肌肉瘤项目（LMS project）-并在整个研究过程中同意了3，000名患者。 study.我们将收集医疗记录，病人报告的数据，存档的肿瘤组织样本，以及唾液和血液 用于基因组分析我们将从至少750个肿瘤标本中生成临床注释的基因组数据， 500份循环肿瘤DNA标本和相应的生殖系标本，共享去识别化数据 广泛地。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各种识字水平、年龄和 发展阶段。为了实现这些目标，我们将建立一个完善的跨学科团队， 布罗德研究所和丹娜-法伯癌症研究所的成员都是这些方法的先驱。我们 领导层（Wagle，Janeway）和单位由患者合作癌症研究的专家组成（Wagle， 画家），肉瘤临床和转化研究（珍妮韦，乔治，克朗普顿，劳特），基因组 表征、分析和临床解释（Gabriel、Getz、货车艾伦、Wagle、Janeway）， 计算生物学/数据科学（Getz，货车艾伦，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，将其整合到一个全面的 数据库的目标是加速研究和改善这些患者的生活。为此，我们还 目的是提出一个可以广泛传播和应用的患者合作研究的一般方法 to other tumors肿瘤types类型and patient患者community社区.

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.