Creation of a knowledgebase of high quality assertions of the clinical actionability of somatic variants in cancer

项目摘要 解释体细胞变异在癌症中的临床意义仍然是癌症的主要挑战 诊断、预后和治疗预测。临床基因组资源(Clingen)已建立 广泛的基础设施，包括工具、Web资源、程序和专家小组模板，以提供帮助 专家团体确立了基因和变异的临床相关性。然而，克莱根的努力是 几乎完全集中于对生殖系变异及其在可遗传表型中的作用的解释， 在癌症的体细胞变异的临床解释上留下了很大的空白。同时，全球联盟 美国健康基因组学协会(GA4GH)已经开始制定基因组数据互操作性的标准。这个 癌症变异的临床解释(公民)资源提供了复杂的变异知识 管理界面。在此应用程序中，我们建议创建高质量断言的知识库 体细胞变异在癌症中的临床意义利用公民平台，适应程序 坚持体细胞变异解释，并执行GA4GH的互操作性标准。这 需要努力使涉及体细胞癌变体的研究和临床翻译能够广泛开展 与致瘤性、诊断、预后和治疗反应有关的知识。通过调整 Clingen生殖系模型，我们将建立与专家社区接触的程序，并促进 建立体细胞癌变异治疗专家小组(SC-VCEP)。这些SC-VCEP的形成将 支持创建临床癌症变种断言的Clingen躯体知识库，并 经专家批准。SC-VCEP将是管理和特定领域指南创建的主要驱动因素。 我们将采用并指导正在进行的几个新兴标准的开发，使可查找的、 基因组知识共享的可获得性、互操作性和可重复使用(公平)原则。具体来说，我们将 采用GA4GH变异表示规范(VRS)和相关基因组知识 GA4GH基因组知识标准(GKS)工作流框架。我们还将使用我们的 专家驱动的管理活动，以告知和制定管理和最低限度的信息标准。最后，我们 将使用自然语言处理(NLP)来加速一组定义的人类知识管理任务，这些任务 目前限制了人类管理的速度。具体地说，NLP将用于(1)简化馆长活动 通过将文本挖掘的数据直接整合到CITAL中；(2)根据可能的证据对论文进行优先排序 例如临床试验或病例报告；(3)识别和匹配更多种类的癌症变异类型 通过不同的层次结构系统；以及(4)自动执行简单但耗时的任务，例如 一致的同义词用法。我们的最终目标是支持一个庞大的特定领域专家小组社区 共同努力创建癌症变异及其临床相关性的公共知识库。

Project Summary Interpretation of the clinical significance of somatic variants in cancer remains a major challenge in cancer diagnosis, prognosis and treatment prediction. The Clinical Genome Resource (ClinGen) has established extensive infrastructure including tools, web resources, procedures, and expert panel templates to help communities of experts establish the clinical relevance of genes and variants. However, ClinGen’s effort is almost exclusively focused on the interpretation of germline variants and their role in heritable phenotypes, leaving a significant gap in clinical interpretation of somatic variants in cancer. Concurrently the Global Alliance for Genomics in Health (GA4GH) has begun to develop standards for genomic data interoperability. The Clinical Interpretation of Variants in Cancer (CIViC) resource provides a sophisticated variant knowledge curation interface. In this application, we propose to create a knowledgebase of high quality assertions of the clinical significance of somatic variants in cancer that utilizes the CIViC platform, adapts the procedures of ClinGen to somatic variant interpretation and implements the interoperability standards of the GA4GH. This effort is needed to broadly enable research and clinical translation involving the use of somatic cancer variant knowledge as it relates to oncogenicity, diagnosis, prognosis and therapeutic response. By adapting the ClinGen germline model, we will establish processes to engage the expert community and facilitate the creation of Somatic Cancer Variant Curation Expert Panels (SC-VCEPs). Formation of these SC-VCEPs will support creation of a ClinGen Somatic Knowledgebase of clinical cancer variant assertions curated and approved by experts. SC-VCEPs will be the primary drivers of curation and domain specific guideline creation. We will adopt and guide ongoing development of several emerging standards that enable the Findable, Accessible, Interoperable, and Reusable (FAIR) principles for genomic knowledge sharing. Specifically, we will adopt the GA4GH Variation Representation Specification (VRS) and associated genomic knowledge framework of the GA4GH Genomic Knowledge Standards (GKS) Work Stream. We will also use our expert-driven curation activities to inform and develop curation and minimal information standards. Finally, we will use natural language processing (NLP) to accelerate a set of defined human knowledge curation tasks that currently limit the rate of human curation. Specifically, NLP will be used to (1) streamline curator activities through integration of text-mined data directly into CIViC; (2) prioritize papers based on their likely evidence level such as clinical trials or case reports; (3) identify and match a larger variety of cancer variant types through a variant hierarchy system; and (4) automate simple but time-consuming tasks such as enforcing consistent synonym usage. Our ultimate goal is to support a large community of domain-specific expert panels working together to create a public knowledgebase of cancer variants and their clinical relevance.