Standardized and Genome-Wide Clinical Interpretation of Complex Genotypes for Cancer Precision Medicine

癌症精准医学复杂基因型的标准化和全基因组临床解释

• 批准号: 10370336
• 负责人: Obi L. Griffith
• 金额: $ 71.94万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-02 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10370336
• 关键词: Address; Adopted; Adoption; Biological; Biological Assay; Biological Markers; CLIA certified; Client; ClinVar; Clinical; Code; Collaborations; Communities; Community Outreach; Complex; Cytogenetics; Data; Databases; Development; Documentation; Education and Outreach; Educational workshop; FDA approved; Freezing; Generations; Genetic; Genome; Genomics; Genotype; Growth; Guidelines; Immunotherapy; Informatics; International; Internet; Internships; Knowledge; Licensing; Malignant Neoplasms; Measures; Medical Genetics; Methods; Molecular; Molecular Profiling; Mutation; Oncogenic; Oncology; Patient-Focused Outcomes; Patients; Phenotype; Public Domains; Pythons; Reporting; Research; Research Personnel; Sampling; Standardization; Technology; Testing; Training; Variant; base; cBioPortal; cancer genomics; clinical application; clinical decision-making; clinically relevant; clinically significant; community engagement; cost; crowdsourcing; data modeling; data standards; epigenome; experimental study; genome sequencing; genome-wide; hackathon; health care settings; high throughput screening; improved; interoperability; knowledge curation; knowledge repository; knowledgebase; meetings; molecular pathology; next generation; novel; open source; outreach; portability; precision medicine; precision oncology; prediction algorithm; response; software development; targeted sequencing; targeted treatment; tool; transcriptome; tumor; tumor heterogeneity; usability; user-friendly; whole genome; working group

Project Summary/Abstract High-throughput molecular profiling technologies have allowed the systematic identification of molecular drivers of cancer for most major tumor types. Clinical and functional studies have correlated these drivers with patient outcomes and helped develop targeted therapies. However, maintaining current and comprehensive interpretations of the clinical significance of variants represents a major bottleneck. To address this challenge, the Clinical Interpretations of Variants in Cancer knowledgebase (CIViC; ​civicdb.org​) was created to provide a knowledge repository and sophisticated curation interface for expert-crowdsourcing the curation of actionable cancer variants. Importantly, all data are made freely available with a public domain license, daily and monthly data freezes, and public API. This has allowed widespread adoption of CIViC variant interpretations into many research tools for variant annotation as well as commercial and non-commercial report generation workflows. To date, these have focused predominantly on small mutations, detected through targeted sequencing panels, and assumed a single-target-to-single-therapy paradigm. As sequencing costs decrease, whole genome, transcriptome, and epigenome approaches will replace these targeted methods. This will allow increasingly unbiased assay of molecular alterations of most types (large and small) and will simultaneously replace many traditional cytogenetic assays. It will also dramatically increase the number of variants of potential and unknown clinical significance. Furthermore, our understanding has evolved to recognize that spatial and temporal tumor heterogeneity result in complex tumor genotypes of collaborating mutations that will require a more sophisticated decision support framework. To address these challenges, the CIViC data model will be extended to support: new frameworks for representing complex tumor genotypes; ACMG and AMP guidelines for both germline and somatic variant curation; and new evidence codes for assessing somatic variant oncogenicity. New user interfaces will be developed to support curation, browsing and searching of these features. Clinical collaborations will be extended to: (a) develop a distributable clinical-grade (CLIA-certified) analysis platform for comprehensive genomic profiling of patient samples using whole-genome sequencing; (b) support standardized somatic variant curation through the ClinGen Somatic Working group; and (c) integrate CIViC reports into the Personalized Oncogenomics (POG) trial. The proposal will address several key challenges including: 1) understanding the importance of integrating germline annotations with somatic cancer variant interpretations; 2) determining if a whole genome approach can replace existing targeted sequencing panels and cytogenetic assays; and 3) assessing the impact of a public variant interpretation knowledgebase on clinical decisions at molecular tumor board meetings. Finally, community outreach and training will be performed to develop online workshops, improve internship opportunities, and increase interaction with medical genetics fellows to train the next-generation of researchers in precision medicine informatics.

项目摘要/摘要 高通量分子分析技术允许系统识别分子驱动器 大多数主要肿瘤类型的癌症。临床和功能研究已将这些驱动因素与患者相关 结果并帮助开发有针对性的疗法。但是，保持当前和全面 对变体的临床意义的解释代表了主要的瓶颈。为了应对这个挑战， 创建了癌症知识库中变体的临床解释 知识存储库和精致的策划界面，用于专家杂交的策划 癌症变体。重要的是，所有数据均通过公共领域许可，每日和每月免费提供 数据冻结和公共API。这使得广泛采用公民变体解释为许多 用于变异注释以及商业和非商业报告生成工作流程的研究工具。 迄今 并假设单一靶向单向治疗范式。随着测序成本的降低，整个基因组， 转录组和表观基因组方法将取代这些目标方法。这将越来越多 对大多数类型（大小）分子改变的无偏评估，只会取代许多类型 传统的细胞遗传学评估。它还将大大增加潜力变体的数量和 未知的临床意义。此外，我们的理解已经发展为认识到这个空间和 临时肿瘤异质性导致协作突变的复杂肿瘤基因型，这将需要 更复杂的决策支持框架。为了应对这些挑战，公民数据模型将是 扩展到支持：代表复杂肿瘤基因型的新框架； ACMG和AMP指南 对于种系和体细胞变体策展；以及评估躯体变体的新证据代码 致癌性。将开发新的用户界面以支持策划，浏览和搜索这些 特征。临床合作将扩展到：（a）开发可分布的临床级（CLIA认证） 使用全基因组测序对患者样品进行全面基因组分析的分析平台； （b） 通过克林根躯体工作组支持标准化的体细胞变体策展； （c）整合 公民报告了个性化的致癌基因组学（POG）试验。该提案将解决几个关键 挑战包括：1）了解将种系注释与体癌融为一体的重要性 变体解释； 2）确定整个基因组方法是否可以替代现有的目标测序 面板和细胞遗传学评估； 3）评估公共变体解释知识库的影响 关于分子肿瘤板会议的临床决策。最后，社区宣传和培训将是 表演以开发在线研讨会，改善实习机会并增加与 医学遗传学家伙在精密医学信息中培训下一代研究人员。