Data Processing, Analysis and Modeling Unit

数据处理、分析和建模单元

• 批准号: 10005918
• 负责人: Jeremy Goecks
• 金额: $ 67.21万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-19 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005918
• 关键词: 3-Dimensional; ATAC-seq; Aftercare; Atlases; Biological; Biological Assay; Biological Process; Biopsy; CDK4 gene; Cancer Patient; Cells; Characteristics; Communities; Computer software; Data; Data Analyses; Data Management Resources; Data Storage and Retrieval; Disseminated Malignant Neoplasm; Electron Microscopy; Generations; Genes; Goals; Image; Image Analysis; Immune; Immune checkpoint inhibitor; Immunofluorescence Immunologic; Immunohistochemistry; Immunomodulators; Individual; Infiltration; Malignant Neoplasms; Malignant neoplasm of prostate; Maps; Measurement; Metastatic breast cancer; Methods; Modeling; Mutation; Neoplasm Metastasis; Pathway interactions; Patients; Periodicity; Population; Primary Neoplasm; Reproducibility; Research; Resistance; Resistance development; Running; Sampling; Services; Standardization; Statistical Data Interpretation; Structure; System; Techniques; Time; Tissues; Visualization; Visualization software; animation; base; blood vessel development; castration resistant prostate cancer; cohort; computerized data processing; dashboard; data management; epigenomics; hormone receptor-positive; hormone therapy; immune checkpoint; indexing; individual patient; inhibitor/antagonist; malignant breast neoplasm; molecular imaging; molecular targeted therapies; multimodal data; multimodality; novel; prospective; resistance mechanism; single cell sequencing; statistical and machine learning; targeted treatment; therapy resistant; triple-negative invasive breast carcinoma; tumor

ABSTRACT – Data Analysis Unit We propose to create a Data Analysis Unit in service of the Omics and Multidimensional Spatial (OMS) Atlas. The OMS Atlas will enable discovery of mechanisms of resistance that arise in individual patients with metastatic breast and prostate cancer during treatment with current generation of targeted therapeutic combinations and immune checkpoint inhibitors. Treatment will these therapies in metastatic cancer is rarely effective for an extended period of time, and understanding the mechanisms by which these cancers become resistant to therapy is the primary goal of the OMS Atlas. The Data Analysis Unit will support this goal by developing and deploying data management, processing, analysis, and visualization methods and software to create the Atlas. The OMS Atlas will collect two biopsies, one before treatment and one during treatment for 3 different cohorts of cancer patients. The final product of the Data Analysis Unit will be a complete tumor atlas accessible via an interactive portal that enables use-case biologists in the OMS Atlas, the HTAN and the larger research community to develop hypotheses about tumor resistance mechanisms through quantified, longitudinal, and spatially-resolved comparisons of pre- and on/post-treatment biopsies from individual patients. Using primary data generated from omics and imaging assays (Tier 1 data), the Data Analysis Unit will generate three additional tiers of data: (Tier 2) single gene/cell measurements obtained by processing data from a single data platform; (Tier 3) tumor maps generated by combining single-cell and spatially-resolved omics and imaging data as well as quantification of systems-level functions such as biological pathway activity and the cells comprising the tumor and its surrounding tissue using integrative analyses of multiple data platforms; (Tier 4) a tumor atlas that can be used to compare pre- and on/post-treatment biopsies and identify features potentially correlated with resistance to treatment. Data tiers will be generated using a robust software pipeline consisting of a data management system, image management software, a workflow execution system, and visualization tools. Standardized and reproducible workflows that run on this platform will be implemented to generate all tiers of data. Statistical and machine learning approaches will be used to create tumor maps by connecting mirror image sections and cell populations across different assays. The OMS Atlas portal will provide a single interface with access to 10 different visualizations of tumor maps. Tumor maps can be visualized and compared longitudinally within a single patient or laterally across patients. Many visualizations can be displayed simultaneously using a dashboard approach where visualizations can be progressively added as desired, making it possible to view many different types of data about tumor maps simultaneously. Specialized animation approaches and 3D techniques will be used in visualizations to effectively display multidimensional, spatially resolved tumor map data.

摘要 - 数据分析单元 我们建议创建一个数据分析单元，以服务OMIC和多维空间（OMS）地图集。 OMS地图集将能够发现在患有的个别患者中出现的抗药性机制 治疗过程中的转移性乳腺癌和前列腺癌与当前产生的靶向治疗 组合和免疫切除点抑制剂。这些疗法将在转移性癌症中很少 在很长一段时间内有效，并了解这些癌症成为的机制 对治疗的抵抗力是OMS地图集的主要目标。数据分析单元将通过 开发和部署数据管理，处理，分析和可视化方法以及软件 创建地图集。 OMS地图集将收集两次活检，一个在治疗前，一个在治疗期间进行3 癌症患者的不同人群。数据分析单元的最终产品将是一个完整的肿瘤图集 可以通过互动门户访问，该门户可在OMS Atlas，Htan和更大 研究社区通过量化的，关于肿瘤抗性机制的假设 纵向和空间分辨的比较 患者。使用从OMICS和成像测定（第1层数据）生成的主要数据，数据分析单元 将生成三个额外的数据：（第2层）通过处理数据获得的单基因/细胞测量值 来自一个数据平台； （第3层）通过组合单细胞和空间分辨而产生的肿瘤图 OMICS和成像数据以及数量的系统级功能，例如生物途径活动 以及通过多个数据的集成分析来完成肿瘤及其周围组织的细胞 平台； （第4层）可用于比较前后的肿瘤图集 特征可能与对治疗的抗性有关。数据层将使用强大的软件生成 管道由数据管理系统，图像管理软件，工作流执行系统组成， 和可视化工具。将实现在此平台上运行的标准化和可重现的工作流程 生成所有数据层。统计和机器学习方法将用于创建肿瘤图 在不同的测定中连接镜像截面和细胞种群。 OMS Atlas Portal将 提供单个接口，可访问10个不同的肿瘤图可视化。肿瘤图可以是 在单个患者或横向的患者中进行可视化和纵向比较。许多可视化 可以简单地使用仪表板方法显示可视化的仪表板方法 根据需要，可以简单地查看有关肿瘤图的许多不同类型的数据。 专门的动画方法和3D技术将用于可视化以有效显示 多维，空间分辨的肿瘤图数据。