Cancer Immunologic Data Commons (CIDC) Supplement Request

摘要 癌症免疫疗法已经成为治疗癌症患者的非常有希望的方法，特别是 因为它们可以应用于不同的组织和癌症类型，尽管临床疗效有限 癌症患者的子集1。以生物标志物为重点的翻译研究对 了解肿瘤免疫界面。尽管许多用于肿瘤和免疫分析的技术 被应用于NCI赞助的免疫治疗试验，测试方案和数据分析的标准化 方法对于生物标志物鉴定研究的数据整合和比较是至关重要的2。这 强调需要统一数据和建立统一的分析管道。 我们建议继续发展达纳-法伯癌症免疫数据共享中心(CIDC) 癌症研究所的目标是使用生物标记物来推动翻译研究努力，以帮助进一步 癌症免疫治疗的进展。此应用程序的短期目标是建立和 管理生物标记物和相关临床数据的数据库，用于癌症免疫监测和 分析中心(CIMAC)，并为综合多维分析提供信息学环境 通过不同的研究和存储产生的数据。具体地说，我们建议：目标1，与 CIMAC和实验室协调委员会(LCC)协调建立检测方案和数据格式 标准；目标2，开发集中数据存储库和管理系统，并协调CIMAC数据 提交给CIDC；目标3，开发统一的生物信息学处理管道和计算 为CIMAC和更大的研究界进行计算密集型分析的基础设施；目的 4、提供生物信息学算法，实现对CIMAC数据的综合分析和关联分析 用于发现生物标记物的其他可访问的数据库和资源；目标5，开发基于角色的集中数据 使用高级编程接口访问功能，以实现CIMAC数据共享；目标6，开发 交互式网络可视化功能，使调查人员和免疫学社区能够检查 CIMAC数据；以及目标7，在CIMAC-CIDC网络内协调物流和科学活动 生物标记物的发现和验证。 最后，我们将为以下所有数据和结果建立一个生物标记库 CIMAC，辅以标准化的信息学工具，以便与其他可访问的数据库相结合； 并兼容外部研究人员的数据贡献和二次分析。这些努力将 为CIMACs-CIDC网络提供生物信息学支持。已建立的数据共享中心还将 为更大的研究社区提供未来的免疫肿瘤学数据资源。

ABSTRACT Cancer immunotherapies have emerged as highly promising approaches to treat cancer patients, particularly since they can be applied across different tissue and cancer types, although clinical efficacy has been limited to a subset of cancer patients1. Translational studies with strong focus on biomarkers are critical to understanding the tumor-immune interface. Although numerous technologies for tumor and immune profiling are applied to NCI sponsored immunotherapy trials, standardization of both assay protocols and data analysis methods is crucial to data integration and comparisons across studies for biomarker identification2. This underlines the need for data harmonization and creation of uniform analysis pipelines. We propose to continue development of the Cancer Immunology Data Commons (CIDC) at the Dana-Farber Cancer Institute with the goal of advancing translational research efforts using biomarkers to aid in the further development of cancer immunotherapy. The short-term objectives of this application are to establish and manage the data repository for biomarkers and associated clinical data for Cancer Immune Monitoring and Analysis Centers (CIMACs), and provide an informatics environment for integrative multidimensional analysis across different studies and storage of data generated. Specifically, we propose to: Aim 1, coordinate with the CIMAC and Laboratory Coordinating Committee (LCC) to harmonize establish assay protocols and data format standards; Aim 2, develop a centralized data repository and management system, and coordinate CIMAC data submission to the CIDC; Aim 3, develop uniform bioinformatics processing pipelines and computing infrastructure for computationally intensive analyses for the CIMACs and the larger research community; Aim 4, provide bioinformatics algorithms to enable integrative and correlative analysis of CIMAC data and integrate other accessible databases and resources for biomarker discovery; Aim 5, develop centralized role-based data access functions with advanced programming interface to enable sharing of CIMAC data; Aim 6, develop interactive web visualization functions to enable investigators and the immunology communities to examine the CIMAC data; and Aim 7, coordinate within the CIMACs-CIDC Network logistic and scientific activities for biomarker discovery and validation. At the conclusion, we will have established a biomarker repository for all data and results generated by CIMACs, supplemented with standardized informatics tools for integration with other accessible databases, and compatible for data contribution and secondary analyses by external researchers. These efforts will provide bioinformatics support for the CIMACs-CIDC Network. The established Data Commons will also provide the foundation for a future immuno-oncology data resource for the larger research community.