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前途的方法，特别是 由于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 癌症患者的一个子集1。重点关注生物标志物的转化研究对于 了解肿瘤免疫界面。尽管许多肿瘤和免疫分析技术 应用于NCI赞助的免疫治疗试验，标准化测定方案和数据分析 方法对于生物标志物鉴定研究的数据整合和比较至关重要2。这 强调需要统一数据和建立统一的分析渠道。 我们建议继续在Dana-Farber开发癌症免疫学数据共享（CIDC）。 癌症研究所的目标是利用生物标志物推进转化研究工作，以帮助进一步 癌症免疫疗法的发展。本申请的短期目标是建立和 管理用于癌症免疫监测的生物标志物和相关临床数据的数据储存库， 分析中心（CIMAC），并提供了一个信息学环境的综合多维分析 在不同的研究和存储数据产生。具体而言，我们建议：目标1，与 CIMAC和实验室协调委员会（LCC）协调建立测定方案和数据格式 目标2，开发一个中央数据储存库和管理系统，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和更大的研究社区提供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CIMAC数据的综合和相关分析， 用于生物标志物发现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 利用先进的编程接口访问功能，以便能够共享CIMAC数据;目标6，开发 交互式网络可视化功能，使研究人员和免疫学社区能够检查 目标7，协调CIMAC-CIDC网络内的后勤和科学活动， 生物标志物发现和验证。 最后，我们将建立一个生物标志物储存库，用于所有数据和结果， CIMAC，辅以标准化的信息学工具，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。已建立的数据共享空间还将 为更大的研究社区提供未来免疫肿瘤学数据资源的基础。

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.