PRIMAVO: Interactive exploration of cancer patient precision immune monitoring data in clinical trials

项目总结 癌症免疫疗法极大地改变了临床实践，此前有超过一项 过去几年的十几种新药和/或适应症1-4。然而，只有少数患者 临床受益，而有些则会产生非靶向效应。寻找新的疾病病程和生物标志物 NCI‘s癌症患者对免疫治疗的反应以及潜在的非靶点反应 登月计划(CMI)正在支持越来越多的癌症免疫治疗试验。我们队在最后一站 CMI努力的前沿有两项赠款：1)关于NCI支持的高维免疫监测的U24 作为癌症治疗评估计划(CTEP)一部分的免疫治疗试验；和2)U01关于 免疫检查点阻断中免疫疗法的毒副作用结肠炎的特征和预测- 治疗癌症患者，作为免疫肿瘤学翻译网络(IOTN)的一部分。然而，随着 随着新技术和改进技术的快速发展，这些研究产生了前所未有的各种数据类型 不断扩大的规模和复杂性。可视化、探索和交流计算的结果 分析这些不同的高维免疫监测分析势在必行，但具有挑战性， 尤其是因为许多可视化工具要么仅为内部使用而构建，要么通常专门 只有一种或几种数据类型。同时，交叉分析或交叉参与者的数据解释是 识别影响临床试验设计和临床癌症护理的相关免疫生物标记物的唯一方法。 因此，对用于癌症患者综合探查的简单易用的交互工具的需求尚未得到满足 生物学家和临床医生的免疫监测数据。本提案旨在通过以下方式解决这一需求 开发一个用户友好的基于Web的综合可视化工具--精密免疫学监测 在线分析和可视化(PRIMAVO)，这将使所有计算技能水平的研究人员能够 直观地分析和交互地探索属于癌症的免疫监测化验结果 免疫治疗试验，在多个级别的粒度。PRIMAVO工具将根据当前和未来的数据进行扩展 增长和复杂性，以实现快速有效的研究，以确定不同 数据类型、参与者和临床变量。我们假设发展中的(I)队列水平；和(Ii) 参与者级别的可视化，集成了跨多种免疫数据类型、参与者、队列的视图 和时间点将提供对事件的深入、全面的看法；以及(Iii) 在PRIMAVO开发期间，通过与用户社区接触，它将得到极大的增强。结果是 这一高度集成的努力将对临床和公共卫生产生重要影响， 了解癌症患者对免疫疗法的免疫反应并显著影响 来自临床试验的免疫生物标记物将被识别、解释、验证和转化为 临床上可操作的发现。总体而言，PRIMAVO对研究界来说将是一个非常有价值的工具。

PROJECT SUMMARY Cancer immunotherapies have dramatically changed clinical practice following the approval of more than a dozen new drugs and/or indications in the past few years1–4. However, only a minority of patients derives clinical benefit, while some develop off-target effects. To identify novel biomarkers of disease course and response, as well as potential off-target responses to immunotherapy in cancer patients, the NCI’s Cancer Moonshot Initiative (CMI) is supporting a growing number of cancer immunotherapy trials. Our team is at the forefront of the CMI efforts with two grants: 1) a U24 on high-dimensional immune monitoring of NCI-supported immunotherapy trials as part of the Cancer Therapy Evaluation Program (CTEP); and 2) a U01 on characterizing and predicting a toxic side-effect of immunotherapy, colitis, in immune checkpoint blockade- treated cancer patients, as part of the Immuno-Oncology Translational Network (IOTN). However, with the rapid development of new and improved technologies, these studies produce diverse data types of ever- expanding size and complexity. Visualizing, exploring, and communicating results from the computational analysis of these disparate high-dimensional immune monitoring assays is imperative but challenging, especially because many visualization tools are either built only for in-house utilization or typically specialize in only one or perhaps a few data types. At the same time, cross-assay or cross-participant data interpretation is the only way to identify relevant immune biomarkers that impact clinical trial design and clinical cancer care. There is thus an unmet need for easy-to-use interactive tools for integrative exploration of cancer patient immune monitoring data by biologists and clinicians. This proposal aims to address this need through the development of a user-friendly, integrative web-based visualization tool, Precision Immunology Monitoring Analysis and Visualization Online (PRIMAVO), that will enable researchers of all computational skill levels to visually analyze and interactively explore immune monitoring assay results that belong to a cancer immunotherapy trial, at multiple levels of granularity. The PRIMAVO tool will scale with current and future data growth and complexity to enable fast and effective research towards identifying associations between different data types, participants, and clinical variables. We hypothesize that developing (i) cohort-level; and (ii) participant-level visualizations that integrate views across multiple immune data types, participants, cohorts and time points will provide a deep, comprehensive view of events; and that (iii) the content and features of PRIMAVO will be greatly enhanced by engaging with the user community during its development. The results from this highly integrated effort will have important clinical and public health implications by accelerating our understanding of the immune responses of cancer patients to immunotherapies and significantly impact the rate at which immune biomarkers from clinical trials will be identified, interpreted, verified and translated into clinically actionable findings. Overall, PRIMAVO will be a highly valuable tool for the research community.