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

PRIMAVO:临床试验中癌症患者精准免疫监测数据的互动探索

基本信息

项目摘要

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.
项目概要 在多个国家批准后,癌症免疫疗法极大地改变了临床实践 过去几年中出现了十几种新药和/或适应症1-4,但是只有少数患者获得了治疗。 临床获益,同时有些会产生脱靶效应,以确定疾病进程和的新生物标志物。 反应,以及癌症患者对免疫治疗的潜在脱靶反应,NCI 的癌症 Moonshot Initiative (CMI) 正在支持越来越多的癌症免疫治疗试验。 凭借两项资助走在 CMI 工作的最前沿:1) NCI 支持的 U24 高维免疫监测 作为癌症治疗评估计划 (CTEP) 一部分的免疫治疗试验;以及 2) U01; 表征和预测免疫疗法的毒副作用,即结肠炎,在免疫检查点封锁中- 然而,作为免疫肿瘤转化网络(IOTN)的一部分,治疗癌症患者。 随着新技术和改进技术的快速发展,这些研究产生了各种不同的数据类型 扩大规模和复杂性,可视化、探索和交流计算结果。 对这些不同的高维免疫监测分析的分析势在必行,但具有挑战性, 特别是因为许多可视化工具要么仅供内部使用,要么通常专门用于 仅一种或可能几种数据类型 同时,跨测定或跨参与者数据解释。 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志物的唯一方法。 因此,对于用于癌症患者综合探索的易于使用的交互式工具的需求尚未得到满足 该提案旨在通过生物学家和暴民提供的免疫监测数据来满足这一需求。 开发用户友好的、基于网络的综合可视化工具“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 直观地分析和交互探索属于癌症的免疫监测测定结果 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,以识别不同类型之间的关联 我们开发了(i)队列级别的数据类型、参与者和临床变量; 参与者级可视化,整合多种免疫数据类型、参与者、群组的视图 时间点将提供对事件的深入、全面的看法;以及 (iii) 事件的内容和特征; PRIMAVO 在开发过程中通过与用户社区的互动将大大增强其成果。 这项高度综合的努力将加速我们的研究,从而产生重要的临床和公共卫生影响 了解癌症患者对免疫疗法的免疫反应并显着影响 临床试验中的免疫生物标志物被识别、解释、验证并转化为免疫生物标志物的速度 总体而言,PRIMAVO 将成为研究界非常有价值的工具。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Germline rare deleterious variant load alters cancer risk, age of onset and tumor characteristics.
  • DOI:
    10.1038/s41698-023-00354-3
  • 发表时间:
    2023-01-27
  • 期刊:
  • 影响因子:
    7.9
  • 作者:
  • 通讯作者:
Are polygenic risk scores ready for the cancer clinic?-a perspective.
Scientists without borders: lessons from Ukraine.
  • DOI:
    10.1093/gigascience/giad045
  • 发表时间:
    2022-12-28
  • 期刊:
  • 影响因子:
    9.2
  • 作者:
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