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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

批准号：
10294555
负责人：
Zeynep Hulya Gumus
金额：
$ 154.25万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-23 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10294555
关键词：
16S ribosomal RNA sequencing Address Antigens Award Biological Assay Biological Markers Cancer Patient Cancer Therapy Evaluation Program Clinical Clinical Trials Clinical Trials Design Colitis Communication Communities Computer Analysis Custom Cytometry Data Data Analyses Data Commons Data Set Development Dimensions Disease Enzyme-Linked Immunosorbent Assay Event Feedback Flow Cytometry Future Grant Growth Immune Immune response Immune system Immunologic Markers Immunologic Monitoring Immunologics Immunology Immunooncology Immunotherapy Infrastructure Interview Malignant Neoplasms Metagenomics Minority Mission Monitor Mutation Online Systems Output Participant Patients Principal Component Analysis Proteomics Public Health Research Research Personnel Serology Shotguns Standardization Surveys Technology Time Toxic effect Translating Visual Visualization Visualization software analysis pipeline anticancer research base biomarker discovery cancer care cancer immunotherapy clinical practice clinical trial participant clinically actionable cohort data exploration data visualization demographics design diverse data exome experience flexibility high dimensionality immune checkpoint blockade immune-related adverse events immunotherapy clinical trials immunotherapy trials improved interactive tool interest medical schools microbiome analysis novel marker novel therapeutics response response biomarker side effect skills tool tool development transcriptome sequencing treatment response tumor user-friendly web-based tool

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.

项目摘要癌症免疫疗法已经大大改变了临床实践后，批准超过一个在过去几年中，有十几种新药和/或适应症1 - 4。然而，只有少数患者临床受益，而有些则产生脱靶效应。确定疾病进程的新生物标志物，反应，以及癌症患者对免疫疗法的潜在脱靶反应，NCI的癌症 Moonshot Initiative（CMI）正在支持越来越多的癌症免疫治疗试验。我们的团队在在CMI工作的最前沿，有两个赠款：1）一个U24对高维免疫监测NCI支持的作为癌症治疗评估计划（CTEP）的一部分的免疫治疗试验;和2）U01 表征和预测免疫治疗的毒副作用，结肠炎，在免疫检查点阻断- 作为免疫肿瘤学转化网络（IOTN）的一部分。但随着随着新技术和改进技术的快速发展，这些研究产生了各种各样的数据类型，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测定的分析是必要的但具有挑战性，特别是因为许多可视化工具要么仅为内部使用而构建，要么通常专门用于只有一种或几种数据类型。与此同时，交叉测定或交叉参与者数据解释是这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志物的唯一方法。因此，对于用于癌症患者的综合探索的易于使用的交互式工具存在未满足的需求生物学家和临床医生的免疫监测数据。本建议旨在通过以下方式满足这一需求：开发一个用户友好的、基于网络的综合可视化工具，精确免疫学监测分析和可视化在线（PRIMAVO），这将使所有计算技能水平的研究人员，可视化分析和交互式探索属于癌症的免疫监测测定结果免疫治疗试验，在多个粒度级别。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（i）集群水平;和（ii）参与者级别的可视化，可跨多种免疫数据类型、参与者、队列整合视图和时间点将提供一个深刻的，全面的看法的事件;和（三）的内容和特点， PRIMAVO将通过在开发过程中与用户社区的互动而得到极大的增强。结果从这个高度综合的努力将有重要的临床和公共卫生的影响，加快我们的了解癌症患者对免疫疗法的免疫反应，并显著影响临床试验中免疫生物标志物的识别、解释、验证和转化率临床上可行的发现。总体而言，PRIMAVO将成为研究界非常有价值的工具。