Advancing technologies for the collection and analysis of high dimensional immunoprofiles and tumor images

先进的高维免疫图谱和肿瘤图像收集和分析技术

• 批准号: 10707358
• 负责人: Jia-Ren Lin
• 金额: $ 17.47万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707358
• 关键词: Aftercare; Area; Atlases; Cancer Biology; Cancer Center; Cell Communication; Cells; Clinic; Clinical Trials; Collaborations; Collection; Core Biopsy; Data; Diagnosis; Disease; Disease Management; Doctor of Philosophy; Environment; Fine needle aspiration biopsy; Formaldehyde; Funding; Goals; Human; Image; Immune system; Immunofluorescence Immunologic; Journals; Laboratories; Lead; Licensing; Methods; Microscopy; Molecular; Morphology; Mus; Paraffin Embedding; Patients; Periodicity; Pharmacology; Play; Protocols documentation; Public Domains; Publications; Publishing; Research; Research Support; Resolution; Role; Slide; Solid Neoplasm; Specialist; Specimen; Staging; Structure; System; Technology; Three-Dimensional Imaging; Tissue Preservation; Tissue imaging; Tissues; Transcript; Work; cancer imaging; cancer initiation; cell type; design; digital pathology; high dimensionality; high resolution imaging; immunological synapse; improved; insight; invention; mass spectrometric imaging; novel strategies; performance site; protein biomarkers; research and development; technology development; treatment response; tumor; tumor progression

SUMMARY-ABSTRACT The overall goal of this proposal is to use highly multiplexed, high-resolution imaging of tissues and tumors to deeply characterize the microenvironments of diverse solid tumors being studied by NCI-funded collaborators at the Harvard Laboratory of Systems Pharmacology (LSP), Dana Farber/Harvard Cancer Center and four other NCI cancer centers. The PI of this proposal, Research Specialist Jerry Lin PhD, invented tissue-based cyclic immunofluorescence (CyCIF) in 2018 and has made it the leading public domain (license-free) method for performing high-plex tissue analysis. He has adapted the method to high resolution 3D imaging of selected fields of view (~103 cells using deconvolution microscopy) as well as rapid analysis of whole slides (~106 cells) at lower resolution. As developed CyCIF can collect data from 20-60 protein markers from a single specimen making it possible to identify cell types and states in a preserved tissue environment. It can also image structures as small as immune synapses allowing cell-cell interactions to be analyzed at a functional level. Dr. Lin’s work directly supports research by 18 NCI-funded laboratories and the CyCIF protocols he has published are used by multiple other labs working independent of the HMS team. Dr. Lin also performs his own research as part of a Human Tumor Atlas Network Trans Network Project that conceived and now leads. These activities have resulted in 20 collaborative publications over the past three years including several in high impact journals with Dr. Lin as first or co-first author. As part of this R50 proposal Dr Lin will engage in three primary activities. First, he will continue to collaborate with research groups to acquire CyCIF data at different stages before and after treatment. This is will make it possible to identify molecular and morphological features associated with disease initiation, progression, and therapeutic response. Second, he will continue to improve the CyCIF method and integrate it with other methods for spatial interrogation of human and murine tumors (e.g. transcript profiling and imaging mass spectrometry). Dr. Lin will also continue to lead an HTAN TNP designed to compare spatial profiling methods across technologies and performance sites. This research has already led to unexpected insights into adequately powering spatial profiles as well as the relative merits of whole-slide 2D and 3D imaging. Third, he will continue to develop and validate new approaches to tissue imaging, particularly those that are applicable to digital pathology workflows in the setting of clinical trials and patient diagnosis. This builds on the proven ability of CyCIF to collect high quality data from the formaldehyde-fixed paraffin embedded (FFPE) specimens routinely acquired for patient diagnosis and staging (including core biopsies and fine needle aspirates). This combination of collaborative and original research and technology development is expected to have a high impact on an emerging area of translational cancer biology and is fully consistent with the roles expected of a laboratory-based R50 Research Specialist.

摘要提取 该提案的总体目标是使用高度多路复用的高分辨率成像 组织和肿瘤以深层表征潜水员实体瘤的微环境 由NCI资助的Systems药理学实验室的NCI资助的合作者研究 （LSP），Dana Farber/Harvard Cancer Center和其他四个NCI癌症中心。这个的pi 提案，研究专家杰里·林（Jerry Lin PhD），发明了基于组织的循环免疫荧光 （Cycif）在2018年，使其成为执行的领先公共领域（无许可）方法 高质组织分析。他已将方法调整为高分辨率3D成像的选定成像 视野（使用反卷积显微镜的〜103个细胞）以及整体的快速分析 较低分辨率的幻灯片（〜106个细胞）。随着开发的Cycif可以从20-60蛋白收集数据 来自单个标本的标记，使得可以在 保存的组织环境。它还可以成像与免疫突触一样小的结构 允许在功能水平上分析细胞 - 细胞相互作用。林博士的工作直接支持 18个NCI资助的实验室的研究和他发表的Cycif协议的研究由 独立于HMS团队工作的其他多个实验室。林博士还表演自己的 研究是人类肿瘤Atlas网络跨网络项目的一部分，该项目构思和 现在领先。这些活动在过去的三个中导致了20个合作出版物 多年包括在高影响期刊上与林博士担任第一任作者或联合首先作者的几年。 作为R50提案的一部分，林博士将进行三个主要活动。首先，他会的 继续与研究小组合作以在不同阶段获取Cycif数据 并在治疗后。这将使识别分子和形态学特征成为可能 与疾病倡议，进展和治疗反应有关。其次，他会的 继续改善CYCIF方法并将其与其他空间方法集成 人类和鼠肿瘤的询问（例如，成绩单分析和成像质量 光谱法）。林博士还将继续领导HTAN TNP，以比较空间 跨技术和性能站点的分析方法。这项研究已经导致 意想不到的见解可以充分为空间概况提供动力以及相对优点 全滑动2D和3D成像。第三，他将继续开发并验证新方法 进行组织成像，尤其是适用于数字病理学工作流程的成像 临床试验和患者诊断的设置。这建立在赛季库的可靠能力基础上 甲醛固定石蜡（FFPE）的高质量数据常规标本 获得用于患者诊断和分期的（包括核心活检和细针抽吸物）。 协作和原始研究与技术发展的这种结合是 预计将对转化癌生物学的新兴领域产生很大影响，并且完全是 与基于实验室的R50研究专家所期望的角色一致。