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: 10517572
• 负责人: Jia-Ren Lin
• 金额: $ 18.02万
• 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/10517572
• 关键词: Aftercare; Area; Atlases; Cancer Biology; Cancer Center; Cell Communication; Cells; Clinic; Clinical Trials; 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; base; cancer imaging; cancer initiation; cell type; design; digital pathology; high dimensionality; high resolution imaging; immunological synapse; improved; insight; mass spectrometric imaging; novel strategies; performance site; protein biomarkers; technology research and 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 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，以深入表征不同实体瘤的微环境， 由国家癌症研究所资助的合作者在哈佛系统药理学实验室进行研究 (LSP)、Dana Farber/哈佛癌症中心和其他四个NCI癌症中心。这个PI 研究专家Jerry Lin博士，发明了基于组织的循环免疫荧光 （CyCIF）在2018年，并已使其成为领先的公共领域（免许可证）的方法， 高级组织分析他已经将该方法应用于选定的高分辨率3D成像。 视野（约103个细胞，使用去卷积显微镜）以及快速分析整个 切片（~106个细胞），分辨率较低。开发的CyCIF可以收集20-60种蛋白质的数据 来自单个样本的标记物，使得可以在细胞中识别细胞类型和状态。 保存的组织环境。它还可以成像小到免疫突触的结构 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了 18个国家癌症研究所资助的实验室的研究和他发表的CyCIF协议被用于 多个独立于HMS团队工作的其他实验室。林医生也会表演他自己的 作为人类肿瘤图谱网络跨网络项目的一部分， 现在领导。通过这些活动，在过去三年中共出版了20份合作出版物。 多年来，包括与林博士作为第一或共同第一作者在高影响力期刊上发表的几篇文章。 作为R50提案的一部分，林博士将从事三项主要活动。首先，他会 继续与研究小组合作，在不同阶段获取CyCIF数据， 和治疗后。这将使识别分子和形态特征成为可能 与疾病的发生、进展和治疗反应相关。第二，他将 继续改进CyCIF方法，并将其与其他空间方法相结合， 人和鼠肿瘤的询问（例如转录物谱分析和成像质量 光谱法）。林博士还将继续领导HTAN TNP，旨在比较空间 跨技术和性能站点分析方法。这项研究已经导致 对充分供电的空间配置文件以及 全载玻片2D和3D成像。第三，他将继续开发和验证新方法 本发明涉及组织成像，特别是适用于医学领域中的数字病理学工作流程的那些组织成像。 临床试验和患者诊断的设置。这是建立在CyCIF收集 常规使用甲醛固定石蜡包埋（FFPE）标本的高质量数据 采集用于患者诊断和分期（包括核心活检和细针抽吸）。 这种合作和原创性研究与技术开发的结合， 预计将对转化癌症生物学的新兴领域产生重大影响，并完全 符合基于实验室的R50研究专家的预期角色。