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.

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