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
基本信息
- 批准号:10517572
- 负责人:
- 金额:$ 18.02万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AftercareAreaAtlasesCancer BiologyCancer CenterCell CommunicationCellsClinicClinical TrialsCollectionCore BiopsyDataDiagnosisDiseaseDisease ManagementDoctor of PhilosophyEnvironmentFine needle aspiration biopsyFormaldehydeFundingGoalsHumanImageImmune systemImmunofluorescence ImmunologicJournalsLaboratoriesLeadLicensingMethodsMicroscopyMolecularMorphologyMusParaffin EmbeddingPatientsPeriodicityPharmacologyPlayProtocols documentationPublic DomainsPublicationsPublishingResearchResearch SupportResolutionRoleSlideSolid NeoplasmSpecialistSpecimenStagingStructureSystemTechnologyThree-Dimensional ImagingTissue PreservationTissue imagingTissuesTranscriptWorkbasecancer imagingcancer initiationcell typedesigndigital pathologyhigh dimensionalityhigh resolution imagingimmunological synapseimprovedinsightmass spectrometric imagingnovel strategiesperformance siteprotein biomarkerstechnology research and developmenttreatment responsetumortumor progression
项目摘要
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.
SUMMARY-ABSTRACT
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jia-Ren Lin其他文献
Jia-Ren Lin的其他文献
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{{ truncateString('Jia-Ren Lin', 18)}}的其他基金
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 - 财政年份:2022
- 资助金额:
$ 18.02万 - 项目类别:
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