Advancing technologies for the collection and analysis of high dimensional immunoprofiles and tumor images
Advancing technologies for the collection and analysis of high dimensional immunoprofiles and tumor images
批准号:
10517572
负责人:
Jia-Ren Lin
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
项目状态:
未结题
起止时间:
2022-09-20 至 2027-08-31
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
中文摘要
摘要-摘要
这项提议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,以深入表征各种实体肿瘤的微环境
由NCI资助的合作者在哈佛系统药理学实验室进行的研究
(LSP)、Dana Farber/哈佛癌症中心和其他四个NCI癌症中心。这件事的PI
建议,研究专家曾傑瑞林博士发明了基于组织的循环免疫荧光
(CyCIF),并已使其成为领先的公有领域(免许可证)执行方法
高丛组织分析。他已经将这种方法应用于选定的高分辨率3D成像
视野(使用去卷积显微镜约103个细胞)以及快速分析整体
以较低的分辨率幻灯片(约106个单元格)。目前,CyCIF可以收集20-60个蛋白质的数据
单个样本的标记使识别细胞类型和状态成为可能
保存的组织环境。它还可以成像免疫突触般小的结构
允许在功能水平上分析细胞间的相互作用。林博士的工作直接支持了
NCI资助的18个实验室的研究和他发表的CyCIF协议被
独立于HMS团队工作的多个其他实验室。林博士还表演了他自己的表演
作为人类肿瘤图谱网络传输网络项目的一部分进行的研究
现在有线索了。在过去的三年里,这些活动产生了20种合作出版物
多年来,包括几篇发表在高影响力期刊上的文章,林博士是第一作者或联合第一作者。
作为R50计划的一部分,林博士将参与三项主要活动。首先,他会
继续与研究小组合作,获取之前不同阶段的CyCIF数据
并在治疗后。这将使鉴定分子和形态特征成为可能
与疾病的发生、发展和治疗反应有关。第二,他会
继续改进CyCIF方法,并将其与其他空间方法相结合
人类和小鼠肿瘤的询问(例如,转录谱分析和成像质量
光谱分析)。林博士还将继续领导Htan TNP,旨在比较空间
跨技术和性能站点的分析方法。这项研究已经导致了
对充分支持空间配置文件的意想不到的见解以及
全幻灯片2D和3D成像。第三,他将继续开发和验证新的方法
适用于组织成像,尤其是适用于
临床试验和患者诊断的设置。这是建立在CyCIF经过验证的收集能力的基础上的
常规甲醛固定石蜡包埋(FFPE)标本的高质量数据
用于患者诊断和分期(包括核心活组织检查和细针抽吸物)。
这种协作和原创研究和技术开发的组合是
预计将对转译癌症生物学的一个新兴领域产生重大影响,并完全
与实验室R50研究专家应有的角色一致。
英文摘要
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.
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会议论文
Advancing technologies for the collection and analysis of high dimensional immunoprofiles and tumor images
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批准号:10707358
-
项目类别:
-
资助金额:$17.47万
-
财政年份:2022
-
负责人:Jia-Ren Lin
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依托单位:
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依托单位: