Analytical tools for studying the tumor microenvironment leveraging spatial transcriptomics
利用空间转录组学研究肿瘤微环境的分析工具
基本信息
- 批准号:10524921
- 负责人:
- 金额:$ 41.57万
- 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:2022-09-01 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:ArchitectureAutomobile DrivingBasic ScienceBioconductorBioinformaticsBiologicalBiological AssayCancer CenterCancer PatientCancer PrognosisCancer ScienceCellsClinicalClinical SciencesCollaborationsColoradoCommunicationComputer softwareComputing MethodologiesCytometryDNA Sequence AlterationDataData ScientistDevelopmentEnsureEpigenetic ProcessFutureGene ExpressionGenomicsGoalsHeterogeneityImageImmunofluorescence ImmunologicImmunotherapyIndividualInfiltrationLocationMalignant NeoplasmsManuscriptsMeasurementMeasuresMethodologyMethodsModalityNeoplasm MetastasisOnline SystemsOutcomePatientsPharmaceutical PreparationsPhenotypeProcessRNAResearchResearch PersonnelResearch Project GrantsResolutionSamplingSliceSoftware ToolsSpottingsStatistical MethodsTechnologyTissue FixationTissue SampleTissuesTranscriptTranslatingTranslational ResearchTumor-infiltrating immune cellsUniversitiesVisualizationanalytical methodanalytical toolbasecell typecommercializationcomputerized toolsdata integrationdata structuredesignexperimental studyfallshigh dimensionalityimmune functioninnovationinsightinterestmultidimensional datanovelpatient responsepersonalized medicinephenotypic dataprognosticationresponsesingle-cell RNA sequencingsoftware developmentspatial integrationstatisticstooltranscriptometranscriptome sequencingtranscriptomicstreatment responsetumortumor heterogeneitytumor microenvironmenttumorigenesisusabilityuser friendly softwareweb app
项目摘要
PROJECT SUMMARY/ABSTRACT
Understanding the tumor microenvironment (TME) heterogeneity and architecture are key to stratify cancer
patients responsive to immunotherapy and clinical outcome. Single-cell RNA sequencing (scRNAseq) is a
powerful tool for studying the TME at the single-cell level, however, spatial information between single cells
was not preserved in this technology, which is vital in studying the TME. In contrast, use of spatially resolved
transcriptomics holds the promise in the understanding of the spatial contexture of the TME because of its
power to capture the location of individual cells within the larger tissue architecture. Recently,
commercialization of spatial transcriptomic (ST) technologies have allowed researchers to study at an
unprecedented level the spatial architecture of the TME. Similar to other “omics” technologies, novel
computational tools are urgently needed to decipher and infer biological meaning for these high-dimensional
ST data. In addition to the need for methods for analyzing and visualizing ST data in its current form, there is
the need to develop methods for the future state of ST, whereby the level of cellular resolution is vastly
decreasing to the single cell level. Moreover, the application of multiple assays to one tissue sample is also
producing multiple modalities measured on the same sample (e.g., scRNAseq, image-based cytometry
methods such as multiplex immunofluorescence) which requires effective methods for data integration. Lastly,
many ST studies are completed on multiple samples simultaneous with the goal of correlating TME features
with clinical outcome, thus requiring computational tools to unravel the impact of the spatial architecture of the
TME on clinical response. In the proposed research, we will tackle these challenges by implementing state-of-
the-art statistical and computational methods that account for and leverage the spatial information present in
ST data to understanding the TME. We will develop innovative methods for assessing the TME’s composition
(Aim 1) and studying co-localization and spatial heterogeneity (Aim 2), along with hardening of the analytical
software, spatialGE, for the analysis and visualization of ST data (Aim 3). The statistical and bioinformatics
analytical approaches implemented in spatialGE will allow cancer researchers to easily leverage these
methods in their studies of the TME. These analytical methods, along with the developed software tools
(spatialGE R/Bioconductor package along with web-based software), will be established in collaboration with
clinical, translational, and basic science cancer investigators to ensure usability and interpretability of the
developed approaches.
项目概要/摘要
了解肿瘤微环境 (TME) 异质性和结构是癌症分层的关键
对免疫治疗和临床结果有反应的患者。单细胞 RNA 测序 (scRNAseq) 是一种
在单细胞水平上研究 TME 的强大工具,但是单细胞之间的空间信息
这项技术中没有保留这一点,这对于研究 TME 至关重要。相比之下,使用空间分辨
转录组学在理解 TME 的空间背景方面具有希望,因为它
能够捕获更大组织结构中单个细胞的位置。最近,
空间转录组 (ST) 技术的商业化使研究人员能够在
TME 的空间建筑达到了前所未有的水平。与其他“组学”技术类似,新颖
迫切需要计算工具来破译和推断这些高维的生物学意义
ST数据。除了需要分析和可视化当前形式的 ST 数据的方法之外,还需要
需要为 ST 的未来状态开发方法,其中细胞分辨率水平将大大提高
降低至单细胞水平。此外,对一个组织样本进行多种测定也很重要。
产生在同一样本上测量的多种模式(例如 scRNAseq、基于图像的细胞计数
方法,如多重免疫荧光),这需要有效的数据整合方法。最后,
许多 ST 研究是在多个样本上同时完成的,目的是关联 TME 特征
与临床结果相关,因此需要计算工具来揭示空间结构的影响
TME 对临床反应的影响。在拟议的研究中,我们将通过实施现状来应对这些挑战
最先进的统计和计算方法,可以解释和利用存在于其中的空间信息
ST数据来理解TME。我们将开发评估 TME 成分的创新方法
(目标 1)并研究共定位和空间异质性(目标 2),以及分析的强化
SpatialGE 软件,用于 ST 数据的分析和可视化(目标 3)。统计和生物信息学
SpatialGE 中实施的分析方法将使癌症研究人员能够轻松利用这些方法
他们的 TME 研究中的方法。这些分析方法以及开发的软件工具
(spatialGE R/Bioconductor 软件包以及基于网络的软件),将与
临床、转化和基础科学癌症研究人员,以确保其可用性和可解释性
开发的方法。
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)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Brooke L Fridley其他文献
Polymorphisms in NF-κB Inhibitors and Risk of Epithelial Ovarian Cancer
- DOI:
10.1186/1471-2407-9-170 - 发表时间:
2009-06-06 - 期刊:
- 影响因子:3.400
- 作者:
Kristin L White;Robert A Vierkant;Catherine M Phelan;Brooke L Fridley;Stephanie Anderson;Keith L Knutson;Joellen M Schildkraut;Julie M Cunningham;Linda E Kelemen;V Shane Pankratz;David N Rider;Mark Liebow;Lynn C Hartmann;Thomas A Sellers;Ellen L Goode - 通讯作者:
Ellen L Goode
Gene set analysis of SNP data: benefits, challenges, and future directions
单核苷酸多态性数据的基因集分析:益处、挑战和未来方向
- DOI:
10.1038/ejhg.2011.57 - 发表时间:
2011-04-13 - 期刊:
- 影响因子:4.600
- 作者:
Brooke L Fridley;Joanna M Biernacka - 通讯作者:
Joanna M Biernacka
Brooke L Fridley的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Brooke L Fridley', 18)}}的其他基金
Bayesian Integrative Clustering for Determining Molecular Based Cancer Subty
用于确定基于分子的癌症亚型的贝叶斯整合聚类
- 批准号:
8625856 - 财政年份:2013
- 资助金额:
$ 41.57万 - 项目类别:
Bayesian hierarchical nonlinear models for pharmacogenomic cytotoxicity studies
用于药物基因组细胞毒性研究的贝叶斯分层非线性模型
- 批准号:
8286143 - 财政年份:2011
- 资助金额:
$ 41.57万 - 项目类别:
Bayesian hierarchical nonlinear models for pharmacogenomic cytotoxicity studies
用于药物基因组细胞毒性研究的贝叶斯分层非线性模型
- 批准号:
7984103 - 财政年份:2011
- 资助金额:
$ 41.57万 - 项目类别:
Integrative genomic models for analysis of pharmacogenomic studies
用于分析药物基因组研究的综合基因组模型
- 批准号:
7698677 - 财政年份:2009
- 资助金额:
$ 41.57万 - 项目类别:
相似海外基金
Establishment of a method for evaluating automobile driving ability focusing on frontal lobe functions and its application to accident prediction
以额叶功能为中心的汽车驾驶能力评价方法的建立及其在事故预测中的应用
- 批准号:
20K07947 - 财政年份:2020
- 资助金额:
$ 41.57万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Evaluation of the Effectiveness of Multi-Professional Collaborative Assessment of Cognitive Function and Automobile Driving Skills and Comprehensive Support
认知功能与汽车驾驶技能多专业协同评估效果评价及综合支持
- 批准号:
17K19824 - 财政年份:2017
- 资助金额:
$ 41.57万 - 项目类别:
Grant-in-Aid for Challenging Research (Exploratory)
Development of Flexible Automobile Driving Interface for Disabled People
残疾人灵活汽车驾驶界面开发
- 批准号:
25330237 - 财政年份:2013
- 资助金额:
$ 41.57万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Automobile driving among older people with dementia: the effect of an intervention using a support manual for family caregivers
患有痴呆症的老年人的汽车驾驶:使用家庭护理人员支持手册进行干预的效果
- 批准号:
23591741 - 财政年份:2011
- 资助金额:
$ 41.57万 - 项目类别:
Grant-in-Aid for Scientific Research (C)














{{item.name}}会员




