System Dynamics of PD-1 Signaling in T Cells
T 细胞中 PD-1 信号传导的系统动力学
基本信息
- 批准号:10399590
- 负责人:
- 金额:$ 78.53万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-05-03 至 2027-04-30
- 项目状态:未结题
- 来源:
- 关键词:AccountingAffinityAntibodiesAntigen PresentationAntigen-Presenting CellsAntigensAutoimmune DiseasesAutoimmunityB7-DC antigenBioinformaticsBiological AssayCD28 geneCD8-Positive T-LymphocytesCD80 geneCD86 geneCell LineCellsChronicClustered Regularly Interspaced Short Palindromic RepeatsComplementDataData AnalysesDiseaseEngineeringEvaluationFamilyFluorescence MicroscopyFormulationHumanITAMImmuneImmune TargetingImmune responseImmune systemImmunologic SurveillanceImmunotherapyIndividualInnate Immune ResponseInterventionInvestigationKnowledgeLabelLigandsMass Spectrum AnalysisMeasurementMeasuresMediatingMembraneMethodsModelingMolecularMonitorNR0B2 geneOncologyPTPN11 genePTPN6 genePatternPhosphoric Monoester HydrolasesPhosphorylationPhosphorylation SitePhosphotransferasesPhosphotyrosinePlayPopulationProtein DephosphorylationProtein Tyrosine KinaseProtein Tyrosine PhosphataseProteinsProtocols documentationReagentReceptor InhibitionReceptor SignalingRoleSYK geneSamplingSignal TransductionSignaling ProteinSiteStructureSystems BiologyT-Cell ActivationT-Cell ReceptorT-LymphocyteTechniquesTestingTherapeutic antibodiesTimeToll-like receptorsTyrosine PhosphorylationValidationWestern BlottingZAP-70 Geneadaptive immune responsearmcancer cellchronic infectiondectin 1dynamic systemexhaustionexperimental studyimmune activationimmune checkpointimprovedinterestmachine learning predictionmathematical modelneoplastic cellnovel therapeutic interventionparticlepathogenpathogenic fungusphosphoproteomicspredictive modelingpredictive testpreventprogrammed cell death ligand 1programmed cell death protein 1receptorrecruitresponsesegregationsingle molecule
项目摘要
PROJECT SUMMARY/ABSTRACT
Adaptive immune responses are governed by T cell receptor (TCR) signaling, which determines the fates and
activities of T cells (helper, effector, etc.). The TCR and its signaling partners integrate antigen-recognition
signals and second signals, which carry information about the context in which antigen presentation is
occurring. Second signals can be either stimulatory or inhibitory: stimulatory signals are essential for T cell
activation, whereas inhibitory signals (also called checkpoints) are responsible for T cell exhaustion and
antigen tolerance. Stimulatory second signals are generated by the innate arm of the immune system when, for
example, signaling by Toll-like receptors induces expression of the B7-family ligands B7-1 (CD80) and B7-2
(CD86) on antigen-presenting cells. Expression of B7-1/B7-2 indicates that antigen presentation is occurring
within the context of an ongoing innate immune response. B7-1 and B7-2 are recognized by CD28, a TCR
coreceptor that potently enhances TCR-generated T-cell activation signals. Inhibitory second signals arise
during the course of chronic stimulation of TCR signaling. They are important for limiting the collateral damage
caused by an immune response and avoidance of autoimmunity, but they can also be deleterious. For
example, tumor cells commonly express the B7-family ligands B7-H1 (PD-L1/CD274) and B7-DC (PD-
L2/CD273), which are recognized by PD-1, a TCR coreceptor that inhibits TCR-generated T-cell activation
signals. B7-H1/B7-DC expression conveys immune privilege to tumor cells. For these and other reasons, it is
imperative that we improve our basic understanding of checkpoint signaling. Here, we propose to characterize
the dynamics of PD-1-regulated tyrosine phosphorylation in Jurkat E6-1, HuT 78, and TALL-104 cells,
CRISPR-engineered cells derived from these parental cell lines, and primary human CD8+ cells. We will apply
quantitative mass spectrometry (MS) to obtain an unbiased, nearly comprehensive picture of phosphotyrosine
(pTyr) site abundances with and without PD-1/CD28 coreceptor signaling in populations of T cells over time
and across conditions. Concurrently, using fluorescence microscopy and engineered SH2 domain affinity
reagents, we will characterize single-molecule patterns of multisite phosphorylation for TCR, CD28, and PD-1.
We will also measure membrane-recruitment lifetimes for individual cytosolic signaling partners of these
receptors. The resulting data will be used to drive the formulation and parameterization of a detailed
mechanistic model for TCR signaling accounting for the effects of CD28 and PD-1 coactivation. Although PD-1
is viewed as a platform for recruitment of phosphatases that counteract activation signals from kinases, we will
evaluate specific hypotheses about how PD-1 could potentially generate positive signals for T-cell activation.
These hypotheses are motivated by the fact that the best characterized signaling partners of PD-1 are protein
tyrosine phosphatases, SHP1 and SHP2, which are known to promote cell activation in other contexts by, for
example, mediating the dephosphorylation of inhibitory pTyr sites. Model predictions will be tested.
项目总结/文摘
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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William S Hlavacek其他文献
William S Hlavacek的其他文献
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{{ truncateString('William S Hlavacek', 18)}}的其他基金
System Dynamics of PD-1 Signaling in T Cells
T 细胞中 PD-1 信号传导的系统动力学
- 批准号:
10211871 - 财政年份:2021
- 资助金额:
$ 78.53万 - 项目类别:
Multiscale Modeling to Optimize Inhibition of Oncogenic ERK Pathway Signaling
多尺度建模优化致癌 ERK 通路信号传导的抑制
- 批准号:
10558581 - 财政年份:2020
- 资助金额:
$ 78.53万 - 项目类别:
Multiscale Modeling to Optimize Inhibition of Oncogenic ERK Pathway Signaling
多尺度建模优化致癌 ERK 通路信号传导的抑制
- 批准号:
10337242 - 财政年份:2020
- 资助金额:
$ 78.53万 - 项目类别:
Computational Model of Autophagy-Mediated Survival in Chemoresistant Lung Cancer
自噬介导的化疗耐药肺癌生存的计算模型
- 批准号:
9547104 - 财政年份:2017
- 资助金额:
$ 78.53万 - 项目类别:
Computational Model of Autophagy-Mediated Survival in Chemoresistant Lung Cancer
自噬介导的化疗耐药肺癌生存的计算模型
- 批准号:
9769647 - 财政年份:2017
- 资助金额:
$ 78.53万 - 项目类别:
Computational Model of Autophagy-Mediated Survival in Chemoresistant Lung Cancer
自噬介导的化疗耐药肺癌生存的计算模型
- 批准号:
9139424 - 财政年份:2015
- 资助金额:
$ 78.53万 - 项目类别:
Hardening Software for Rule-based models-Competitive Revision
基于规则的模型的强化软件 - 竞争性修订
- 批准号:
10382135 - 财政年份:2014
- 资助金额:
$ 78.53万 - 项目类别:
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