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Center of Excellence for High Throughput Proteogenomic Characterization

Center of Excellence for High Throughput Proteogenomic Characterization
高通量蛋白质组表征卓越中心
批准号:
10001970
负责人:
STEVEN A CARR
金额:
$128.62万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-14 至 2021-08-31
关键词:
AddressAdoptedAdoptionAffinityAutomationBiocompatible MaterialsBiological AssayBiological ModelsBiologyCancer BiologyCancer ModelCell LineCellsChemicalsChemistryChromatinClinicalClinical TreatmentCollaborationsCommunitiesCouplesCytometryDNADNA copy numberDataData AnalysesData SetDecision TreesDevelopmentDrug TargetingDrug resistanceFunctional disorderGenomeGenomicsGlioblastomaGoalsGuidelinesHistonesHumanImageInstitutesIntelligenceInternationalInterventionInvestigationKnowledgeLabelLightLiteratureLogicLungLung AdenocarcinomaLysineMalignant NeoplasmsMalignant neoplasm of brainMalignant neoplasm of lungMalignant neoplasm of pancreasMapsMass Spectrum AnalysisMeasurementMeasuresMethodsModelingModificationMolecularMutateMutationNormal tissue morphologyOncogenicPIK3CA genePathway interactionsPatientsPeptidesPerformancePharmacotherapyPhasePhosphopeptidesPopulationPost Translational Modification AnalysisPost-Translational Protein ProcessingProtein IsoformsProteinsProteomeProteomicsPublishingQuality ControlRNA SplicingReagentReproducibilityResearchSamplingSignal PathwaySignal TransductionSiteSpecificitySpecimenSquamous Cell Lung CarcinomaStable Isotope LabelingStandardizationTechnologyTherapeutic InterventionTimeTissuesTumor Cell LineTumor-DerivedVariantXenograft Modelanticancer researchaptamerarmbasebioinformatics toolbiological adaptation to stresscancer typedata acquisitionexperiencegenomic dataimprovedinnovationinsightinstrumentinstrumentationmultidisciplinaryneoplastic cellnew technologynew therapeutic targetnovelpeptide Ipre-clinicalprogramsprotein expressionproteogenomicsrare cancerresponsesingle cell analysisstable isotopetargeted treatmenttranscriptomicstumortumor heterogeneitytumor xenograft

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英文摘要
Project Summary (Carr, Mertins) Genetic alterations in human cancer have been systematically mapped by genomics landscape studies in the past decade, however, the direct consequences of these alterations on the functional proteome are poorly understood. Deep scale, mass spectrometry-based proteomic studies of three tumor types in the current phase of the Clinical Proteomics Tumor Analysis Consortium (CPTAC) program have revealed that integration of proteomic data with genomic data can improve specificity for identifying cancer-relevant pathways triggered by somatic DNA variants or DNA copy number alterations (CNAs) compared to genomic characterization alone, and help narrow target selection for potential therapeutic intervention. Here we propose to extend proteogenomic characterization to additional genetically defined tumor types – lung, brain and pancreatic cancer – and preclinical patient-derived tumor xenografts and cell line models. State-of-the-art LC-MS/MS proteomics technology with highly multiplexed stable- isotope mass tagging (TMT 10-plex) will be employed for precise relative quantification of the proteome, phosphoproteome and acetylome with very deep coverage. Improved multiplexing capabilities in these discovery type analyses enable a throughput of over 500 samples per year in conjunction with longitudinal quality control performance measurements. The proteome data produced will be integrated with genomics data in collaboration with the CPTAC Proteogenomics Data Analysis Centers. The goal will be to identify proteins with somatic variants or cancer-specific splice site junctions, correlate effects between copy number alterations and protein expression, and to identify signaling pathways in the phosphoproteome and lysine-acetylome that are activated by genetic alterations. This proteogenomics approach will inform target selection for confirmatory targeted mass spectrometry assays with a particular emphasis on mutated proteins, oncogenic regulators/effectors, and druggable proteins. We will develop and deploy new and existing analytically validated, highly multiplexed targeted MS- based assays (MRM and PRM) to measure cancer-relevant proteins and modified peptides in human biospecimens for candidate verification. Stable isotope-labeled peptides will be used as internal standards for unambiguous identification and quantification at a multiplex level of up to 200 analytes per assay. Existing technology will be further developed to enable comprehensive analysis of rare tumor cell populations, to evaluate tumor heterogeneity, to increase depth and breadth of post-translational modification analysis, and to improve depth, reliability and repeatability of peptide i.d. and quantification in general by intelligent data acquisition.
期刊论文(42)
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科研奖励(0)
会议论文
DOI: 10.1016/j.mcpro.2021.100133
发表时间: 2021
期刊: Molecular & cellular proteomics : MCP
影响因子: --
作者: [Klaeger S, Apffel A, Clauser KR, Sarkizova S, Oliveira G, Rachimi S, Le PM, Tarren A, Chea V, Abelin JG, Braun DA, Ott PA, Keshishian H, Hacohen N, Keskin DB, Wu CJ, Carr SA]
通讯作者: Carr SA
DOI: 10.1016/j.cell.2020.10.036
发表时间: 2020-11-25
期刊: Cell
影响因子: 64.5
作者: [Krug K, Jaehnig EJ, Satpathy S, Blumenberg L, Karpova A, Anurag M, Miles G, Mertins P, Geffen Y, Tang LC, Heiman DI, Cao S, Maruvka YE, Lei JT, Huang C, Kothadia RB, Colaprico A, Birger C, Wang J, Dou Y, Wen B, Shi Z, Liao Y, Wiznerowicz M, Wyczalkowski MA, Chen XS, Kennedy JJ, Paulovich AG, Thiagarajan M, Kinsinger CR, Hiltke T, Boja ES, Mesri M, Robles AI, Rodriguez H, Westbrook TF, Ding L, Getz G, Clauser KR, Fenyö D, Ruggles KV, Zhang B, Mani DR, Carr SA, Ellis MJ, Gillette MA, Clinical Proteomic Tumor Analysis Consortium]
通讯作者: Clinical Proteomic Tumor Analysis Consortium
DOI: 10.1038/s41597-021-01008-4
发表时间: 2021-08-25
期刊: Scientific data
影响因子: 9.8
作者: [Dele-Oni DO, Christianson KE, Egri SB, Vaca Jacome AS, DeRuff KC, Mullahoo J, Sharma V, Davison D, Ko T, Bula M, Blanchard J, Young JZ, Litichevskiy L, Lu X, Lam D, Asiedu JK, Toder C, Officer A, Peckner R, MacCoss MJ, Tsai LH, Carr SA, Papanastasiou M, Jaffe JD]
通讯作者: Jaffe JD
Spatiotemporally-resolved mapping of RNA binding proteins via functional proximity labeling reveals a mitochondrial mRNA anchor promoting stress recovery.
通过功能接近标记对RNA结合蛋白的空间分辨映射揭示了线粒体mRNA锚固,可促进应力恢复。
DOI: 10.1038/s41467-021-25259-2
发表时间: 2021-08-17
期刊: Nature communications
影响因子: 16.6
作者: [Qin W, Myers SA, Carey DK, Carr SA, Ting AY]
通讯作者: Ting AY
22
    Proteogenomic Predictors of Recurrence in Non-small Cell Lung Cancer
    • 批准号:
      10459716
    • 项目类别:
    • 资助金额:
      $108.43万
    • 财政年份:
      2022
    • 负责人:
      STEVEN A CARR
    • 依托单位:
    Center of Excellence for High Throughput Proteogenomic Characterization
    • 批准号:
      10643840
    • 项目类别:
    • 资助金额:
      $106.63万
    • 财政年份:
      2022
    • 负责人:
      STEVEN A CARR
    • 依托单位:
    Proteogenomic Predictors of Recurrence in Non-small Cell Lung Cancer
    • 批准号:
      10643902
    • 项目类别:
    • 资助金额:
      $103.23万
    • 财政年份:
      2022
    • 负责人:
      STEVEN A CARR
    • 依托单位:
    Center of Excellence for High Throughput Proteogenomic Characterization
    • 批准号:
      10438235
    • 项目类别:
    • 资助金额:
      $108.81万
    • 财政年份:
      2022
    • 负责人:
      STEVEN A CARR
    • 依托单位:
    海外基金