Novel Methods to localize protein-protein interactions in fixed cells and tissues
Novel Methods to localize protein-protein interactions in fixed cells and tissues
批准号:
7613514
负责人:
Seema Agarwal
金额:
$22.34万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-04-11 至 2012-03-31
关键词:
Basic ScienceBiological MarkersCellsDNADevelopmentDiagnosticEngineeringEvolutionGoalsHumanIn SituIn VitroIndividualLocationMalignant NeoplasmsMeasurementMeasuresMetabolicMethodsMolecularMonoclonal AntibodiesOutcomePatientsPharmaceutical PreparationsPhenotypePlayProcessProteinsRoleSamplingSolutionsSpecimenSpeedTestingTissue SampleTissuescarcinogenesiscell fixingcell typeimprovedneoplastic cellnovelprognosticprotein expressionprotein protein interactionresponsetumor
中文摘要
描述(由申请人提供):虽然DNA, RNA和蛋白质表达的分析可以阐明细胞的表型,但最终决定代谢功能的是蛋白质之间的相互作用。了解蛋白质之间的相互作用对癌症的研究至关重要,而大多数新的化疗药物的目的是破坏异常的相互作用。患者样本中肿瘤生物标志物定量的最新进展显示了预测患者预后和治疗反应的巨大希望。然而,目前还没有很好的方法来评估组织样品中蛋白质的共定位。生物特异性治疗和相关药物诊断的成功发展可能最终需要对每个患者肿瘤内蛋白质-蛋白质相互作用进行定量测量。从基础科学的角度来看,肿瘤样品中蛋白共定位的新方法将促进对癌变的理解和靶向治疗的后续发展。我们假设,工程稳健的方法来评估人类肿瘤样品中的蛋白质-蛋白质相互作用将显著改善患者标本的分析,并最终加快靶向患者特异性治疗的发展。蛋白质的相互作用是驱动细胞的齿轮。在肿瘤细胞中,许多这些过程都被破坏了。今天,我们可以研究患者肿瘤样本中单个蛋白质的表达;然而,我们无法观察这些蛋白质在患者肿瘤中的相互作用。我们的目标是创造新的方法来识别和研究这种相互作用。我们希望这些方法能提高我们对癌症的理解,并提供评估哪些肿瘤对特定疗法有反应的手段。
英文摘要
DESCRIPTION (provided by applicant): Although analyses of DNA, RNA, and protein expression can elucidate the phenotype of a cell, ultimately it is the interactions between proteins that determine metabolic function. Understanding protein-protein interactions is vital to the study of cancer, and the aim of most new chemotherapeutic drugs is to disrupt aberrant interactions. Recent advances in the quantification of tumor biomarkers in patient samples show great promise in predicting patient outcome and response to treatment. However, there is no good way to assess the co-localization of proteins in tissue samples. The successful evolution of bio-specific therapies and associated pharmaco-diagnostics may ultimately require quantitative measures of protein-protein interactions within each patient's tumor. From the basic science perspective, new methods in co-localizing proteins in tumor samples will advance the understanding of carcinogenesis and the subsequent development of targeted therapies. We hypothesize that engineering robust methods for assessing protein-protein interactions in human tumor samples will significantly improve the analysis of patient specimens and ultimately speed the development of targeted patient-specific therapies. Protein interactions are the gears which drive cells. In tumor cells, many of these processes are corrupted. Today, we can study the expression of individual proteins in patient tumor samples; however, we cannot look at the interactions between these proteins in patient tumors. Our goal is to create new methods for recognizing and studying such interactions. We hope that these methods will improve our understanding of cancer and provide means to assess which tumors will respond to specific therapies.
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