PROTEOME SIGNATURES AND TARGET VALIDATION IN LYMPHOMAS

淋巴瘤的蛋白质组特征和靶标验证

基本信息

批准号：
7622961
负责人：
Daniel G. Jay
金额：
$ 65.86万
依托单位：
TUFTS UNIVERSITY BOSTON
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-05-01 至 2010-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7622961
关键词：
Address Antibodies Antigens Apoptosis Biological Assay Biological Markers Biological Models Cell Count Cell Line Cell Survival Cells Classification Combination Chemotherapy Complement Custom Development Disease Doxorubicin Drug Combinations End Point Funding Gene Expression Profile Genetic Goals In Vitro Libraries Link Lymphoma Malignant Neoplasms Mass Spectrum Analysis Measures Methods Modeling Mouse Cell Line Mus Mutation Oncogenic PTEN gene Patients Phage Display Pharmaceutical Preparations Pharmacogenomics Phase Positioning Attribute Predictive Value Predictive Value of Tests Primary Neoplasm Proteins Proteome Proteomics Research Role Route Sampling Surface Surface Antigens TP53 gene Technology Testing Therapeutic Thymic Lymphoma Thymic Tissue Tissue Sample Tissues Transgenic Organisms Treatment Efficacy Treatment Protocols Tumor Burden Tumor Tissue Uncertainty Validation Work base chemotherapy drug discovery drug efficacy drug sensitivity falls immunocytochemistry in vivo mouse model neoplastic cell novel outcome forecast response therapeutic target therapy design tumor

项目摘要

DESCRIPTION (provided by applicant): To address tumor diversity and their varied responses to chemotherapy, we require the ability to custom design treatment for each tumor. The goal of pharmacogenomics is to generate gene expression signatures for tissue using microarrays that are then correlated with prognosis or response to therapeutics. However, much of the complexity and diversity of response may be due to proteomic differences. Thus far, probing for proteomic diversity and linking this to therapeutic efficacy has been difficult. Our overall goals are to develop surface proteome signatures (SPS) and perform functional proteomic target validation analysis directly on primary tumor tissue. There is a great need to assess the efficacy of different chemotherapy combinations directly on patient tissue samples. A major difficulty is this respect is our inability to assess the small amounts of primary tumor tissue available from patient-derived samples. As part of our previous IMAT-funded research, we developed a library of single chain (scFv) phage display antibodies that recognize approximately 500 components of the surface proteome. In this work we also developed high-throughput methods for immunocytochemistry (ICC) using scFvs and apoptosis assays that use small number of cells (< 500) per assay. Together, these developments allow us to generate SPS and measure apoptosis after chemotherapy treatment using small amounts of primary tumor tissue. Cells will be tested with a battery of drugs alone and in combination and analyzed for apoptosis. Thus, a differential response to therapeutics will be correlated with a SPS. We will develop and test these assays in the R21 phase using thymic lymphoma mouse cell lines derived from three mouse models: transgenic MyrAkt and two genetic deletions, PTEN-/+ or p53-/-. This is an ideal model system, as the primary tumors are genetically defined by single oncogenic mutations. We will establish SPS for cell lines derived from thymic lymphoma lines from these mice. We will test for the efficacy of different drug regimens to obtain the optimum combination for inducing apoptosis of the cells. We will then test these drug combinations in primary tumor tissue from MyrAkt mice. We will also address the causal link between SPS and drug response and will test the functional role of scFvs that are biomarker candidates. In the R33 phase we will test the predicted optimal drug regimen on thymic lymphomas in the three mouse models, examining tumor load and survival. We will also characterize ten of the scFvs as potential biomarkers or targets for drug discovery. Our studies complement pharmacogenomics and provide a novel route to pharmacoproteomics.

描述（由申请人提供）：为了解决肿瘤多样性及其对化学疗法的各种反应，我们需要为每个肿瘤定制设计治疗的能力。药物基因组学的目的是使用微阵列与预后或对治疗剂的反应相关的微阵列产生基因表达特征。但是，许多复杂性和反应多样性可能是由于蛋白质组学差异所致。到目前为止，很难探测蛋白质组学多样性并将其与治疗功效联系起来。我们的总体目标是开发表面蛋白质组特征（SPS），并直接对原发性肿瘤组织进行功能性蛋白质组学靶向验证分析。非常需要评估直接对患者组织样品的不同化学疗法组合的疗效。一个主要的困难是我们无法评估少量的原发性肿瘤组织可从患者衍生的样品中获得。作为我们以前由IMAT资助的研究的一部分，我们开发了一个单链（SCFV）噬菌体库，显示抗体，该抗体识别表面蛋白质组的大约500个成分。在这项工作中，我们还使用SCFV和凋亡测定法开发了用于免疫细胞化学化学（ICC）的高通量方法，每种测定使用少量细胞（<500）。这些发展使我们能够使用少量的原发性肿瘤组织产生SPS并测量化学疗法治疗后的凋亡。细胞将单独使用一系列药物进行测试，并结合使用并分析凋亡。因此，对治疗剂的差异反应将与SPS相关。我们将使用源自三种小鼠模型的胸腺淋巴瘤小鼠细胞系在R21期开发和测试这些测定法：转基因myrakt和两个遗传缺失，PTEN-/+或p53 - / - 。这是一个理想的模型系统，因为原发性肿瘤是由单个致癌突变遗传定义的。我们将建立来自这些小鼠胸腺淋巴瘤系的细胞系SP。我们将测试不同药物方案的功效，以获得诱导细胞凋亡的最佳组合。然后，我们将在Myrakt小鼠的原发性肿瘤组织中测试这些药物组合。我们还将解决SPS与药物反应之间的因果关系，并将测试生物标志物候选物的SCFV的功能作用。在R33阶段，我们将在三种小鼠模型中测试胸腺淋巴瘤上预测的最佳药物方案，以检查肿瘤负荷和存活率。我们还将将十个SCFV描述为潜在的生物标志物或药物发现的靶标。我们的研究补充了药物基因组学，并为药物蛋白质组学提供了新的途径。