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Viability Pathway Models in Prostate Cancer Cells

前列腺癌细胞的活力途径模型

基本信息

批准号：
7670398
负责人：
ALEX CHENCHIK
金额：
$ 15.16万
依托单位：
CELLECTA, INC.
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-08-15 至 2011-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7670398
关键词：
Address Algorithms Androgens Antineoplastic Agents Attention Back Bar Codes Bioinformatics Biological Markers Biological Models Cancer Biology Cancer Model Candidate Disease Gene Cell Line Cell Proliferation Cell Survival Cell model Cells Cessation of life Clinical Collaborations Computer Analysis Computer Simulation Computer software DU145 Data Data Analyses Data Set Databases Development Disease Dissection Drug Delivery Systems Eligibility Determination Epithelial Epithelial Cells Exhibits Funding Gene Expression Gene Targeting Generations Genes Genetic Genetic Screening Genomics Goals Growth Human Information Networks Knowledge LNCaP Laboratories Lentivirus Vector Libraries Literature Malignant Epithelial Cell Malignant Neoplasms Malignant neoplasm of prostate Maps Mediating Messenger RNA Mining Modeling Molecular Molecular Profiling Mus Neoplastic Cell Transformation PC3 cell line Pathway Analysis Pathway interactions Pharmaceutical Preparations Pharmacologic Substance Phase Phase II Clinical Trials Phenotype Process Prostate Prostate carcinoma Protocols documentation Publications Published Comment Publishing RNA Interference Reagent Receptor Cell Research Research Personnel Resources Roswell Park Cancer Institute Screening procedure Signal Pathway Signal Transduction Signal Transduction Pathway Silicon Dioxide Small Business Innovation Research Grant Small Interfering RNA Software Tools Specificity Staging Structure System Technology Tetracyclines Therapeutic Therapeutic Intervention Tissues Translational Research Validation base cancer cell cost design drug discovery experience feeding gene function genome-wide high throughput screening high throughput technology improved knock-down knowledge base loss of function malignant phenotype neoplastic next generation novel novel therapeutics particle predictive modeling programs prototype public health relevance reconstruction research study small hairpin RNA software development success tool tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): Despite the rapid advances in elucidating the molecular basis of cancer, an ostensibly more difficult post-genomic challenge will be the functional annotation of signaling pathways and integration of this information into an operational cell-based model. Unfortunately, this is at present challenging, primarily due to the absence of reliable integrative experimental and bioinformatic toolsets to rapidly delineate and describe signaling networks en masse. RNA interference (RNAi) and expression profiling have proven to be extremely potent and versatile experimental tools to identify and validate molecular components of signal transduction pathways. Despite these successes, high-throughput (HT) RNAi screening and expression profiling are technically challenging and significant limitations in the data analysis, integration, and modeling exist. To address these issues, and to expand on previous program funding, we have developed a novel combined experimental and bioinformatics platform to construct, validate, and model cancer-specific signaling pathways on a genome-wide scale. The ultimate goal of the proposed project is to develop and make commercially available an integrative knowledge database with predictive models of signaling networks specific for proliferation and survival of prostate cancer cells, and software tools for analysis and use of this information in the drug discovery process. Under Phase I funding in collaboration with Roswell Park Cancer Institute, we initially propose to develop and commercialize the HT technology for construction of signaling pathways based on loss-of-function RNAi screening with second generation functionally validated (FV) lentiviral shRNA libraries and validation of key regulators and signaling mechanisms by expression profiling analysis in a panel of pathway-specific shRNA- mediated knock-down cell lines. We propose to use our novel HT RNAi resource to delineate the processes which underlie deregulated proliferation in prostate cancer cells. Then, in conjunction with our bioinformatics collaborators at Ariadne Genomics, Inc., we will compare and combine our findings with the data collected from scientific publications and develop a publicly available knowledge base prototype, and in silica models of signaling networks specifically involved in the control of proliferation and survival of prostate cancer cells. Integrative research combining predictive computational models with heterogeneous experimental data have the potential to greatly simplify validation of tissue-specific signaling networks and significantly impact the molecular dissection of human tumorigenesis mechanisms. This research harbors considerable promise to identify new targets for therapeutic intervention, as well as the development of increasingly relevant paradigms for drug discovery. As a result, we foresee that these toolsets will significantly improve the efficiency, economy, and ease of elucidating and modeling of signal transduction networks that drive neoplastic transformation, and will provide basic researchers with preferred, cost-effective alternatives to existing commercially available reagents and software. PUBLIC HEALTH RELEVANCE: The ultimate goal of the proposed project is to develop and make publicly available new, powerful bioinformatics research tools: a knowledge base of functionally validated pathways specific for and controlling prostate cancer cell viability, and supporting software tools for data analysis and prediction of anti-prostate cancer drug targets. The next generation of genetic screening technology based on functionally validated shRNA libraries will be used to generate data necessary for reconstruction of signaling networks in the prostate cancer cell model. The developed bioinformatics tools and technologies will significantly improve the efficiency of Integrative Cancer Biology translational research related to molecular dissection of diverse human cancer mechanisms, improvement of drug discovery research, and therefore, has major implications for the development of new pharmaceuticals.

描述(申请人提供)：尽管在阐明癌症的分子基础方面取得了快速进展，但一个表面上更困难的后基因组挑战将是信号通路的功能注释以及将这些信息整合到一个可操作的基于细胞的模型中。不幸的是，目前这是具有挑战性的，主要是由于缺乏可靠的综合实验和生物信息学工具集来快速描述和描述整体信令网络。RNA干扰(RNAi)和表达谱分析已被证明是识别和验证信号转导途径的分子成分的极其有效和通用的实验工具。尽管取得了这些成功，但高通量(HT)RNAi筛选和表达谱在技术上具有挑战性，在数据分析、集成和建模方面存在重大限制。为了解决这些问题，并扩大以前的计划资金，我们开发了一个新的联合实验和生物信息学平台，以构建、验证和模拟全基因组范围内的癌症特异性信号通路。拟议项目的最终目标是开发一个综合知识数据库并使其在商业上可用，该数据库具有前列腺癌细胞增殖和存活专用信号网络的预测模型，以及用于在药物发现过程中分析和使用这些信息的软件工具。在与Roswell Park癌症研究所合作的第一阶段资金支持下，我们最初提议开发并商业化HT技术，以构建基于第二代功能验证(FV)慢病毒shRNA文库的功能丧失RNAi的信号通路，并通过在一组途径特异性shRNA介导的击倒细胞系中的表达谱分析来验证关键调节因子和信号机制。我们建议使用我们的新的HTRNAi资源来描述前列腺癌细胞非调控增殖的基础过程。然后，我们将与Ariadne基因组公司的生物信息学合作者一起，将我们的发现与从科学出版物收集的数据进行比较和结合，并开发一个公开可用的知识库原型，以及专门参与控制前列腺癌细胞增殖和生存的信号网络的硅胶模型。将预测计算模型与异质实验数据相结合的综合研究有可能极大地简化组织特异性信号网络的验证，并显著影响人类肿瘤发生机制的分子解剖。这项研究在确定治疗干预的新靶点以及开发与药物发现越来越相关的范例方面有着相当大的希望。因此，我们预计，这些工具箱将显著提高驱动肿瘤转化的信号转导网络的效率、经济性和简便性，并将为基础研究人员提供现有商业试剂和软件的首选、成本效益较高的替代方案。公共卫生相关性：拟议项目的最终目标是开发并公开可用的新的、强大的生物信息学研究工具：前列腺癌细胞活性的特定和控制的功能验证路径的知识库，以及用于抗前列腺癌药物靶点的数据分析和预测的支持软件工具。基于经过功能验证的shRNA文库的下一代基因筛选技术将用于生成重建前列腺癌细胞模型中的信号网络所需的数据。所开发的生物信息学工具和技术将显著提高与多种人类癌症机制的分子解剖相关的整合肿瘤生物学转译研究的效率，改进药物发现研究，因此对新药物的开发具有重要意义。