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Deriving Combinatorial Strategies for Therapy of Pancreatic Cancer

制定胰腺癌治疗的组合策略

基本信息

批准号：
7255944
负责人：
MICHAEL A. WHITE
金额：
$ 12.56万
依托单位：
UT SOUTHWESTERN MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-06-01 至 2009-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7255944
关键词：
3-Dimensional Adherent Culture Adoption Animal Model Apoptosis Automobile Driving Cell Communication Cell Line Cell Survival Cells Classification Complex Coupled Dependency Development Drug Combinations Drug resistance Ductal Epithelium Effectiveness Epithelial Cells Epithelium Event Exposure to Extracellular Matrix Gene Targeting Genes Genetic Genome Goals Hand Human Intervention Libraries Malignant Neoplasms Malignant neoplasm of pancreas Mediating Modeling Molecular Molecular Analysis Molecular Target Monitor Neck Normal Cell Normal tissue morphology Oncogenes Oncogenic Pancreas Pancreatic Adenocarcinoma Pathway interactions Pharmaceutical Preparations Pharmacotherapy Population Heterogeneity Pre-Clinical Model Prevention strategy Proteins Recruitment Activity Refractory Regulation Research Research Personnel Rolfing Scientist Screening procedure Signal Transduction Small Interfering RNA Stromal Cells System Testing Tissues Toxic effect Translations Treatment Protocols Xenograft Model Xenograft procedure anti-cancer therapeutic base cancer cell cell behavior chemotherapeutic agent combinatorial coping cyclopamine design high throughput screening interest killings loss of function monolayer mouse model neoplastic cell novel novel therapeutics response therapeutic target tumor tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): The cell autonomous molecular events that drive the initiation and progression of pancreatic cancers are multifarious and complex. This context makes identification of effective intervention and prevention strategies a seemingly daunting task. However, widespread evidence suggests that a unifying principle governing formation of a "minimal oncogenic platform" is the co-dependent aberrant regulation of core machinery driving proliferation and suppressing apoptosis. Linchpin proteins recruited to drive these pathways during tumorigenesis likely represent optimal intervention targets in a heterogeneous population of cancer cells. We have established that high-throughput siRNA-mediated loss-of-function analysis can reveal novel linchpin proteins selectively supporting the survival of cancer cells versus normal epithelia. This approach can now be pursued on a genome-wide scale for an unbiased comprehensive analysis of the molecular framework supporting pancreatic cancer cell survival. Here we will combine an in-hand arrayed genome-wide human siRNA library with high-throughput cell-based screening platforms for broad-spectrum identification of optimal genetic targets for focused development of effective chemotherapeutic agents. Our goal is the identification of optimal molecular targets to help guide rational design of novel combinatorial drug-based therapies for human pancreatic cancer. Our immediate objective is to advance this goal by the comprehensive identification of genes that support drug resistance in treatment-refractory human pancreatic cancer cells. Agents that target these gene products or the pathways they regulate will be prime candidates for effective multi-drug therapies. Our approach is to combine a genome-wide siRNA array with a validated high-throughput cell-based screening platform to identify gene targets that expose enhanced-sensitivity to known chemotherapeutic compounds. Our Specific Aims are: 1) To identify molecular targets selectively supporting drug resistance in human pancreatic cell lines, and 2) To validate the effectiveness of candidate targets within an orthotopic xenograft model of pancreatic cancer. The approach we describe here will facilitate the unambiguous identification of linchpin proteins selectively required for survival of pancreatic cancer cells upon exposure to gemcitibine orcyclopamine, two drugs respectively representing the commonly used but less-than-effective current therapy versus an effective agent in preclinical models yet to be tested in humans. This information will 1) guide rational selection of available drugs and drug combinations for development of new intervention and/or prevention strategies, and 2) help identify novel pharmaceutically tractable therapeutic targets whose inhibition will have minimal impact on normal cells.

描述（由申请人提供）：驱动胰腺癌发生和进展的细胞自主分子事件是多样和复杂的。在这种情况下，确定有效的干预和预防战略似乎是一项艰巨的任务。然而，广泛的证据表明，一个统一的原则，形成一个“最小的致癌平台”是共同依赖的异常调节核心机制驱动增殖和抑制凋亡。在肿瘤发生过程中被招募来驱动这些通路的关键蛋白可能代表了异质性癌细胞群体中的最佳干预靶点。我们已经确定，高通量siRNA介导的功能丧失分析可以揭示新的关键蛋白，选择性地支持癌细胞相对于正常上皮细胞的存活。这种方法现在可以在全基因组范围内进行，用于对支持胰腺癌细胞存活的分子框架进行无偏见的全面分析。在这里，我们将结合联合收割机的手阵列全基因组的人类siRNA文库与高通量的基于细胞的筛选平台，用于广谱鉴定最佳的遗传靶点，集中开发有效的化疗药物。我们的目标是确定最佳的分子靶点，以帮助指导合理设计新的组合药物为基础的治疗人类胰腺癌。我们的近期目标是通过全面鉴定支持治疗难治性人胰腺癌细胞耐药性的基因来推进这一目标。靶向这些基因产物或它们调节的途径的药物将是有效的多药物疗法的主要候选者。我们的方法是联合收割机将全基因组siRNA阵列与经验证的高通量细胞筛选平台相结合，以鉴定对已知化疗化合物具有增强敏感性的基因靶点。我们的具体目标是：1）鉴定在人胰腺细胞系中选择性支持耐药性的分子靶标，和2）验证候选靶标在胰腺癌原位异种移植模型中的有效性。我们在这里描述的方法将有助于明确识别关键蛋白的选择性所需的胰腺癌细胞的生存后，暴露于吉西替宾或环巴胺，两种药物分别代表常用的，但低于有效的当前治疗与有效的药物在临床前模型中尚未在人类中进行测试。这些信息将1）指导合理选择可用的药物和药物组合，以开发新的干预和/或预防策略，以及2）帮助识别新的药学上易处理的治疗靶点，其抑制对正常细胞的影响最小。