Identification of cancer stem cell therapeutic targets

该计划项目拨款是对RFA-CA-08-020号文件的响应，标题为“肿瘤干细胞在癌症生物学中， 最近的证据表明，癌症有一个细胞层次，其中少数癌细胞群体，称为癌症干细胞，驱动肿瘤的生长和扩散。前瞻性地识别致瘤癌细胞的能力将有助于识别 调节患者的生长、转移和生存。以自我更新等基本过程中涉及的途径为目标可能会导致更有效的治疗。这项提案是一系列相互关联的项目，旨在确定针对乳腺癌和白血病干细胞的新的癌症干细胞治疗靶点，并在临床前癌症干细胞模型中测试针对其中一些靶点的药物。我们计划的三个项目如下所示。项目1：乳腺癌干细胞自我更新途径的确定和治疗性药理学干预措施的发展。派·迈克·克拉克，斯坦福大学。项目2：CD47靶向治疗人白血病和其他肿瘤干细胞PI、IRV 韦斯曼，斯坦福大学。项目3：微流控技术用于癌症干细胞的基因表达、染色质结构和体外培养的分子和功能分析。派·史蒂夫·奎克，斯坦福大学。这些项目高度相互联系，相互依赖，才能取得个别项目的成功以及本项目的成功。每个项目将由4个核心支持：一个 行政核心、生物信息学核心、动物模型核心和流式细胞仪核心。

This program project grant is in response to RFA-CA-08-020 entitled "Tumor Stem Cells in Cancer Biology, Prevention, and Therapy". Recent evidence suggests that cancers have a cellular hierarchy in which a minority population of cancer cells, called cancer stem cells, drives the growth and spread of a tumor. The ability to prospectively identify tumorigenic cancer cells will facilitate the identification of pathways that regulate their growth, metastasis and survival in patients. Targeting the pathways involved in essential processes such as self renewal may lead to more effective therapies. This proposal is an interlocking set of projects designed to identify new cancer stem cell therapeutic targets against breast cancer and leukemia stem cells and to test drugs against some of these targets in a preclinical cancer stem cell model. The three projects of our Program are listed below. Project 1: Identification of self-renewal pathways in breast cancer stem cells and development of therapeutic pharmacological interventions. PI Mike Clarke, Stanford University. Project 2: Therapeutic targeting of CD47 on human leukemia and other cancer stem cells PI, Irv Weissman, Stanford University. Project 3: Microfluidic techniques for the molecular and functional analysis of gene expression, chromatin structure and in vitro culturing of cancer stem cells. PI Steve Quake, Stanford University. These projects are highly interconnected and reliant on each other for the success of the individual project as well as the success of this program. Each project will be supported by 4 cores: an administrative core, a bioinformatics core, an animal model core, and a flow cytometry core.