Identification of cancer stem cell therapeutic targets

这项计划项目赠款是为了响应RFA-CA-08 - 020题为"肿瘤干细胞在癌症生物学， 预防和治疗”。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。前瞻性鉴定致瘤性癌细胞的能力将有助于鉴定 调节其在患者中的生长、转移和存活。靶向参与自我更新等基本过程的途径可能会导致更有效的治疗。该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鉴定和治疗药理学干预的发展。PI迈克克拉克，斯坦福大学。项目2：CD47对人类白血病和其他癌症干细胞的治疗靶向PI，Irv 韦斯曼，斯坦福大学。项目三：微流控技术用于癌症干细胞基因表达、染色质结构和体外培养的分子和功能分析。PI史蒂夫奎克，斯坦福大学。这些项目高度相互关联，并且相互依赖，以确保单个项目以及该计划的成功。每个项目将得到4个核心的支持： 管理核心、生物信息学核心、动物模型核心和流式细胞术核心。

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.