A transdisciplinary approach for dissecting stem cell states in prostate cancer

项目摘要/摘要 了解推动前列腺癌进展的分子机制对 定义了致命性前列腺癌的生物学。癌症干细胞模型提出，肿瘤内的细胞是 以等级血统关系组织，并显示出不同的致瘤潜力。这款车有 重要的翻译含义，因为它表明有效的治疗方法应该针对癌症干细胞 维持肿瘤恶性的物质。然而，尽管进行了密集的调查，但关于 前列腺癌干细胞的存在和性质仍未解决。识别、表征和 在治疗方面，我们将把癌症干细胞研究人员的专业知识与 计算/数学方法。利用理论物理中的技术(随机矩阵 理论)和代数拓扑学(拓扑数据分析)，我们将提供一个统计框架来剖析 分子签名(称为CasPro)与前列腺癌的祖细胞活性有关。我们将在实验中 通过研究基因工程小鼠前列腺模型中的CasPro-High细胞来验证我们的发现 并在干细胞活性测定中分析其功能特性。然后，这些发现将被 在对人类前列腺癌样本的研究中进一步验证，特别是来自耐药患者的样本 耐去势前列腺癌(CRPC)。从长远来看，我们预计我们对关键监管机构的研究 干细胞特征以及CasPro-High细胞的表观基因组图谱将确定新的靶点 治疗，并导致针对这些靶点的新候选药物。候选药物的进一步开发可能 导致抑制癌症干细胞活性，从而为CRPC提供潜在的治疗方法。

PROJECT SUMMARY/ABSTRACT Understanding the molecular mechanisms that drive prostate cancer progression has profound significance for defining the biology of lethal prostate cancer. The cancer stem cell model proposes that cells within a tumor are organized in a hierarchical lineage relationship and display different tumorigenic potential. This model has important translational implications since it suggests that effective therapeutics should target cancer stem cells that sustain tumor malignancy. However, despite intensive investigation, long-standing questions about the existence and properties of prostate cancer stem cells remain unresolved. To identify, characterize, and therapeutically target this population, we will combine the expertise of cancer stem cell researchers with computational/mathematical approaches. Leveraging techniques from theoretical physics (Random Matrix Theory) and algebraic topology (Topological Data Analysis), we will provide a statistical framework to dissect a molecular signature (termed CasPro) implicated in progenitor activity in prostate tumors. We will experimentally validate our findings by investigating CasPro-high cells in genetically-engineered mouse models of prostate cancer and analyzing their functional properties in assays of stem cell activities. These findings will then be further validated in studies of human prostate tumor samples, particularly from patients with treatment-resistant castration-resistant prostate cancer (CRPC). In the longer-term, we anticipate that our studies of key regulators of the stem cell signature as well as the epigenomic landscape of CasPro-high cells will identify novel targets for therapy, and lead to novel candidate drugs for these targets. Further development of candidate drugs might result in inhibition of cancer stem cell activity, thereby providing potential treatments for CRPC.