A transdisciplinary approach for dissecting stem cell states in prostate cancer

项目总结/摘要 了解推动前列腺癌进展的分子机制对治疗前列腺癌具有深远意义。 定义致命前列腺癌的生物学。癌症干细胞模型提出肿瘤内的细胞是 以等级谱系关系组织并显示不同的致瘤潜力。该模型具有 重要的翻译意义，因为它表明有效的治疗应该靶向癌症干细胞 维持肿瘤恶性程度。然而，尽管进行了深入的调查， 前列腺癌干细胞的存在和性质仍然没有解决。识别、表征和 为了治疗这一人群，我们将联合收割机结合癌症干细胞研究人员的专业知识， 计算/数学方法。理论物理学的杠杆技术（随机矩阵 理论）和代数拓扑（拓扑数据分析），我们将提供一个统计框架来剖析一个 分子标记（称为CasPro）参与前列腺肿瘤中的祖细胞活性。我们将实验性地 通过研究前列腺遗传工程小鼠模型中的CasPro-高细胞来验证我们的发现， 癌症和在干细胞活性测定中分析它们的功能特性。这些发现将被 在人前列腺肿瘤样品的研究中进一步得到验证，特别是来自具有治疗抗性的患者的样品。 去势抵抗性前列腺癌（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高细胞的表观基因组景观将确定新的靶点， 治疗，并导致这些目标的新的候选药物。候选药物的进一步开发可能 导致癌症干细胞活性的抑制，从而为CRPC提供潜在的治疗。

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.