"Novel Mouse Models for Quantitative Understanding of Baseline and Therapy-Driven Evolution of Prostate Cancer Metastasis"

项目总结/摘要 平均每16分钟就有一名男性死于前列腺癌，主要是由于继发性恶性肿瘤的发展。 在原发癌部位以外的生长，称为转移。PCa治疗的基础是 雄激素剥夺疗法（ADT）。ADT暂时停止PCa，但在几乎所有情况下都会导致耐药性， 导致去势抵抗性PC（CRPC）。CRPC然后经历转移性亚克隆的进一步演变 导致不治之症揭示抗性机制和克隆进化的研究技术 由于目前的动物模型在其体内模拟PCa演变的能力有限， 原生微环境以及追踪亚克隆进化的无效方法。 因此，我们开发了EvoCaP（！前列腺癌的演变”），内源性前列腺癌的小鼠模型。 通过使用在转移性前列腺癌中富集的PTEN/TP 53共缺失， 患者和表型，通过原发性疾病进展到骨、肺、淋巴结的局灶性启动 和肝转移我们的模型使用慢病毒平台- LV.CreBC10，其携带：（1）Cre（Pten/Trp 53 co-）， 缺失; Cas9的激活，荧光和发光标记）;（2）具有十个标记位点的条形码 通过Cas9（BC 10）;（3）特异性标记BC 10的RNA指导;和（4）用于测试的指导或短发夹RNA 转移性驱动因素。发光（FLuc）允许连续跟踪疾病进展和发光 （eGFP）允许对癌细胞进行特异性分选。BC 10代表靶位点的合成阵列，按顺序 对于吸引Cas9产生随后特异性编辑的RNA向导，活性降低。到 为了简化条形码分析，我们建立了一个R软件包- EvoTraceR。这个综合系统 能够：（1）基于原发性和转移中的共同突变模式来分析癌细胞;以及 (2)构建系统发育树，以稳健和灵活的方式跟踪向转移的演变。 我们的中心假设是，不同的分子和表型克隆结构的差异将是 根据治疗状态在原发部位和转移部位之间精确检测， 转移和/或抗性促进基因和途径。我们的分析将建立和机械地 验证Pten/Tp 53丢失（基础）引起的转移性克隆扩增的驱动因素，并研究如何 来自治疗的进化压力（ADT），应用于PCa的不同阶段，导致 抗性克隆然后，我们将使用Cas9/guide（g）RNA和可诱导的短发夹来靶向基因改变， 这些扩增的克隆以鉴定未经治疗的和治疗诱导的PCa转移的驱动因素。 EvoCaP可以可行地跟踪分子进化并验证药物开发的靶点，这可能导致 新的转移驱动基因和途径的鉴定。因此，治疗可应用于：（1）原发性 用于早期检测和阻断转移发展的疾病;和（2）已经存在的转移。 重要的是，该项目开发的技术也可以应用于其他类型的转移性癌症。

PROJECT SUMMARY / ABSTRACT On average, a man dies from PCa every 16 minutes, mainly due to development of secondary malignant growths outside of the primary cancer site, known as metastases. The cornerstone of PCa treatment is androgen deprivation therapy (ADT). ADT temporarily halts PCa, but leads to resistance in nearly all cases, resulting in castration-resistant PC (CRPC). CRPC then undergoes further evolution of metastatic subclones and results in incurable disease. Research techniques revealing resistance mechanisms and clonal evolution of metastatic PCa are lacking due to the limited capacity of current animal models to mimic PCa evolution in its native microenvironment as well as inefficient methods for tracing subclonal evolution. Therefore, we developed EvoCaP (!Evolution in Cancer of the Prostate”), a mouse model of endogenous metastasis that recapitulates human PCa genetically, by using PTEN/TP53 co-deletions enriched in metastatic patients, and phenotypically, by focal initiation of primary disease progressing to bones, lungs, lymph nodes and liver metastases. Our model uses a lentiviral platform - LV.CreBC10 carrying: (1) Cre (Pten/Trp53 co- deletions; activation of Cas9, fluorescence and luminescence markers); (2) Barcode with ten sites for marking by Cas9 (BC10); (3) RNA guide specifically marking BC10; and (4) guide or short hairpin RNA for testing metastatic drivers. Luminescence (FLuc) permits continuous tracking of disease progression and fluorescence (eGFP) allows for specific sorting of cancer cells. BC10 represents a synthetic array of on-target sites, in order of decreasing activity, for the RNA guide that attracts Cas9 to generate subsequently specific edits. To streamline barcode analysis, we have established an R package - EvoTraceR. This comprehensive system enables: (1) the profiling of cancer cells based on shared mutational patterns in primary and metastasis; and (2) the building of phylogenetic trees to track evolution toward metastases in a robust and flexible way. Our central hypothesis is that differences in distinct molecular and phenotypical clonal architectures will be precisely detected between primary and metastatic sites depending on therapy status, enabling the inhibition of metastasis and/or resistance promoting genes and pathways. Our analyses will establish and mechanistically validate drivers of metastatic clonal expansion caused by Pten/Tp53-loss (basal) and also investigate how evolutionary pressure from therapy (ADT), applied at different stages of PCa, leads to the emergence of resistant clones. We will then use Cas9/guide (g)RNA and inducible short hairpins to target genes altered in those expanding clones to identify drivers of both treatment-naive and treatment-induced PCa metastasis. EvoCaP can feasibly track molecular evolution and validate targets for drug development, which may lead to identification of novel metastatic driver genes and pathways. Thus, therapies could be applied in: (1) primary diseases for early detection and interruption of metastases development; and (2) already existing metastases. Importantly, technologies developed in this project can also be applied to other types of metastatic cancers.