Unraveling the regulatory circuits that drive Merkel cell carcinoma

神经内分泌肿瘤发生在多种组织中，包括皮肤、肺、前列腺和胰腺， 常见的神经和内分泌表型。发现它们的致癌机制具有挑战性， 我们无法直接观察肿瘤的形成，以及已建立肿瘤的突变异质性。 与通过随机突变过程产生的肿瘤不同，默克尔细胞癌（MCC）是一种恶性肿瘤。 神经内分泌皮肤癌，可由默克尔细胞多瘤病毒（MCPyV）感染引起， 可以在体外研究机制。MCPyV含有两种致癌基因，小T（ST）和大T（LT）抗原。 ST对细胞迁移的影响和LT对细胞周期的影响是已知的，但还没有全基因组的、定量的研究。 了解ST和LT如何将正常细胞重编程为易于转移的神经内分泌肿瘤。我们 来自表达MCPyV癌基因的正常细胞的初步RNA测序数据表明，LT 在转录上改变侵袭和迁移相关的途径，如WNT和TGF-β信号传导， 这与人类MCC肿瘤和转移瘤中的表达变化相似。利用这个系统，我们可以 还可以测量基因表达动力学，并直接观察分子事件的时间序列 潜在的致癌作用的方式，不能通过静态肿瘤测量单独实现。病毒 因此，MCC的病因学为我们提供了一个独特的机会，系统地研究和量化 调节电路驱动神经内分泌肿瘤的形成和转移。在目标1中，我们将重建主机 MCPyV利用转录网络和信号传导途径来促进细胞运动和侵袭， 确定LT，WNT和TGF-β在促进转移中的作用，并预测最佳策略， 抑制这些机制。与亚利桑那大学的转移专家合作，我们将测试 我们在一系列MCC模型系统中的预测，包括基于细胞的迁移和侵袭测定， 小鼠异种移植研究。在目标2中，我们将测量ST激活的神经调节因子的蛋白质动力学， LT并将它们与基因表达和ATAC-seq数据整合，以构建细胞命运的网络模型 由MCPyV诱导的转变。我们的工作将提供一个系统级的分析监管电路的基础 转移和细胞重编程的神经内分泌肿瘤，并将确定新的治疗默克尔细胞 这可能适用于其他类型的肿瘤。

Neuroendocrine tumors arise in multiple tissues, including the skin, lung, prostate, and pancreas, and share common neural and endocrine phenotypes. Discovering their mechanism of carcinogenesis is challenging due to our inability to directly observe tumor formation, as well as the mutational heterogeneity of established tumors. Unlike tumors that arise through random mutational processes, Merkel cell carcinoma (MCC) is a neuroendocrine skin cancer that can be caused by infection with Merkel cell polyomavirus (MCPyV) and whose mechanisms can be studied in vitro. MCPyV contains two oncogenes, the small T (ST) and large T (LT) antigens. The impact of ST on cell migration and LT on the cell cycle are known, but there is no genome-wide, quantitative understanding of how ST and LT reprogram normal cells into a neuroendocrine tumor prone to metastasis. Our preliminary RNA-sequencing data from normal cells expressing MCPyV oncogenes indicates that LT transcriptionally alters invasion and migration-related pathways such as WNT and TGF-beta signaling, in a manner that is similar to expression changes in human MCC tumors and metastases. Using this system, we can also measure gene expression dynamics and directly observe the temporal sequence of molecular events underlying carcinogenesis in a way that cannot be achieved through static tumor measurements alone. The viral etiology of MCC therefore provides us with a unique opportunity to systematically investigate and quantify the regulatory circuits driving neuroendocrine tumor formation and metastasis. In Aim 1, we will reconstruct the host transcriptional networks and signaling pathways utilized by MCPyV to promote cell motility and invasion, determine the roles of LT, WNT, and TGF-beta in promoting metastasis, and predict the optimal strategy for inhibiting these mechanisms. In collaboration with metastasis experts at the University of Arizona, we will test our predictions in a series of MCC model systems, including cell-based migration and invasion assays and mouse xenograft studies. In Aim 2, we will measure protein dynamics of neural regulators activated by ST and LT and integrate them with gene expression and ATAC-seq data to build a network model of the cell fate transition induced by MCPyV. Our work will provide a systems-level analysis of regulatory circuits underlying metastasis and cellular reprograming in neuroendocrine tumors, and will identify new therapies for Merkel cell carcinoma that may be applicable to other tumor types.