Single-cell characterization of tumor and microenvironment co-evolution in Peripheral T-cell Lymphomas

项目摘要 肿瘤和微环境构成复杂的生态系统，涉及大量基质细胞，免疫细胞， 在某些情况下，还有共存的微生物。复杂肿瘤微环境的典型例子 相互作用是外周T细胞淋巴瘤，侵袭性和遗传复杂的肿瘤，其中肿瘤细胞经常 构成少数细胞群体。外周T细胞淋巴瘤通常与以下情况相关： EB病毒，其在疾病中的作用在很大程度上仍不明确。我们已经证明， 特定巨噬细胞群体和病毒转录程序与存活相关。但是， 肿瘤和微环境共同进化并告知预后？我们的项目目标是描述肿瘤的特征- 外周T细胞淋巴瘤的微环境相互作用和协同进化 转录组学数据和来自最近开发的小鼠模型的纵向单细胞测序数据。我们将 开发一种基于随机矩阵理论和拓扑数据分析的方法， 肿瘤微环境的演变。我们将进一步部署我们的实验室开发的方法， 病原体检测，以研究EB病毒与外周T细胞淋巴瘤之间的相互作用 淋巴瘤发生和进展。成功完成我们的目标将提供一个普遍的，实验性的 验证策略，以揭示肿瘤微环境相互作用的动态性质，在单细胞 具有复杂基质成分的肿瘤类型的消退。此外，我们的方法将有助于发现新的 微环境驱动的支持淋巴瘤细胞生长的靶点，对淋巴瘤的治疗具有潜在的意义。 治疗这种致命的疾病。

Project Summary Tumor and microenvironment constitute complex ecologies involving a multitude of stromal cells, immune cells, and in some cases coexisting microbes. A paradigmatic example of complex tumor-microenvironment interactions are peripheral T-cell lymphomas, aggressive and genetically complex tumors where tumor cells often constitute a minority cell population. Peripheral T-cell lymphomas are frequently associated with the presence of Epstein-Barr virus whose role in the disease remains largely uncharacterized. We have shown that the presence of specific macrophage populations and viral transcriptional programs are associated to survival. But, how do tumor and microenvironment coevolve and inform prognosis? Our project goal is to characterize the tumor- microenvironment interactions and coevolution in peripheral T-cell lymphomas using large collections of human transcriptomic data and longitudinal single-cell sequencing data from recently developed mouse models. We will develop an approach based on random matrix theory and topological data analysis for modelling the continuous aspect of tumor microenvironment evolution. We will further deploy our lab-developed methodology for in silico pathogen detection to study the interactions between the Epstein-Barr virus and peripheral T-cell lymphoma lymphomagenesis and progression. Successful completion of our goals will provide a general, experimentally validated strategy to uncover the dynamical nature of tumor-microenvironment interactions at the single-cell resolution in tumor types with complex stromal component. Additionally, our approach will help uncover new microenvironment driven targets supporting lymphoma cell growth, with potential therapeutic implications for the treatment of this deadly disease.