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，涉及大量的基质细胞、免疫细胞、 在某些情况下，共存的微生物。复杂肿瘤微环境的一个范例 相互作用是外周T细胞淋巴瘤、侵袭性和基因复杂的肿瘤，其中肿瘤细胞通常 构成一个少数族裔细胞群体。外周T细胞淋巴瘤常与 爱泼斯坦-巴尔病毒，其在疾病中的作用在很大程度上尚不清楚。我们已经证明了 特定的巨噬细胞群和病毒转录程序与生存相关。但是，如何 肿瘤和微环境共同进化并决定预后？我们的项目目标是确定肿瘤的特征- 外周T细胞淋巴瘤的微环境相互作用和共同进化 来自最近发展的小鼠模型的转录数据和纵向单细胞测序数据。我们会 提出了一种基于随机矩阵理论和拓扑数据分析的建模方法 肿瘤微环境演变方面。我们将进一步部署我们的实验室开发的方法用于In Silico 病原体检测研究EB病毒与外周T细胞淋巴瘤的相互作用 淋巴瘤的发生和发展。成功完成我们的目标将提供一个一般性的，试验性的 在单细胞上发现肿瘤-微环境相互作用的动力学本质的有效策略 具有复杂间质成分的肿瘤类型的分辨率。此外，我们的方法将有助于发现新的 支持淋巴瘤细胞生长的微环境驱动的靶点，具有潜在的治疗意义 治疗这种致命疾病。

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.