Core A: Pathobiology Core

项目概要/摘要 癌症是一种高度异质性的疾病，由多种遗传因素组成并以多种遗传因素为特征。 由空间上不同的组织内复杂的动态细胞相互作用驱动的表型 微环境。准确描绘肿瘤内异质性的能力及其对 转移、治疗耐药以及最终对临床结果的影响仍然是一个挑战。在 此外，支持肿瘤与其微环境之间相互作用的分子机制是 很大程度上缺乏。 该前列腺癌计划项目旨在研究肿瘤细胞内在以及基质 使用单细胞测序技术研究肿瘤进展中的免疫微环境因素。 此外，该计划将采用多学科和综合方法，旨在整合 基因工程小鼠和类器官模型的单细胞 RNA 测序和系统分析， 对幼稚肿瘤、去势抵抗肿瘤和神经内分泌肿瘤的人体组织样本进行补充分析， 局部和转移性的。 病理生物学核心（核心 A）将通过提供专家组织病理学分析来支持这些项目 小鼠和人类肿瘤，验证用于小鼠和人类组织的抗体和探针，比较和 对比小鼠模型和患者样本中上皮和微环境中的多个信号。 将利用包括器官型培养和重组实验在内的创新方法 功能测定。最后，改进计算方法的策略来比较人类的单细胞分析 和小鼠以及开发新方法来改进和自动化原位表达方式将 代表该核心的创新部门。

Project Summary/Abstract Cancer is a highly heterogenous disease, composed of and characterized by a diverse set of genetic phenotypes driven by complex dynamic cellular interactions within spatially distinct organized microenvironments. The ability to accurately delineate this intra tumor heterogeneity and its contribution to metastasis, therapeutic resistance and ultimately the impact of clinical outcomes, remains a challenge. In addition, the molecular mechanisms underpinning the cross-talk between tumor and its microenvironment are largely lacking. This prostate cancer Program Project sets out to investigate the tumor cell intrinsic as well as stromal and immune microenvironmental factors in tumor progression using single cell sequencing technologies. Additionally, the Program will incorporate a multi-disciplinary and integratory approach that aims to integrate single-cell RNA-sequencing and systems analyses of genetically engineered mouse and organoid models, with complementary analyses of human tissue samples in naïve, castration-resistant and neuroendocrine tumors, both local and metastatic. The Pathobiology Core (Core A) will support the projects by providing expert histopathologic analysis of murine and human tumors, validating antibodies and probes for use in mouse and human tissue, comparing and contrasting multiple signals in epithelium and microenvironment in mouse models and patient samples. Innovative approaches including organotypic cultures and recombination experiments will be utilized as functional assays. Finally, refining strategies in computational methods to compare single cell analyses in human and mouse as well as developing novel approaches to improve and automate in situ expression modalities will represent the innovation arm of this core.