Core A: Pathobiology Core

项目概要/摘要 癌症是一种高度异质性的疾病，由一组不同的遗传因子组成并以其为特征。 表型由空间上不同组织的复杂动态细胞相互作用驱动 微环境准确描述这种肿瘤内异质性的能力及其对 转移、治疗抗性以及最终对临床结果的影响仍然是一个挑战。在 此外，肿瘤与其微环境之间相互作用的分子机制是 大部分缺乏。 这个前列腺癌计划项目着手研究肿瘤细胞内在以及间质 和免疫微环境因素在肿瘤进展中的作用。 此外，该计划将采用多学科和整合的方法，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， 对初治、去势抵抗和神经内分泌肿瘤的人体组织样本进行补充分析， 包括局部和转移性。 病理生物学核心（核心A）将通过提供以下方面的专家组织病理学分析来支持这些项目： 小鼠和人肿瘤，验证用于小鼠和人组织的抗体和探针，比较和 对比小鼠模型和患者样品中上皮和微环境中的多种信号。 创新的方法，包括器官型培养和重组实验将被利用， 功能测定最后，改进计算方法中的策略以比较人类单细胞分析， 以及开发新的方法来改善和自动化原位表达模式， 代表了这个核心的创新力量。

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.