High-Content Imaging & Analysis Core

项目摘要/摘要 高含量成像与分析核心将为SASCO中心的三个项目提供实验性的 以及利用多重荧光显微镜分析不同生物样本的计算资源 并从基于显微镜的图像中提取定量数据。核心将进行开发、验证和应用 高度多路传输(迭代)成像方法，集成跨多个 循环迭代成像，并构建用于图像分析、特征识别和提取的定制工具。 生成的多参数数据集将满足每个项目的特定需求，从而实现模型- 涉及不同癌症驱动因素、信号通路和亚细胞细胞器的实验迭代 多个生物背景。高内容成像和分析核心将由两名调查人员共同领导 (法拉希-西沙尼和罗德)在多路免疫荧光成像、图像方面具有互补的专业知识 分析和数据科学。目标#1将支持开发、验证和应用High 多重免疫荧光染色和成像程序，以测量细胞的分子特征， 亚细胞和细胞器分辨率。这些程序将使有丝分裂信号的分子分析成为可能。 乳腺癌有机体中期染色体的途径和募集模式(项目 1)、结直肠癌细胞和肿瘤的线粒体形态、细胞信号和代谢酶 (项目2)，关键的EGFR信号分子的翻译后修饰，蛋白质-蛋白质相互作用， 以及它们在胶质母细胞瘤细胞中的亚细胞定位(项目3)。AIM#2将定制工具以实现量化 图像分析，包括图像对齐和跟踪、细胞和亚细胞结构的分割，如 以及特征提取和识别。高内容成像和分析核心将提供这三种功能 计划必要的专业知识和工具，以量化有关细胞、培养和组织的信息 用于支持假设生成和模型测试的图像数据，这些假设和模型测试与 萨斯科中心。

PROJECT ABSTRACT/SUMMARY The High-Content Imaging & Analysis Core will provide the three SASCO Center projects with experimental and computational resources to analyze different biological samples by multiplexed fluorescence microscopy and to extract quantitative data from microscopy-based images. The core will develop, validate, and apply highly multiplexed (iterative) imaging approaches, integrate subcellular imaging data collected across multiple rounds of iterative imaging, and build customized tools for image analysis, feature recognition, and extraction. The generated multi-parametric datasets will address specific needs of each project, enabling model- experiment iterations involving diverse cancer drivers, signaling pathways, and subcellular organelles in multiple biological contexts. The High-Content Imaging & Analysis Core will be co-led by two investigators (Fallahi-Sichani and Rohde) with complementary expertise in multiplexed immunofluorescence imaging, image analysis, and data science. Aim #1 will support the development, validation, and application of highly multiplexed immunofluorescence staining and imaging procedures to measure molecular features at cellular, subcellular, and organelle resolution. These procedures will enable the molecular analysis of mitotic signaling pathways and recruitment patterns in metaphase chromosomes derived from breast cancer organoids (Project 1), mitochondrial morphology, cell signaling and metabolic enzymes in colorectal cancer cells and tumors (Project 2), and post-translational modifications of key EGFR signaling molecules, protein-protein interactions, and their subcellular localization in glioblastoma cells (Project 3). Aim #2 will customize tools for quantitative image analysis, including image alignment and tracking, segmentation of cells and subcellular structures, as well as feature extraction and recognition. The High-Content Imaging & Analysis Core will provide all three projects the necessary expertise and tools for quantifying information about cells, cultures, and tissues from image data to support hypothesis generation and model testing related to the overall hypotheses of the SASCO Center.