PO.BCS01.08 · 生物信息与计算
一体化数字病理学比较并对照肾细胞癌组织与配对的患者来源类肿瘤（tumoroids）的肿瘤微环境
All-in-one digital pathology compares and contrasts the tumor microenvironment of renal cell carcinoma tissue with paired, patient derived tumoroids
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
AI驱动的病理学通过高性能的分析能力缩小从发现到诊断的差距，从而推进转化研究。在此，我们利用HALO®/HALO AI定量图像分析平台，比较患者肿瘤样本与相应类肿瘤（tumoroids）的肿瘤微环境（TME）。由原发肿瘤组织（体内）创建的类肿瘤（体外）使肿瘤学领域的研究者能够更准确地复现患者生物标本的TME。与二维细胞培养相比，类肿瘤被认为通过减少对天然组织结构和细胞组成的破坏，更好地模拟生理相关的环境。我们对多重免疫荧光组织进行AI驱动的图像和空间分析，纳入了免疫亚型的生物标志物以及类肿瘤的关键特征，如TME、细胞增殖和免疫谱。样本获取自BioStudies BioImage Archive中编号为S-BIAD1661的研究，包含透明细胞肾细胞癌（ccRCC）样本1。通过将数字病理学技术应用于这些研究方法，我们展示了一套全面而通用的分析工作流程，以应对类肿瘤及其相应患者样本的表征，并强调了这些工具对研究、发现和诊断的影响。Greice Michele Zickuhr、Hazem Abdullah、In Hwa Um、Alexander Laird、Peter Mullen、David J. Harrison和Alison L. Dickson。"Clear Cell Renal Cell Carcinoma Patient-Derived Tumoroids characterisation by Spatial Mass Spectrometry, Histology and Multiplex Immunofluorescence." BioStudies，S-BIAD1661，2025，www.ebi.ac.uk。访问日期2025年9月22日。
查看英文原文 English abstract
AI-powered pathology advances translational research by shrinking the gap from discovery to diagnosis through highly performant analytical capabilities. Here, we utilize the HALO®/HALO AI quantitative image analysis platform to compare the tumor microenvironment (TME) of patient tumor samples and corresponding tumoroids. Tumoroids created (in vitro) from primary tumor tissue (in vivo) allow researchers in the field of oncology to more accurately replicate the TME of patient biological specimens. Tumoroids compared to 2-D cell culture are believed to better mimic the physiologically relevant environment by reducing the destruction of native tissue structure and cellular composition. We perform AI-powered image and spatial analysis on multiplexed immunofluorescent tissues incorporating biomarkers for immune subtypes and key features of tumoroids such as TME, cell proliferation, immune profile. The samples have been obtained from the BioStudies BioImage Archive under the study S-BIAD1661 containing samples of clear cell Renal Cell Carcinoma (ccRCC) 1 . By applying digital pathology techniques to these research approaches, we demonstrate a thorough and versatile analysis workflow to address the characterization of tumoroids and their corresponding patient samples and highlight the impact of these tools on research, discovery and diagnostics. Greice Michele Zickuhr, Hazem Abdullah, In Hwa Um, Alexander Laird, Peter Mullen, David J. Harrison and Alison L. Dickson. "Clear Cell Renal Cell Carcinoma Patient-Derived Tumoroids characterisation by Spatial Mass Spectrometry, Histology and Multiplex Immunofluorescence." BioStudies , S-BIAD1661, 2025, www.ebi.ac.uk. Accessed 22 September 2025.
利益披露 Disclosure
L. Maston,
Indica Labs Employment, Other, Do not use products on or by patients. I do not think this is an ineligible company.
A. L. Ortiz,
Indica Labs Employment, Other, Do not use products on or by patients. I do not think this is an ineligible company.