PO.TB10.06 · 肿瘤生物学
整合苏木精-伊红组织学与多重成像质谱流式技术以对抗体-药物偶联物靶向生物标志物进行空间蛋白质组学分析
Integrating hematoxylin & eosin histology with multiplexed imaging mass cytometry for spatial proteomic profiling of antibody-drug conjugate targeted biomarkers
该海报暂无可下载的资料
AACR 官方页面
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
苏木精和伊红（H&E）染色仍是组织病理学的基石，为组织结构和疾病表征提供必要的形态学背景。然而，传统的 H&E 缺乏提供精准医学应用所需的全面分子洞察的能力。成像质谱流式技术（IMC）通过使用金属标记抗体在亚细胞分辨率下同时检测 40 多种生物标志物来弥补这一空白。与基于荧光的多重技术不同，IMC 是一种定量、高通量的空间蛋白质组学方法，具有巨大的（5 个数量级）线性动态范围，使其成为 ADC 工作的完美搭配。将 IMC 直接应用于经 H&E 处理的切片并对齐所得图像，将组织学的熟悉度与空间蛋白质组学的力量相结合，使研究人员和病理学家能够在不损害组织完整性的情况下将分子数据叠加到常规形态学上。我们实施了一个工作流程，将 H&E 染色切片与靶向抗体-药物偶联物（ADC）开发相关生物标志物的 IMC 抗体板块相整合。基于组织学特征选择感兴趣区域，随后进行 IMC 采集和用于细胞表型分析及空间图谱绘制的计算分析。图像对齐以及 H&E 形态学与 IMC 数据的整合，实现了在同一组织切片上对组织病理学特征与多重蛋白质表达进行空间分辨的关联。使用计算流程，将 H&E 衍生的感兴趣区域与 IMC 分割图对齐，在多样化的组织结构中实现了高配准精度。IMC 使用金属标记的一抗而无需扩增，并保持定量生物标志物强度的灵敏度。定量分析证明了在特定组织学背景下识别和计数表达 ADC 靶标（HER2、TROP2、EGFR 等）细胞的能力，为生物标志物分布的空间模式提供了洞察。总体而言，这一整合工作流程改善了细胞类型注释和空间解读，揭示了仅从形态学无法明显看出的临床相关微环境异质性。将 IMC 与 H&E 组织学整合为 ADC 开发提供了一个强大的平台，提供了将组织结构、生物标志物表达和免疫背景相联系的无与伦比的能力，并能够使用存档材料进行空间蛋白质组学研究。在临床上，这一方法可通过将免疫浸润与靶标表达相关联来为患者分层提供信息、指导 ADC 选择并预测治疗反应，最终支持个性化肿瘤学策略。仅供研究使用。不用于诊断程序。
查看英文原文 English abstract
Hematoxylin and Eosin (H&E) staining remains the cornerstone of histopathology, providing essential morphological context for tissue architecture and disease characterization. However, traditional H&E lacks the ability to deliver comprehensive molecular insights required for precision medicine application. Imaging Mass Cytometry (IMC) addresses this gap by enabling simultaneous detection of 40+ biomarkers at subcellular resolution using metal-tagged antibodies. Unlike fluorescence-based multiplexing, IMC is a quantitative, high-throughput spatial proteomics methodology with a huge (5 orders of magnitude) linear dynamic range, making it a perfect match for ADC work. Applying IMC directly to H&E-processed slides and aligning the resulting images combines the familiarity of histology with the power of spatial proteomics, allowing researchers and pathologists to overlay molecular data on conventional morphology without compromising tissue integrity. We implemented a workflow integrating H&E-stained sections with IMC antibody panels targeting biomarkers relevant to antibody-drug conjugate (ADCs) development. Regions of interest were selected based on histological features, followed by IMC acquisition and computational analysis for cell phenotyping and spatial mapping. Alignment of images and integration of H&E morphology with IMC data enabled spatially resolved correlation of histopathological features with multiplexed protein expression on the same tissue section. Using a computational pipeline, H&E-derived regions of interest were aligned with IMC segmentation maps, achieving high registration accuracy across diverse tissue architectures. IMC uses metal-labeled primary antibodies without amplification and maintains the sensitivity to quantitate the intensity of biomarkers. Quantitative analysis demonstrated the ability to identify and enumerate cells expressing ADC targets (HER2, TROP2, EGFR, etc.) within specific histological contexts, providing insights into spatial patterns of biomarker distribution. Overall, this integrated workflow improved cell-type annotation and spatial interpretation, uncovering clinically relevant microenvironmental heterogeneity not apparent from morphology alone. Integrating IMC with H&E histology provides a powerful platform for ADC development, offering unparalleled capability to link tissue architecture, biomarker expression, and immune contexture and enables the use of archival material for spatial proteomic studies. Clinically, this approach could inform patient stratification, guide ADC selection, and predict therapeutic response by correlating immune infiltration with target expression, ultimately supporting personalized oncology strategies. For Research Use Only. Not for use in diagnostic procedures.
利益披露 Disclosure
N. Zabinyakov, None..
Q. Raza, None.