Krajewska Maryla, Smith Layton H, Rong Juan, Huang Xianshu, Hyer Marc L, Zeps Nikolajs, Iacopetta Barry, Linke Steven P, Olson Allen H, Reed John C, Krajewski Stan
Burnham Institute for Medical Research, La Jolla, California 92037, USA.
J Histochem Cytochem. 2009 Jul;57(7):649-63. doi: 10.1369/jhc.2009.952812. Epub 2009 Mar 16.
Cell death is of broad physiological and pathological importance, making quantification of biochemical events associated with cell demise a high priority for experimental pathology. Fibrosis is a common consequence of tissue injury involving necrotic cell death. Using tissue specimens from experimental mouse models of traumatic brain injury, cardiac fibrosis, and cancer, as well as human tumor specimens assembled in tissue microarray (TMA) format, we undertook computer-assisted quantification of specific immunohistochemical and histological parameters that characterize processes associated with cell death. In this study, we demonstrated the utility of image analysis algorithms for color deconvolution, colocalization, and nuclear morphometry to characterize cell death events in tissue specimens: (a) subjected to immunostaining for detecting cleaved caspase-3, cleaved poly(ADP-ribose)-polymerase, cleaved lamin-A, phosphorylated histone H2AX, and Bcl-2; (b) analyzed by terminal deoxyribonucleotidyl transferase-mediated dUTP nick end labeling assay to detect DNA fragmentation; and (c) evaluated with Masson's trichrome staining. We developed novel algorithm-based scoring methods and validated them using TMAs as a high-throughput format. The proposed computer-assisted scoring methods for digital images by brightfield microscopy permit linear quantification of immunohistochemical and histochemical stainings. Examples are provided of digital image analysis performed in automated or semiautomated fashion for successful quantification of molecular events associated with cell death in tissue sections.
细胞死亡具有广泛的生理和病理重要性，因此对与细胞死亡相关的生化事件进行量化是实验病理学的首要任务。纤维化是涉及坏死性细胞死亡的组织损伤的常见后果。我们使用创伤性脑损伤、心脏纤维化和癌症的实验小鼠模型的组织标本，以及以组织微阵列（TMA）形式组装的人类肿瘤标本，对表征与细胞死亡相关过程的特定免疫组织化学和组织学参数进行了计算机辅助量化。在本研究中，我们展示了用于颜色反卷积、共定位和核形态测定的图像分析算法在表征组织标本中细胞死亡事件方面的实用性：（a）进行免疫染色以检测裂解的半胱天冬酶-3、裂解的聚（ADP-核糖）-聚合酶、裂解的核纤层蛋白-A、磷酸化的组蛋白H2AX和Bcl-2；（b）通过末端脱氧核苷酸转移酶介导的dUTP缺口末端标记测定法进行分析以检测DNA片段化；（c）用Masson三色染色法进行评估。我们开发了基于算法的新型评分方法，并使用TMA作为高通量形式对其进行了验证。所提出的通过明场显微镜对数字图像进行计算机辅助评分的方法允许对免疫组织化学和组织化学染色进行线性量化。提供了以自动或半自动方式进行数字图像分析以成功量化组织切片中与细胞死亡相关的分子事件的示例。
