HPASubC: A suite of tools for user subclassification of human protein atlas tissue images.
HPASubC: A suite of tools for user subclassification of human protein atlas tissue images.
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DOI：
10.4103/2153-3539.159213
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发表时间：
2015-01-01
影响因子：
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通讯作者：
Halushka, Marc K
中科院分区：
文献类型：
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作者：
Cornish, Toby C;Chakravarti, Aravinda;Halushka, Marc K
背景技术背景：人类蛋白质图谱（HPA）是一个强大的蛋白质组学工具，用于可视化大多数人体组织和许多常见恶性肿瘤中蛋白质表达的分布。HPA包括来自组织微阵列（TMA）的化学染色图像，涵盖48种组织类型和20种常见恶性肿瘤。TMA数据用于提供组织、细胞和偶尔亚细胞水平的表达信息。HPA还提供了来自三种细胞系的共聚焦免疫荧光数据的亚细胞数据。尽管本地化数据的可用性，许多独特的模式，细胞和亚细胞的表达没有documented.MATERIALS和METHODS：为了得到在这个更细粒度的数据，我们已经开发了一套Python脚本，HPASubC，以帮助亚细胞和细胞类型的特定分类HPA图像。该方法允许用户下载和优化特定HPA TMA图像以供查看。然后，使用一个playstation风格的视频游戏控制器，一个训练有素的观察员可以迅速通过10个步骤的1000的图像，以确定感兴趣的patterns of interests.RESULTS：我们已经成功地使用这种方法来识别703内皮细胞（EC）和/或平滑肌细胞（SMCs）内发现49,200心脏TMA图像的特异性蛋白质。这份名单将有助于我们在细分心脏基因或蛋白质阵列数据到表达的心肌的主要细胞类型之一：肌细胞，SMC或ECs.CONCLUSIONS：机会，以进一步表征独特的染色模式在一系列的人体组织和恶性肿瘤将加速我们的疾病过程的理解，并指出新的标志物在外科病理学组织评价。
BACKGROUND: The human protein atlas (HPA) is a powerful proteomic tool for visualizing the distribution of protein expression across most human tissues and many common malignancies. The HPA includes immunohistochemically-stained images from tissue microarrays (TMAs) that cover 48 tissue types and 20 common malignancies. The TMA data are used to provide expression information at the tissue, cellular, and occasionally, subcellular level. The HPA also provides subcellular data from confocal immunofluorescence data on three cell lines. Despite the availability of localization data, many unique patterns of cellular and subcellular expression are not documented.MATERIALS AND METHODS: To get at this more granular data, we have developed a suite of Python scripts, HPASubC, to aid in subcellular, and cell-type specific classification of HPA images. This method allows the user to download and optimize specific HPA TMA images for review. Then, using a playstation-style video game controller, a trained observer can rapidly step through 10's of 1000's of images to identify patterns of interest.RESULTS: We have successfully used this method to identify 703 endothelial cell (EC) and/or smooth muscle cell (SMCs) specific proteins discovered within 49,200 heart TMA images. This list will assist us in subdividing cardiac gene or protein array data into expression by one of the predominant cell types of the myocardium: Myocytes, SMCs or ECs.CONCLUSIONS: The opportunity to further characterize unique staining patterns across a range of human tissues and malignancies will accelerate our understanding of disease processes and point to novel markers for tissue evaluation in surgical pathology.