Immunofluorescence Image Feature Analysis and Phenotype Scoring Pipeline for Distinguishing Epithelial-Mesenchymal Transition.
Immunofluorescence Image Feature Analysis and Phenotype Scoring Pipeline for Distinguishing Epithelial-Mesenchymal Transition.
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DOI：
10.1017/s1431927621000428
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
Weinberg SH
中科院分区：
文献类型：
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作者：
Hirway SU;Hassan NT;Sofroniou M;Lemmon CA;Weinberg SH
上皮-间充质转化(EMT)是一种重要的生物学过程，也与肿瘤转移等病理过程有关，即上皮细胞向间充质细胞转化。我们设计了一种图像分析管道，根据从不同生化标记物的免疫荧光图像中提取的特征，区分由上皮细胞和间充质细胞组成的组织。将乳腺上皮细胞与0(对照组)、2、4和10 ng/mL转化生长因子-β-1(一种成熟的EMT诱导剂)共同培养。通过免疫荧光显微镜固定、染色细胞，并对E-钙粘蛋白、肌动蛋白、纤维连接蛋白和细胞核进行成像。使用特征袋提取在单个细胞标记的不同组合上进行特征选择。对照和高剂量图像组成训练数据集，而中剂量图像组成测试数据集。进行特征距离分析以量化治疗组之间的差异。该管道成功地区分了对照组(上皮细胞)和高剂量组(间充质细胞)，并展示了中等剂量组中EMT过程的进展。定量聚合酶链式反应(QPCR)验证表明，生物标记物的表达测量与特征距离分析有很好的相关性。总体而言，我们确定了用于免疫荧光图像特征提取和量化的图像管道特征，以区分EMT的进展。
Epithelial-Mesenchymal Transition (EMT) is an essential biological process, also implicated in pathological settings such as cancer metastasis, in which epithelial cells transdifferentiate into mesenchymal cells. We devised an image analysis pipeline to distinguish between tissues comprised of epithelial and mesenchymal cells, based on extracted features from immunofluorescence images of differing biochemical markers. Mammary epithelial cells were cultured with 0 (control), 2, 4 or 10 ng/mL TGF-β1, a well-established EMT-inducer. Cells were fixed, stained, and imaged for E-cadherin, actin, fibronectin, and nuclei via immunofluorescence microscopy. Feature selection was performed on different combinations of individual cell markers using a Bag-of-Features extraction. Control and high dose images comprised the training data set, and the intermediate dose images comprised the testing data set. A feature distance analysis was performed to quantify differences between the treatment groups. The pipeline was successful in distinguishing between control (epithelial) and the high dose (mesenchymal) groups, as well as demonstrating progress along the EMT process in the intermediate dose groups. Validation using quantitative PCR (qPCR) demonstrated that biomarker expression measurements were well correlated with the feature distance analysis. Overall, we identified image pipeline characteristics for feature extraction and quantification of immunofluorescence images to distinguish progression of EMT.