Quantifying HER-2 expression on circulating tumor cells by ACCEPT

Circulating tumor cells (CTCs) isolated from blood can be probed for the expression of treatment targets. Immunofluorescence is often used for both the enumeration of CTC and the determination of protein expression levels related to treatment targets. Accurate and reproducible assessment of such treatment target expression levels is essential for their use in the clinic. To enable this, an open source image analysis program named ACCEPT was developed in the EU-FP7 CTCTrap and CANCER-ID programs. Here its application is shown on a retrospective cohort of 132 metastatic breast cancer patients from which blood samples were processed by CellSearch® and stained for HER-2 expression as additional marker. Images were digitally stored and reviewers identified a total of 4084 CTCs. CTC’s HER-2 expression was determined in the thumbnail images by ACCEPT. 150 of these images were selected and sent to six independent investigators to score the HER-2 expression with and without ACCEPT. Concordance rate of the operators’ scoring results for HER-2 on CTCs was 30% and could be increased using the ACCEPT tool to 51%. Automated assessment of HER-2 expression by ACCEPT on 4084 CTCs of 132 patients showed 8 (6.1%) patients with all CTCs expressing HER-2, 14 (10.6%) patients with no CTC expressing HER-2 and 110 (83.3%) patients with CTCs showing a varying HER-2 expression level. In total 1576 CTCs were determined HER-2 positive. We conclude that the use of image analysis enables a more reproducible quantification of treatment targets on CTCs and leads the way to fully automated and reproducible approaches.循环肿瘤细胞（Circulating Tumor Cells, CTCs）是从血液中分离得到的细胞，可用于检测治疗靶点的表达情况。免疫荧光（Immunofluorescence）常被同时用于循环肿瘤细胞的计数，以及与治疗靶点相关的蛋白质表达水平的测定。对这类治疗靶点表达水平进行精准且可重复的评估，是其应用于临床的必要前提。为实现这一目标，研究人员在欧盟第七框架计划（EU-FP7）的CTCTrap与CANCER-ID项目中，开发了一款名为ACCEPT的开源图像分析程序。本研究将该程序的应用场景展示于一项包含132例转移性乳腺癌患者的回顾性队列：所有受试者的血液样本均通过CellSearch®平台进行处理，并针对作为额外标志物的HER-2（Human Epidermal Growth Factor Receptor 2）表达进行染色。所有图像均以数字形式存储，经评审人员共识别出4084个循环肿瘤细胞。研究人员通过ACCEPT程序对缩略图中的循环肿瘤细胞HER-2表达水平进行测定。从中选取150张图像，发送给6名独立研究人员，让其分别在使用和不使用ACCEPT程序的情况下对HER-2表达进行评分。未使用ACCEPT程序时，各操作者对循环肿瘤细胞HER-2表达的评分结果一致性率仅为30%；借助ACCEPT工具后，该一致性率可提升至51%。通过ACCEPT程序对132例患者的4084个循环肿瘤细胞的HER-2表达进行自动化评估后发现：8例（6.1%）患者的所有循环肿瘤细胞均表达HER-2，14例（10.6%）患者未检测到表达HER-2的循环肿瘤细胞，剩余110例（83.3%）患者的循环肿瘤细胞HER-2表达水平存在差异。总计共有1576个循环肿瘤细胞被判定为HER-2阳性。本研究结论表明，图像分析技术可实现循环肿瘤细胞上治疗靶点更具可重复性的定量检测，为全自动化且可重复的检测方法铺平了道路。