Jou Hei-Jen, Chou Li-Yun, Chang Wen-Chun, Ho Hsin-Cheng, Zhang Wan-Ting, Ling Pei-Ying, Tsai Ko-Hsin, Chen Szu-Hua, Chen Tze-Ho, Lo Pei-Hsuan, Chen Ming, Hsu Heng-Tung
Departments of Obstetrics and Gynecology, Taiwan Adventist Hospital, Taipei 105, Taiwan.
Departments of Obstetrics and Gynecology, National Taiwan University Hospital, Taipei 100, Taiwan.
Micromachines (Basel). 2021 Apr 21;12(5):473. doi: 10.3390/mi12050473.
Circulating tumor cell (CTC) test is currently used as a biomarker in cancer treatment. Unfortunately, the poor reproducibility and limited sensitivity with the CTC detection have limited its potential impact on clinical application. A reliable automated CTC detection system is therefore needed. We have designed an automated microfluidic chip-based CTC detection system and hypothesize this novel system can reliably detect CTC from clinical specimens. SKOV3 ovarian cancer cell line was used first to test the reliability of our system. Ten healthy volunteers, 5 patients with benign ovarian tumors, and 8 patients with epithelial ovarian cancer (EOC) were recruited to validate the CTC capturing efficacy in the peripheral blood. The capture rates for spiking test in SKOV3 cells were 48.3% and 89.6% by using anti-EpCAM antibody alone and a combination of anti-EpCAM antibody and anti-N-cadherin antibody, respectively. The system was sensitive to detection of low cell count and showed a linear relationship with the cell counts in our test range. The sensitivity and specificity were 62.5% and 100% when CTC was used as a biomarker for EOC. Our results demonstrated that this automatic CTC platform has a high capture rate and is feasible for detection of CTCs in EOC.
循环肿瘤细胞(CTC)检测目前在癌症治疗中用作生物标志物。不幸的是,CTC检测的重现性差和灵敏度有限,限制了其在临床应用中的潜在影响。因此,需要一种可靠的自动化CTC检测系统。我们设计了一种基于微流控芯片的自动化CTC检测系统,并假设这种新型系统能够可靠地从临床标本中检测出CTC。首先使用SKOV3卵巢癌细胞系来测试我们系统的可靠性。招募了10名健康志愿者、5名患有良性卵巢肿瘤的患者和8名上皮性卵巢癌(EOC)患者,以验证外周血中CTC的捕获效率。单独使用抗EpCAM抗体和抗EpCAM抗体与抗N-钙黏蛋白抗体组合时,SKOV3细胞加标试验的捕获率分别为48.3%和89.6%。该系统对低细胞计数检测敏感,并且在我们的测试范围内与细胞计数呈线性关系。当将CTC用作EOC的生物标志物时,灵敏度和特异性分别为62.5%和100%。我们的结果表明,这种自动化CTC平台具有高捕获率,并且对于检测EOC中的CTC是可行的。