Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Lab Chip. 2017 Sep 12;17(18):3086-3096. doi: 10.1039/c7lc00703e.
The use of microtechnology for the highly selective isolation and sensitive detection of circulating tumor cells has shown enormous promise. One challenge for this technology is that the small feature sizes - which are the key to this technology's performance - can result in low sample throughput and susceptibility to clogging. Additionally, conventional molecular analysis of CTCs often requires cells to be taken off-chip for sample preparation and purification before analysis, leading to the loss of rare cells. To address these challenges, we have developed a microchip platform that combines fast, magnetic micropore based negative immunomagnetic selection (>10 mL h) with rapid on-chip in situ RNA profiling (>100× faster than conventional RNA labeling). This integrated chip can isolate both rare circulating cells and cell clusters directly from whole blood and allow individual cells to be profiled for multiple RNA cancer biomarkers, achieving sample-to-answer in less than 1 hour for 10 mL of whole blood. To demonstrate the power of this approach, we applied our device to the circulating tumor cell based diagnosis of pancreatic cancer. We used a genetically engineered lineage-labeled mouse model of pancreatic cancer (KPCY) to validate the performance of our chip. We show that in a cohort of patient samples (N = 25) that this device can detect and perform in situ RNA analysis on circulating tumor cells in patients with pancreatic cancer, even in those with extremely sparse CTCs (<1 CTC mL of whole blood).
微技术在高度选择性的循环肿瘤细胞(CTC)分离和灵敏检测方面具有巨大的应用潜力。该技术面临的一个挑战是,小特征尺寸(是该技术性能的关键)可能导致低样品通量和易堵塞。此外,传统的 CTC 分子分析通常需要将细胞从芯片上取下进行样品制备和纯化,然后进行分析,这导致稀有细胞的丢失。为了解决这些挑战,我们开发了一种微芯片平台,该平台将快速、基于磁微孔的负免疫磁选(>10 mL h)与快速的芯片原位 RNA 分析(比传统 RNA 标记快 100 倍以上)相结合。该集成芯片可以直接从全血中分离稀有循环细胞和细胞簇,并允许对单个细胞进行多种 RNA 癌症生物标志物的分析,在不到 1 小时的时间内即可完成 10 mL 全血的样本到答案。为了证明这种方法的强大功能,我们将我们的设备应用于基于循环肿瘤细胞的胰腺癌诊断。我们使用一种遗传工程谱系标记的胰腺癌小鼠模型(KPCY)来验证我们芯片的性能。我们发现,在一组患者样本(N=25)中,该设备可以检测到并对胰腺癌患者的循环肿瘤细胞进行原位 RNA 分析,即使在 CTC 非常稀少的患者(<1 CTC mL 全血)中也是如此。