Ultrafast Cancer Cells Imaging for Liquid Biopsy via Dynamic Self-Assembling Fluorescent Nanoclusters

Lung cancer-specific clinical specimens, such as alveolar lavage fluid, are typically identified by microscopic biopsy, which has limited specificity and sensitivity and is highly susceptible to human manipulation. In this work, we present an ultrafast, specific, and accurate cancer cell imaging strategy based on dynamically self-assembling fluorescent nanoclusters. The presented imaging strategy can be used as an alternative or a complement to microscopic biopsy. First, we applied this strategy to detect lung cancer cells, and established an imaging method that can rapidly, specifically, and accurately distinguish lung cancer cells (e.g., A549, HepG2, MCF-7, Hela) from normal cells (e.g., Beas-2B, L02) in 1 min. In addition, we demonstrated that the dynamic self-assembly process that fluorescent nanoclusters formed by HAuCl4 and DNA are first generated at the cell membrane and then gradually enter the cytoplasm of lung cancer cells in 10 min. In addition, we validated that our method enables the rapid and accurate imaging of cancer cells in alveolar lavage fluid samples from lung cancer patients, whereas no signal was observed in the normal human samples. These results indicate that the dynamic self-assembling fluorescent nanoclusters-based cancer cells imaging strategy could be an effective non-invasive technique for ultrafast and accurate cancer bioimaging during liquid biopsy, thus providing a safe and promising cancer diagnostic platform for cancer therapy.

Automated summary

In this study, an ultrafast, specific, and accurate cancer cell imaging strategy based on dynamically self-assembling fluorescent nanoclusters was developed. It can rapidly and accurately distinguish lung cancer cells from normal cells within 1 minute, and has been validated in alveolar lavage fluid samples from lung cancer patients. This strategy provides a safe and promising cancer diagnostic platform for cancer therapy.