Combined SERS Microfluidic Chip with Gold Nanocone Array for Effective Early Lung Cancer in Mice Model

International journal of nanomedicine(2023)

引用 0|浏览0
暂无评分
摘要
Introduction: As the most common malignant tumor in the world, the prognosis of patients with advanced lung cancer remains poor even after treatment. There are many prognostic marker assays available, but there is still more room for the development of highthroughput and sensitive detection of circulating tumor DNA (ctDNA). Surface-enhanced Raman spectroscopy (SERS), a spectroscopic detection method that has received wide attention in recent years, can achieve exponential amplification of Raman signals by using different metallic nanomaterials. Integrating SERS with signal amplification strategy into the microfluidic chip and applying it to ctDNA detection is expected to be an effective tool for the prognosis of lung cancer treatment effect in the future. Methods: To construct a high-throughput SERS microfluidic chip integrated with enzyme-assisted signal amplification (EASA) and catalytic hairpin self-assembly (CHA) signal amplification strategies, using hpDNA-functionalized Au nanocone arrays (AuNCAs) as capture substrates and cisplatin-treated lung cancer mice to simulate the detection environment for sensitive detection of ctDNA in serum of lung cancer patients after treatment. Results: The SERS microfluidic chip constructed by this scheme, with two reaction zones, can simultaneously and sensitively detect the concentrations of four prognostic ctDNAs in the serum of three lung cancer patients with a limit of detection (LOD) as low as the aM level. The results of the ELISA assay are consistent with this scheme, and its accuracy is guaranteed. Conclusion: This high-throughput SERS microfluidic chip has high sensitivity and specificity in the detection of ctDNA. This could be a potential tool for prognostic assessment of lung cancer treatment efficacy in future clinical applications.
更多
查看译文
关键词
circulating tumor DNA, surface-enhanced Raman scattering, lung cancer, AuNCAs, prognostic assessment
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要