State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, PR China.
International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai 200438, PR China; National Center for Liver Cancer, Shanghai 201805, PR China.
NanoImpact. 2021 Jan;21:100296. doi: 10.1016/j.impact.2021.100296. Epub 2021 Jan 18.
The clinical needs of rapidly screening liver cancer in large populations have asked for a facile and low-cost point-of-care testing (POCT) method. We present a nanoplasmonics biosensing chip (NBC) that would empower antibody-free detection with simplified analysis procedures for POCT. The cheaply fabricable NBC consists of multiple silver nanoparticle-decorated ZnO nanorods on cellulose filter paper and would enable one-drop blood tests through surface-enhanced Raman spectroscopy (SERS) detection. In this work, utilizing such an NBC and deep neural network (DNN) modeling, a direct serological detection platform was constructed for automatically identifying liver cancer within minutes. This chip could enhance Raman signals enough to be applied to POCT. A classification DNN model was established by spectrum-based deep learning with 1140 serum SERS spectra in equal proportions from hepatocellular carcinoma (HCC) patients and healthy individuals, achieving an identification accuracy of 91% on an external validation set of 100 spectra (50 HCC versus 50 healthy). The intelligent platform, based on the biosensing chip and DNN, has the potential for clinical applications and generalizable use in quickly screening or detecting other types of cancer.
临床需要快速筛查大量人群中的肝癌，因此需要一种简便、低成本的即时检测（POCT）方法。我们提出了一种纳米等离子体生物传感芯片（NBC），它可以通过简化的分析程序实现无抗体检测，从而实现 POCT。这种廉价制造的 NBC 由纤维素滤纸上的多个银纳米颗粒修饰的氧化锌纳米棒组成，通过表面增强拉曼光谱（SERS）检测，可以实现一滴血测试。在这项工作中，利用这种 NBC 和深度神经网络（DNN）建模，我们构建了一个直接的血清学检测平台，可在数分钟内自动识别肝癌。这种芯片可以增强拉曼信号，足以应用于 POCT。通过基于光谱的深度学习，我们建立了一个分类 DNN 模型，该模型使用了来自肝细胞癌（HCC）患者和健康个体的血清 SERS 光谱的 1140 个样本，在 100 个外部验证集（50 个 HCC 与 50 个健康个体）上的识别准确率达到 91%。基于生物传感芯片和 DNN 的智能平台具有临床应用的潜力，并可广泛用于快速筛查或检测其他类型的癌症。
