He Liqi, Piao Guanghai, Yin Xu, Feng Jie, Zhang Ting, Hu Caiwei, Bai Yu, Kim Ji Man, Jin Mingshi
Department of Chemistry, Yanbian University, Yanji, 133002, Jilin, China.
Department of Chemistry, Sungkyunkwan University, Suwon, 440-746, Republic of Korea.
Talanta. 2025 May 1;286:127545. doi: 10.1016/j.talanta.2025.127545. Epub 2025 Jan 6.
Exosomes have emerged as a powerful biomarker for early cancer diagnosis, however, accurately detecting cancer-derived exosomes in biofluids remains a crucial challenge. In this study, we present a novel label-free electrochemical biosensor utilizing titanium dioxide nanotube array films (TiONTAs) for the sensitive detection of exosomes in complex biological samples. This innovative biosensor takes advantage of the excellent electrochemical properties of TiONTAs and their specific interactions with the phosphate groups of exosomes. The transport of ions and electrons within the exosome-captured TiO nanotubes is hindered, leading to a significant alteration in the electrochemical response signal and enabling highly sensitive detection of exosomes. Consequently, the biosensor demonstrates a wide linear detection range from 5 × 10 to 1 × 10 particles/μL with a limit of detection of 12.7 particles/μL and 12.6 particles/μL for the exosomes derived from hepatocellular carcinoma and colon cancer cells, respectively. Furthermore, the TiONTAs biosensor can successfully distinguish the signal of extracellular vesicles in real human serum samples between 20 hepatocellular carcinoma, 20 colon cancer and 20 healthy persons (p < 0.0001). This method had a promising potential in biochemical analysis and clinical cancer diagnosis.
外泌体已成为早期癌症诊断的一种强大生物标志物，然而，在生物流体中准确检测癌症来源的外泌体仍然是一项关键挑战。在本研究中，我们提出了一种新型的无标记电化学生物传感器，利用二氧化钛纳米管阵列薄膜（TiONTAs）对复杂生物样品中的外泌体进行灵敏检测。这种创新的生物传感器利用了TiONTAs优异的电化学性质及其与外泌体磷酸基团的特异性相互作用。捕获外泌体的TiO纳米管内离子和电子的传输受到阻碍，导致电化学响应信号发生显著变化，从而能够对外泌体进行高灵敏检测。因此，该生物传感器对源自肝癌细胞和结肠癌细胞的外泌体分别显示出5×10至1×10颗粒/μL的宽线性检测范围，检测限分别为12.7颗粒/μL和12.6颗粒/μL。此外，TiONTAs生物传感器能够成功区分20例肝癌患者、20例结肠癌患者和20例健康人的真实人血清样本中外细胞囊泡的信号（p<0.0001）。该方法在生化分析和临床癌症诊断方面具有广阔的应用前景。
