The accurate preoperative diagnosis and tracking of lung adenocarcinoma is hindered by non-targeting and diffusion of dyes used for marking tumors. Hence, there is an urgent need to develop a practical nanoprobe for tracing lung adenocarcinoma precisely even treating them noninvasively. Herein, Gold nanoclusters (AuNCs) conjugate with thyroid transcription factor-1 (TTF-1) antibody, then multifunctional nanoprobe Au-TTF-1 is designed and synthesized, which underscores the paramount importance of advancing the machine learning diagnosis and bioimaging-guided treatment of lung adenocarcinoma. Bright fluorescence (FL) and strong CT signal of Au-TTF-1 set the stage for tracking. Furthermore, the high specificity of TTF-1 antibody facilitates selective targeting of lung adenocarcinoma cells as compared to common lung epithelial cells, so machine learning software Lung adenocarcinoma auxiliary detection system was designed, which combined with Au-TTF-1 to assist the intelligent recognition of lung adenocarcinoma jointly. Besides, Au-TTF-1 not only contributes to intuitive and targeted visualization, but also guides the following noninvasive photothermal treatment. The boundaries of tumor are light up by Au-TTF-1 for navigation, it penetrates into tumor and implements noninvasive photothermal treatment, resulting in ablating tumors in vivo locally. Above all, Au-TTF-1 serves as a key platform for target bio-imaging navigation, machine learning diagnosis and synergistic PTT as a single nanoprobe, which demonstrates attractive performance on lung adenocarcinoma.
Keywords: Bioimaging-guided therapy; Dual-mode bioimaging; Lung adenocarcinoma; Machine learning; Nanoprobe.
© 2024. The Author(s).