Bio-Conjugated Magnetic-Fluorescence Nanoarchitectures for the Capture and Identification of Lung-Tumor-Derived Programmed Cell Death Lighand 1-Positive Exosomes

As per the American Cancer Society, lung cancer is the leading cause of cancer-related death worldwide. Since the accumulation of exosomal programmed cell death ligand 1 (PD-L1) is associated with therapeutic resistance in programmed cell death 1 (PD-1) and PD-L1 immunotherapy, tracking PD-L1-positive (PD-L1 (+)) exosomes is very important for predicting anti-PD-1 and anti-PD-L1 therapy for lung cancer. Herein, we report the design of an anti-PD-L1 monoclonal antibody-conjugated magnetic-nanoparticle-attached yellow fluorescent carbon dot (YFCD) based magnetic-fluorescence nanoarchitecture for the selective separation and accurate identification of PD-L1-expressing exosomes. In this work, photostable YFCDs with a good photoluminescence quantum yield (23%) were synthesized by hydrothermal treatment. In addition, nanoarchitectures with superparamagnetic (28.6 emu/g), biocompatible, and selective bioimaging capabilities were developed by chemically conjugating the anti-PD-L1 antibody and YFCDs with iron oxide nanoparticles. Importantly, using human non-small-cell lung cancer H460 cells lines, which express a high amount of PD-L1 (+) exosomes, A549 lung cancer cells lines, which express a low amount of PD-L1 (+) exosomes, and the normal skin HaCaT cell line, which does not express any PD-L1 (+) exosomes, we demonstrate that nanoarchitectures are capable of effectively separating and tracking PD-L1-positive exosomes simultaneously. Furthermore, as a proof-of-concept of clinical setting applications, a whole blood sample infected with PD-L1 (+) exosomes was analyzed, and our finding shows that this nanoarchitecture holds great promise for clinical applications.

Automated summary

According to the American Cancer Society, lung cancer is the leading cause of cancer-related death worldwide. This study reports on the design of a magnetic-fluorescence nanoarchitecture for the selective separation and accurate identification of PD-L1-expressing exosomes. The results show the potential of this nanoarchitecture for clinical applications in predicting and treating lung cancer.