Ultrasensitive PD-L1-Expressing Exosome Immunosensors Based on a Chemiluminescent Nickel-Cobalt Hydroxide Nanoflower for Diagnosis and Classification of Lung Adenocarcinoma.
Manli WangJiangnan ShuYisha WangWencan ZhangKeying ZhengShengnian ZhouDongliang YangHua CuiPublished in: ACS sensors (2024)
Programmed death ligand-1 (PD-L1)-expressing exosomes are considered a potential marker for diagnosis and classification of lung adenocarcinoma (LUAD). There is an urgent need to develop highly sensitive and accurate chemiluminescence (CL) immunosensors for the detection of PD-L1-expressing exosomes. Herein, N-(4-aminobutyl)-N-ethylisopropanol-functionalized nickel-cobalt hydroxide (NiCo-DH-AA) with a hollow nanoflower structure as a highly efficient CL nanoprobe was synthesized using gold nanoparticles as a "bridge". The resulting NiCo-DH-AA exhibited a strong and stable CL emission, which was ascribed to the exceptional catalytic capability and large specific surface area of NiCo-DH, along with the capacity of AuNPs to facilitate free radical generation. On this basis, an ultrasensitive sandwich CL immunosensor for the detection of PD-L1-expressing exosomes was constructed by using PD-L1 antibody-modified NiCo-DH-AA as an effective signal probe and rabbit anti-CD63 protein polyclonal antibody-modified carboxylated magnetic bead as a capture platform. The immunosensor demonstrated outstanding analytical performance with a wide detection range of 4.75 × 10 3 -4.75 × 10 8 particles/mL and a low detection limit of 7.76 × 10 2 particles/mL, which was over 2 orders of magnitude lower than the reported CL method for detecting PD-L1-expressing exosomes. Importantly, it was able to differentiate well not only between healthy persons and LUAD patients (100% specificity and 87.5% sensitivity) but also between patients with minimally invasive adenocarcinoma and invasive adenocarcinoma (92.3% specificity and 52.6% sensitivity). Therefore, this study not only presents an ultrasensitive and accurate diagnostic method for LUAD but also offers a novel, simple, and noninvasive approach for the classification of LUAD.
Keyphrases
- label free
- molecularly imprinted
- mesenchymal stem cells
- highly efficient
- reduced graphene oxide
- quantum dots
- loop mediated isothermal amplification
- stem cells
- sensitive detection
- minimally invasive
- machine learning
- gold nanoparticles
- deep learning
- real time pcr
- squamous cell carcinoma
- metal organic framework
- ejection fraction
- high resolution
- living cells
- newly diagnosed
- risk assessment
- high throughput
- wastewater treatment
- mass spectrometry
- rectal cancer
- aqueous solution
- liquid chromatography
- amino acid