Identification of programmed death ligand-1 positive exosomes in breast cancer based on DNA amplification-responsive metal-organic frameworks

微泡 乳腺癌 外体 生物传感器 癌症研究 液体活检 化学 DNA 癌症 计算生物学 分子生物学 生物 医学 内科学 生物化学 小RNA 基因
作者
Ya Cao,Ying Wang,Xiaomeng Yu,Xihui Jiang,Gang Li,Jing Zhao
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:166: 112452-112452 被引量:75
标识
DOI:10.1016/j.bios.2020.112452
摘要

Cancer-derived exosomes have recently emerged as potent candidates for diagnosis and prognosis of breast cancer. As an example, programmed death ligand-1 positive (PD-L1+) exosomes are found to be correlated with the progression and immunotherapy response of breast cancer, and therefore show great potential in liquid biopsy. Herein, we propose an electrochemical biosensing method for accurate identification of PD-L1+ exosomes by using DNA amplification-responsive metal-organic frameworks, PVP@HRP@ZIF-8. Specially, PD-L1+ exosomes are captured by anti-CD63 functionalized magnetic beads and bound with anti-PD-L1-linked capture probe. Then, in situ hyperbranched rolling circle amplification, a typical DNA amplification reaction, is conducted using the surface-attached capture probes as primers, which lows environmental pH. As a result, disassembly of PVP@HRP@ZIF-8 takes place, leading to the release of enzymes, which can arouse amplified electrochemical responses for the identification of target exosomes. Experimental results reveal that the biosensing method displays a linear range for PD-L1+ exosomes identification from 1 × 103 to 1 × 1010 particles/mL and the detection limit reaches 334 particles/mL. What is more, by using the method, elevated level of circulating PD-L1+ exosomes is found in the undiluted serum samples from patients with breast cancer, particularly for metastatic breast cancer, revealing a positive correlation of the PD-L1+ exosome level with the tumor staging and disease progression of breast cancer. Therefore, the biosensing method may be valuable for not only exosome identification but also providing reference information for diagnosis and real-time monitoring of breast cancer in the future.
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