PD-L1 detection on circulating tumor-derived extracellular vesicles (T-EVs) from patients with lung cancer
Translational Lung Cancer Research | June 1, 2021
Wu F, Gu Y, Kang B, Heskia F, Pachot A, Bonneville M, Wei P and Liang J
Transl Lung Cancer Res. 2021;10:2441-2451
Background: Recent breakthroughs in therapies with immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, only 15–25% of patients respond to the ICIs therapy, and methods to identify those responsive patients are currently a hot research topic. PD-L1 expression measured on tumor tissues using immunohistochemistry (IHC) was approved as one of the companion diagnostic methods, but it is invasive and cannot be used to monitor dynamic changes in PD-L1 expression during treatments.
Methods: In this study, we developed an Epcam-PD-L1 extracellular vesicle (EV) detection prototype using the Simoa platform. This assay detected PD-L1 expression levels on tumor-derived exosomes from the lung cancer cell lines A549 and SK-MES1. In addition, 35 plasma samples from patients with lung cancer were tested with this assay and the results were compared to the tissue PD-L1 expression levels represented by the tumor proportion score (TPS).
Results: PD-L1 TPS-positive patients (≥1% IHC TPS) had significantly higher Simoa Epcam-PD-L1 signals than TPS-negative patients (<1% IHC TPS, P=0.026). The Simoa Epcam-PD-L1 area under curve (AUC) reached 0.776, with a sensitivity of 92.86% and a specificity of 71.43%. When PD-L1 TPS-positive patients were defined as having an IHC TPS ≥10%, the greatest difference in Epcam-PD-L1 signals was observed between IHC TPS-positive and IHC TPS-negative groups (P=0.0024) and the Simoa Epcam-PD-L1 AUC reached 0.832. Finally, the Spearman’s correlation coefficient showed a significant correlation between the TPS and Simoa Epcam-PD-L1 signals (0.428, P=0.0104).
Conclusions: Based on our results, our Simoa Epcam-PD-L1 EV detection assay is a potential liquid biopsy method to predict the PD-L1 expression level in patients with lung cancer.
This study was performed using the Quanterix HD-1 Analyzer.
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