Detection Of Pd-L1 Expression And Its Clinical Significance In Circulating Tumor Cells From Patients With Non-Small-Cell Lung Cancer

Background: The expression of programmed cell death ligand 1 (PD-L1) is related to the efficacy of immune checkpoint inhibitors on patients with non-small cell lung cancer (NSCLC), but tumor tissue (TT) samples are difficult to obtain, and initial TT samples are difficult to reflect the spatial-temporal heterogeneity. Therefore, we explored the feasibility of separating circulating tumor cells (CTCs) and detecting PD-L1 expression on CTCs. Patients and Methods: Peripheral blood specimens were sampled from 66 NSCLC patients, and CTCs were separated by membrane filtration based on size. For 59 patients with paired TT specimens, the expression of PD-L1 in their CTCs and TTs was determined using the immunohistochemistry and immunocytochemistry based on 28-8 antibody, respectively. The PD-L1 expression in TTs was set as a gold standard for calculation of sensitivity, specificity, consistency, positive predictive value (PPV), and negative predictive value (NPV), and the Cohen kappa coefficient for CTCs and paired TTs was calculated. In addition, the T-test, Chi-square test, and Mann-Whitney U-test were adopted to analyze the correlation of clinical pathological features and prognosis with PD-L1 expression. Results: Sensitivity, specificity, concordance, PPV and NPV of detecting PD-L1 in CTCs of the 41 initial treated patients were 88.89%, 73.91%, 80%, 72.73% and 89.47%, respectively, and the Cohen kappa coefficient of CTC and paired TTs was 0.613. The univariate analysis of survival showed that the progression-free survival time of initial treated patients with positive PD-L1 expression was shorter than that of those with negative PD-L1 expression in CTCs or TTs (P>0.05), and the positive PD-L1 expression in CTCs or TTs had nothing to do with age, sex, smoking status, histological type, and stage (P > 0.05). Conclusion: The study confirms the feasibility of CTC PD-L1 detection in peripheral blood and lays a foundation for exploring real-time and individualized immunotherapy molecular biomarkers.