Clinicopathological characteristics correlated with programmed cell death-ligand 1 expression in advanced lung adenocarcinoma.

Background: Recent studies have shown that immune checkpoint inhibitors (ICIs) targeting programmed cell death-ligand 1 (PD-L1) have potential benefits in patients with non-small cell lung cancer (NSCLC) subgroups, while the clinicopathological characteristics associated with PD-L1 expression have not been well established. The purpose of this study was to detect the expression level of PD-L1 in tumor tissues of patients with advanced lung adenocarcinoma (ADC) and analyze its possible relationship with clinicopathological characteristics, so as to identify the predictors of PD-L1 expression. Methods: This retrospective study was conducted by analyzing the clinicopathological and imaging characteristics of hospitalized advanced lung ADC patients with PD-L1 available data and admitted to the respiratory department of our hospital. The expression level of PD-L1 in fresh-frozen tumor tissue samples of 136 advanced ADC patients was analyzed by immunohistochemistry. The patients were divided into positive and negative groups based on a cut-off of 1% PD-L1 expression level. Subsequently, the significant correlation between PD-L1 levels and clinicopathological features were evaluated. The predictive performance of clinicopathological characteristics on PD-L1 expression was evaluated and the optimal cut-off values were identified by plotting the receiver operating characteristic (ROC) curve. Results: The expression level of PD-L1 was related to sex, clinical stage, serum carcinoembryonic antigen (CEA), neuron specific enolase (NSE), white blood cell (WBC), and tumor (T) and metastasis (M) stage. Multivariate logistic regression analysis showed the CEA, NSE, T stage, and WBC were independent predictors of PD-L1 positive expression in lung ADC patients. The ROC curve suggested the model combining CEA with NSE [area under the curve (AUC) =0.815] could better predict the expression levels of PD-L1. The optimal cut-off values for identifying advanced lung ADC patients with PD-L1 positive were CEA ≤13.38 ng/mL and NSE ≤42.35 ng/mL, with sensitivity and specificity of 85.4% and 55.6%, and 92.7% and 32.1%, respectively. Conclusions: Some commonly used clinicopathological features are related to the histological expression of PD-L1. The serum CEA, NSE, T stage, and WBC values can be used as indicators to predict the expression level of PD-L1 in advanced lung ADC, and are used as predictors to evaluate the efficacy of ICIs before treatment.