The Prognostic Significance of PD1 and PDL1 Gene Expression in Lung Cancer: A Meta-Analysis - Chang, Chih-Hao; Shih, Arthur Chun-Chieh; Chang, Ya-Hsuan; Chen, Hsuan‐Yu; Chao, Ying-Ting; Hsu, Yi-Chiung (Frontiers in Oncology, 2021)
Background Immune checkpoint blockade therapy represents an extraordinary advance in lung cancer treatment. It is important to determine the expression of immune checkpoint genes, such as programmed cell death 1 (PD1) and programmed cell death-ligand 1 (PDL1), to develop immunotherapeutic strategies. The aim of this study was to explore the association between PD1 and PDL1 gene expression and prognoses and outcomes in lung cancer. Methods This meta-analysis analyzed 1,251 patients from eight different microarray gene expression datasets and were evaluated for their prognostic implications and verified using another independent research. Results The mean expression levels of PDL1 in adenocarcinoma (AD) and squamous cell carcinoma (SC) were significantly higher in patients who died than in patients who did not. There was a trend toward incremental increases in PD1 and PDL1 expression significantly decreasing the risk of relapse and death among AD patients (HR = 0.69; 95% CI = 0.53 0.91; HR = 0.68; 95% CI = 0.54 0.84, respectively) and SC patients (HR = 0.53; 95% CI = 0.32 0.89; HR = 0.78; 95% CI = 0.57 1.00 respectively), as early-stage patients in this study were more likely to have high expression of both PD1 and PDL1 than late-stage patients (P-trend < 0.05). In contrast, late-stage SC patients expressing one or more of the genes at a high level had a significantly elevated risk of relapse (HR = 1.51; 95% CI = 1.07 2.11) and death (HR = 1.41; 95% CI = 1.08 1.84). This result was consistent with the validation data set. Conclusion These findings indicate that high expression of PD1 and PDL1 is associated with superior outcome in early-stage lung cancer but an adverse outcome in late-stage lung cancer. The expression levels of PD1 and PDL1 individually or jointly are potential prognostic factors for predicting patient outcomes in lung cancer.