Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression

Abstract

Purpose: Immunotherapy plays an important role in non-small cell lung cancer (NSCLC); in particular, immune checkpoint inhibitors (ICIs) therapy has good therapeutic effects in PD-L1-positive patients. This study aims to screen NSCLC patients with PD-L1-positive expression and select effective biomarkers for ICI immunotherapy. Methods: Collected tumor samples from the Affiliated Cancer Hospital of Xinjiang Medical University and 117 patients with stage III–IV NSCLC were included in the study. All patients were on first- or second-line therapy and not on targeted therapy. Based on the molecular profiles and clinical features, we screened biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression. Results: 117 NSCLC patients receiving ICIs immunotherapy were enrolled. First, we found that immunotherapy was more effective in patients with positive PD-L1 expression. Second, we found that ROS1 gene mutations, KRAS gene mutations, tumor stage, and the endocrine system diseases history are independent prognostic factors for PD-L1 positive patients. Then we combined independent risk factors and constructed a new Nomogram to predict the therapeutic efficacy of ICIs immunotherapy in PD-L1 positive patients. The Nomogram integrates these factors into a prediction model, and the predicted C-statistic of 3 months, 6 months and 12 months are 0.85, 0.84 and 0.85, which represents the high predictive accuracy of the model. Conclusions: We have established a model that can predict the efficacy of ICIs immunotherapy in PD-L1 positive patients. The model consists of ROS1 gene mutations, KRAS gene mutations, tumor staging, and endocrine system disease history, and has good predictive ability.