According to multiple studies, the objective response rate of PD-1/PD-L1 inhibitors in the second-line treatment of unscreened non-small cell lung cancer (NSCLC) is only approximately 20%. Predictive biomarkers of treatment efficacies are still under investigation. In selected NSCLC patients with PD-L1 expression ≥ 50%, the response rate of pembrolizumab in first-line treatment can reach 44.8%. Moreover, patients with a higher tumor mutation burden (TMB) tend to achieve a better response with nivolumab. Besides PD-L1 expression and TMB, taking all these indicators into consideration would hypothetically maximize the clinical response in a specific subgroup of patients. Our study aims to accumulate large and complete samples and clinical data to verify the biomarkers and their cutoff values related to the efficacy of PD-1/PD-L1 inhibitors in Chinese NSCLC patients, and to construct a comprehensive predictive model by combining multi-omics data with contemporary machine learning techniques. NSCLC patients administered treatment of anti-PD-1/PD-L1 antibodies or a combination with other drugs have been enrolled. The estimated enrollment is 250 participants. A sophisticated predictive model of immunotherapy response in the Chinese population has not yet been developed. It is clinically and practically imperative to comprehensively evaluate the possible indicators of Chinese NSCLC patients through multiple test platforms, such as next generation sequencing, PCR, or immunohistochemistry. This study is registered in the Chinese Clinical Trial Registry (ChiCTR1900021395).
Keywords: Multi-omics; NSCLC; PD-1/PD-L1 inhibitor; predictive biomarker.
© 2019 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.