Development and Validation of a Gene Mutation-Based Signature to Predict Response to PD-1 Inhibitors in Non-Squamous NSCLC: A Retrospective Multicohort Study

Background: Genetic variations in non-small cell lung cancer (NSCLC) have been shown potential impact on immune microenvironment, and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an unbiased analysis to develop a gene mutation-based signature (GMS) and predict the response to anti-PD-(L1) therapy. Methods: In this retrospective multicohort analysis, 316 patients with nonsquamous NSCLC treated with anti-PD-(L1) based therapy from three independent cohorts were included in our study. We developed a risk model named GMS based on the MSK training cohort (n=123). The predictive model was first validated in the separate internal MSK cohort (n=82), and then validated in Checkmate-012 (n=59) and Keynote/SU2C (n=52) external clinical trial cohorts. Tumor samples from the patients were molecularly profiled by MSK or whole exome sequencing. Findings: A GMS that consisted of 8 genes (TP53, KRAS, STK11, EGFR, PTPRD, KMT2C, SMAD4 and HGF) was generated to classify patients into high and low GMS groups in the training cohort. Patients with high GMS in the training cohort had longer progression-free survival (HR 0·44, 0·30-0·65, p=0·0002) and overall survival (HR 0·56, 0·33-0·94, p=0·0412) compared with low GMS. We noted equivalent findings in the internal validation cohort and in the external validation cohort. The GMS was demonstrated as an independent predictive factor for anti-PD-1(L1) therapy, without affecting the prognosis of non-squamous NSCLC. Meanwhile, GMS showed undifferentiated predictive value in patients with different clinicopathological features. Notably, both GMS and PD-L1 were independent predictors and demonstrated poorly correlated, inclusion of PD-L1 with GMS furtherly improved the predictive capacity for PD-1 blockade immunotherapy. Interpretation: Our study highlights the potential predictive value of GMS for immunotherapeutic benefit in non-squamous NSCLC. Besides, the combination of GMS and PD-L1 may serve as optimal partner in guiding treatment decisions for anti-PD-(L1) based therapy. Funding Statement: The National Natural Science Foundation for Young Scientists of China, the Natural Science Foundation of Guangdong Province, and the Outstanding Youths Development Scheme of Nanfang Hospital, Southern Medical University. Declaration of Interests: The authors have no actual or potential conflicts of interest to declare. Ethics Approval Statement: This study was approved by the Institutional Ethical Review Boards of Nanfang Hospital. Patients provided signed informed consent in accordance with their respective trial protocols or MSK-IMPACT sequencing project.