A dysfunctional T cell gene signature for predicting non-response to PD-1 blockade in non-small cell lung cancer that is suitable for routine clinical diagnostics

Abstract

Purpose: Since PD-1 blockade is only effective in a minority of patients with advanced stage NSCLC, biomarkers are needed to guide treatment decisions. Tumor infiltration by PD-1T TILs, a dysfunctional tumor-infiltrating lymphocyte (TIL) pool with tumor-reactive capacity, can be detected by digital quantitative IHC and has been established as a novel predictive biomarker in NSCLC. To facilitate translation of this biomarker to the clinic, we here aimed to develop a robust RNA signature reflecting a tumor’s PD-1T TIL status. Experimental Design: mRNA expression analysis using Nanostring was performed in baseline tumor samples from 41 advanced stage NSCLC patients treated with nivolumab that were selected based on PD-1T TIL infiltration by IHC. Samples were included as training cohort (n=41) to develop a predictive gene signature. This signature was independently validated in a second cohort (n=42). Primary outcome was disease control at 12 months (DC 12m) and secondary outcome was progression-free and overall survival. Results: Regularized regression analysis yielded a signature using 12 out of 56 differentially expressed genes between PD-1T IHC high tumors from patients with DC 12m and PD-1T IHC low tumors from patients with progressive disease (PD). In the validation cohort 6/6 (100%) patients with DC 12m and 23/36 (64%) with PD were correctly classified with an NPV of 100% and a PPV of 32%. Conclusions: The PD-1T mRNA signature showed a similar high sensitivity and high NPV as the digital IHC quantification of PD-1T TILs. This provides a straightforward approach allowing for easy implementation in a routine diagnostic clinical setting.