Results from a retrospective analysis of the exome sequences of tumor and blood specimens from patients with metastatic non-small cell lung cancer (NSCLC) who had been enrolled in a clinical trial of single-agent nivolumab, a programmed cell death-1 (PD-1) inhibitor, showed that a model involving 9 tumor exome-based parameters was significantly predictive of progression-free survival (PFS) (P <.0001) and overall survival (OS) (P =.002). This study was published online in Clinical Cancer Research.
Although the efficacy of immune checkpoint inhibitor therapy has been clearly demonstrated in the setting of NSCLC, clinical benefit is observed in only approximately one-quarter of patients treated with these agents. While tumor level of programmed cell death ligand-1 (PD-L1), as detected by immunohistochemistry, remains the gold standard for identifying patients likely to respond to anti-PD-1 therapies, it is considered a suboptimal biomarker.
More recently identified biomarkers of response to immune checkpoint inhibitor therapy include tumor mutational burden (TMB), involving an assessment of the number of nonsynonymous mutations (ie, mutations that alter the protein sequence) per DNA megabase, as well as the neoantigen rate (eg, antigens arising from alterations in host antigens) in tumors. Furthermore, characteristic combinations of types of mutations (ie, mutational signatures) in tumors are being actively explored as markers of response to immunotherapy. Nevertheless, improved models for predicting patient benefit from immune checkpoint inhibitor therapy are needed.
This retrospective study involved an analysis of exome sequencing results of blood and tumor specimens collected at baseline as part of a clinical trial of second- or third-line nivolumab therapy of patients with metastatic NSCLC from a single institution in France. The objective of this study was to identify a biomarker or set of biomarkers that could better predict response to immune checkpoint inhibitor therapy compared with preexisting models.
Seventy-seven patients with metastatic NSCLC were included in the analysis, with a median follow-up of 11 months. All planned tests were performed on the specimens of 65 patients, and an estimation of tumor T-cell receptor (TCR) clonality was performed for 12 patients who did not have adequate samples for exome analysis.
Results of this study included the finding that a 9-exome–based parameter model (ie, a model including high TMB, high neoantigen level, mutational signatures 1A and 1B, several DNA pathway mutations, and a low number of TCR clones) was predictive of PFS and OS benefit in NSCLC patients treated with anti-PD-1 therapy. In addition, a comparison of the new model with a model involving PD-L1 level with or without TMB showed the former to be a better predictor of response to nivolumab.
The predictive ability of the exome-based model was externally validated in 2 cohorts of patients with NSCLC and 1 cohort of patients with urothelial cancer treated with anti-PD-1 or PD-L1 therapy.
In conclusion, the authors wrote that “these results suggest that our signature could be generalized to different types of immunotherapy targeting checkpoints, and suggest that it could be tested in other tumor types like urothelial cancer.”