Association Between Response to Nivolumab Treatment and Peripheral Blood Lymphocyte Subsets in Patients With Non-small Cell Lung Cancer - Ottonello, Selene; Genova, Carlo; Cossu, Irene; Fontana, Vincenzo; Rijavec, Erika; Rossi, Giovanni; Biello, Federica; Dal Bello, Maria Giovanna; Tagliamento, Marco; Alama, Angela; Coco, Simona; Boccardo, Simona; et al. (Frontiers in Immunology, 2020)
Immune checkpoint blockade represents a major breakthrough in advanced non-small cell lung cancer (NSCLC) therapy. However, success is limited to a subset of patients and there is a critical need to identify robust biomarkers associated with clinical response. In this study, we assessed whether pre-existing immunological characteristics, as well as immune parameters measured during treatment, might provide such clinical guidance. We studied blood samples collected at baseline and during treatment in a cohort of advanced NSCLC patients (n=74) treated with nivolumab. Several lymphocyte subsets and biomarkers were then correlated with overall survival (OS) as well as clinical response, assessed using RECIST criteria. We found that patients characterized by longer OS had higher levels of CD3+, CD4+ and CD8+ T cells but lower levels of NK cells at baseline. Moreover, that they displayed a statistically significant lower expression of PD-1 on both CD3+ and CD8+ T cells (p=0.013 and p=0.033, respectively). The pre-treatment level of exhausted T cells (CD8+PD1+Eomes+) was significantly lower in patients with controlled disease (CD), defined as partial response (PR) and stable disease (SD), compared to those with progressive disease (PD) (p=0.046). In CD patients, the frequency of exhausted CD8+ T cells further decreased during treatment cycles (p=<0.0001, p=0.0032, and p=0.0239, respectively). In conclusion, our results suggest that the distribution of lymphocyte subsets and expression of PD-1 on T cells before treatment may help predict the outcome of anti-PD-1 treatment in NSCLC patients. In addition, assessing the initial levels of exhausted T cells as well as their decrease upon treatment may also predict response and clinical outcome.