Abstract
Anti-programmed death (ligand)-1 [anti-PD-(L)1] therapies such as pembrolizumab, nivolumab or atezolizumab have become standard of care for non-small cell lung cancer (NSCLC) patients either in first line or beyond. PD-L1 expression level allows enriching the treated population with responders, but it is still not an optimal biomarker. Even in patients with PD-L1 tumor proportion score (TPS) levels of ≥50% treated with first line pembrolizumab overall response rate (ORR) is only 44.8% and overall survival at one year is 70%. Moreover, in combination trials with chemotherapy and anti-PD-(L)1 therapy, a significant proportion of patients does not respond (ORR ranges from 45.3% to 64.0%), regardless of PD-L1 expression. Furthermore, PD-L1 expression level is not associated with improved benefit in patients treated with combinations of anti-PD-(L)1 and anti-cytotoxic T-lymphocyte-associated antigen (anti-CTLA4) therapy. One of the new promising biomarkers is tumor mutational burden (TMB). It has been discovered that especially tumor types with a known high mutation rate such as NSCLC and melanoma respond best to immune checkpoint inhibitors (ICIs). An explanation is that this high mutation rate makes it more likely that neoantigens arise that are targeted by activated immune cells, but it is not feasible to determine neoantigen load in daily practice. However, TMB of a certain tumor type is associated with neoantigen load and outcome on ICIs. In this comprehensive review, we discuss the TMB analysis methods, the rationale to use TMB as a predictive biomarker and the clinical utility of TMB in NSCLC patients treated with ICIs.