Check point inhibitors, such as anti- programmed death 1 (PD-1) (Nivolumab, Pembrolizumab)/ anti-programmed death-ligand 1 (PD-L1) therapies (Atezolizumab, Avelumab and Durvalumab) have dramatically changed the therapeutic and prognostic landscape for several types of malignancy. These agents provide significant survival benefits in many cancers, but the efficacy of these treatments varies considerably across different cancer types. Therefore, identifying the underlying variables associated with this cancer type–specific response was an important challenge.
To address this, Lee JS et al  demonstrated that among the 36 variables, estimated CD8+ T-cell abundance was the most predictive of the response to anti–PD-1/PD-L1 therapy across cancer types (R = 0.72), followed by the tumor mutational burden (R = 0.68), and the fraction of samples with high PD1 gene expression (R = 0.68). Importantly, combination of these 3 variables highly correlated with response (R = 0.90), explaining more than 80% of the ORR variance observed across different tumor types.
This is an important finding which can be used to predict likelihood of response to anti-PD-1 or anti-PD-L1 therapy; and to identify the subset of patients most likely to derive clinical benefit to get cost-effective solution.
Reference: 1. Lee JS, Ruppin E. Multiomics Prediction of Response Rates to Therapies to Inhibit Programmed Cell Death 1 and Programmed Cell Death 1 Ligand 1. JAMA Oncol.2019 Aug 22.