Gene expression profiles (GEPs) of immuno-oncologic pathways as predictors of response to checkpoint inhibitors in advanced NSCLC

Abstract

BackgroundImmune checkpoint inhibitors (ICIs) revolutionized non-small-cell lung cancer (NSCLC) treatment. However, improving patients’ selection for this therapy is needed. Gene expression profile (GEP) is a promising biomarker tool. We assessed the predictive value of 48 onco-immune GEPs in an NSCLC real-world scenario. MethodsRetrospective cohort of Brazilian NSCLC patients treated with ICIs in any line. GEP was assessed in FFPE tumor tissue using the nCounter PanCancer IO360 panel, comprising 770 cancer immune genes. ResultsThe median age of the 135 patients was 61 years old, most male (57.8 %), history of smoking (83.6 %), ECOG-PS 0-1 (88.7 %), clinical stage IV (91.9 %) and adenocarcinoma (65.1 %). First-line ICI in 40 % of cases, alone or in combination with chemotherapy. The median follow-up was 28 months, overall survival after starting immunotherapy (post-immunotherapy survival – PIS) was 17.8 months, and real-world progression-free survival was 5.5 months. The GEP analysis was possible in 66 patients. We found that 14 different GEPs associated with PIS, namely IDO1, PD-L2, Cytotoxicity, Cytotoxic Cells, IFN Downstream, CTLA4, PD-L1, TIGIT, Lymphoid, Immunoproteasome, Exhausted CD8, IFN Gamma, TIS and APM. TIS and IFN-γ were the most significant GEPs associated with favorable outcomes. The median PIS for patients with high TIS expression was 29.2 versus 15.5 months (HR 0.42; 95 %CI; 0.17–0.67; p<0.05) for those with low expression. Similar results were observed for IFN-γ. Conclusions: The TIS (tumor inflammation signature) and IFN-γ signatures constitute predictive biomarkers to identify patients with NSCLC patients who would possibly benefit from ICI therapies.