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

Background: Immune 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.Methods: Retrospective 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.Results: The 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-gamma 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-gamma.Conclusions: The TIS (tumor inflammation signature) and IFN-gamma signatures constitute predictive biomarkers to identify patients with NSCLC patients who would possibly benefit from ICI therapies.

Automated summary

The TIS and IFN-gamma signatures are predictive biomarkers for identifying NSCLC patients who could potentially benefit from immune checkpoint inhibitor therapies.