Interferon gamma, an important marker of response to immune checkpoint blockade in non-small cell lung cancer and melanoma patients

Background: Programmed death-ligand 1 (PD-L1) may be induced by oncogenic signals or can be upregulated via interferon gamma (IFN-y). We have explored whether the expression of IFNG, the gene encoding IFN-y, is associated with clinical response to the immune checkpoint blockade in non-small cell lung cancer (NSCLC) and melanoma patients. The role of inflammation-associated transcription factors STAT3, IKBKE, STAT1 and other associated genes has also been examined

Association between PD1 mRNA and response to anti-PD1 monotherapy across multiple cancer types

Background: We hypothesized that the abundance of PD1 mRNA in tumor samples might explain the differences in overall response rates (ORR) observed following anti-PD1 monotherapy across cancer types. Patients and methods: RNASeqv2 data from 10 078 tumor samples representing 34 different cancer types was analyzed from TCGA. Eighteen immune-related gene signatures and 547 immune-related genes, including PD1, were explored. Correlations between each gene/signature and ORRs reported in the literature following anti-PD1 monotherapy were calculated. To translate the in silico findings to the clinical setting, we analyzed the expression of PD1 mRNA using the nCounter platform in 773 formalin-fixed paraffin embedded (FFPE) tumor samples across 17 cancer types. To test the direct relationship between PD1 mRNA, PDL1 immunohistochemistry (IHC), stromal tumor-infiltrating lymphocytes (sTILs) and ORR, we evaluated an independent FFPE-based dataset of 117 patients with advanced disease treated with anti-PD1 monotherapy. Results: In pan-cancer TCGA, PD1 mRNA expression was found strongly correlated (r > 0.80) with CD8 T-cell genes and signatures and the proportion of PD1 mRNA-high tumors (80th percentile) within a given cancer type was variable (0%–84%). Strikingly, the PD1-high proportions across cancer types were found strongly correlated (r ¼ 0.91) with the ORR following antiPD1 monotherapy reported in the literature. Lower correlations were found with other immune-related genes/signatures, including PDL1. Using the same population-based cutoff (80th percentile), similar proportions of PD1-high disease in a given cancer type were identified in our in-house 773 tumor dataset as compared with TCGA. Finally, the pre-established PD1 mRNA FFPE-based cutoff was found significantly associated with anti-PD1 response in 117 patients with advanced disease (PD1-high 51.5%, PD1-intermediate 26.6% and PD1-low 15.0%; odds ratio between PD1-high and PD1-intermediate/low ¼ 8.31; P < 0.001). In this same dataset, PDL1 tumor expression by IHC or percentage of sTILs was not found associated with response. Conclusions: Our study provides a clinically applicable assay that links PD1 mRNA abundance, activated CD8 T-cells and anti-PD1 efficacy