Paré, LPascual, TSeguí, ETeixidó, CGonzalez-Cao, MGalván, PRodríguez, AGonzález, BCuatrecasas, MPineda, ETorné, ACrespo, GMartin-Algarra, SPérez-Ruiz, EReig, ÒViladot, MFont, CAdamo, BVidal, MGaba, LMuñoz, MVictoria, IRuiz, GViñolas, NMellado, BMaurel, JGarcia-Corbacho, JMolina-Vila, M ÁJuan, MLlovet, J MReguart, NArance, APrat, A2025-01-072025-01-072018https://hdl.handle.net/10668/26687We 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. 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. 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 = 0.91) with the ORR following anti-PD1 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 = 8.31; P  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 = 0.91) with the ORR following anti-PD1 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 = 8.31; P  Our study provides a clinically applicable assay that links PD1 mRNA abundance, activated CD8 T-cells and anti-PD1 efficacy.enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Antineoplastic Agents, ImmunologicalBiomarkers, TumorCD8-Positive T-LymphocytesCohort StudiesFemaleFollow-Up StudiesGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingMaleMiddle AgedNeoplasmsPrognosisProgrammed Cell Death 1 ReceptorRNA, MessengerSurvival Rateresearch article30165419open access10.1093/annonc/mdy3351569-8041http://www.annalsofoncology.org/article/S0923753419342085/pdf