RT Journal Article
T1 Association between PD1 mRNA and response to anti-PD1 monotherapy across multiple cancer types.
A1 Paré, L
A1 Pascual, T
A1 Seguí, E
A1 Teixidó, C
A1 Gonzalez-Cao, M
A1 Galván, P
A1 Rodríguez, A
A1 González, B
A1 Cuatrecasas, M
A1 Pineda, E
A1 Torné, A
A1 Crespo, G
A1 Martin-Algarra, S
A1 Pérez-Ruiz, E
A1 Reig, Ò
A1 Viladot, M
A1 Font, C
A1 Adamo, B
A1 Vidal, M
A1 Gaba, L
A1 Muñoz, M
A1 Victoria, I
A1 Ruiz, G
A1 Viñolas, N
A1 Mellado, B
A1 Maurel, J
A1 Garcia-Corbacho, J
A1 Molina-Vila, M Á
A1 Juan, M
A1 Llovet, J M
A1 Reguart, N
A1 Arance, A
A1 Prat, A
AB 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. 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.
YR 2018
FD 2018
LK https://hdl.handle.net/10668/26687
UL https://hdl.handle.net/10668/26687
LA en
DS RISalud
RD Apr 8, 2025