Clinical and molecular correlates of PD-L1 expression in patients with lung adenocarcinomas.

BACKGROUND

Programmed death-ligand 1 (PD-L1) expression is the only FDA-approved biomarker for immune checkpoint inhibitors (ICIs) in patients with lung adenocarcinoma, but sensitivity is modest. Understanding the impact of molecular phenotype, clinical characteristics, and tumor features on PD-L1 expression is largely unknown and may improve prediction of response to ICI.

PATIENTS AND METHODS

We evaluated patients with lung adenocarcinoma for whom PD-L1 testing and targeted next-generation sequencing (using MSK-IMPACT) was performed on the same tissue sample. Clinical and molecular features were compared across PD-L1 subgroups to examine how molecular phenotype associated with tumor PD-L1 expression. In patients treated with anti-PD-(L)1 blockade, we assessed how these interactions impacted efficacy.

RESULTS

A total of 1586 patients with lung adenocarcinoma had paired PD-L1 testing and targeted next-generation sequencing. PD-L1 negativity was more common in primary compared to metastatic samples (P < 0.001). The distribution of PD-L1 expression (lymph nodes enriched for PD-L1 high; bones predominantly PD-L1 negative) and predictiveness of PD-L1 expression on ICI response varied by organ. Mutations in KRAS, TP53, and MET significantly associated with PD-L1 high expression (each P < 0.001, Q < 0.001) and EGFR and STK11 mutations associated with PD-L1 negativity (P < 0.001, Q = 0.01; P = 0.001, Q < 0.001, respectively). WNT pathway alterations also associated with PD-L1 negativity (P = 0.005). EGFR and STK11 mutants abrogated the predictive value of PD-L1 expression on ICI response.

CONCLUSION

PD-L1 expression and association with ICI response vary across tissue sample sites. Specific molecular features are associated with differential expression of PD-L1 and may impact the predictive capacity of PD-L1 for response to ICIs.

Informations de copyright

Copyright © 2020 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Disclosure JLS reports stock ownership in the following companies: Pfizer, Thermo Fischer Scientific, Inc., Merck & Co Inc., and Chemed Corp. KCA has been a compensated consultant for AstraZeneca. MAE is a consultant for AstraZeneca and received support from AstraZeneca, Invivoscribe, and Raindance Technologies. ML has received advisory board compensation from Boehringer Ingelheim, AstraZeneca, Bristol-Myers Squibb, Takeda, and Bayer and research support from Loxo Oncology and Helsinn Healthcare. CML is a consultant for AbbVie, Amgen, Ascentage, AstraZeneca, Bicycle, Celgene, Chugai, Daiichi Sankyo, Genentech/Roche, GI Therapeutics, Loxo, Novartis, PharmaMar, and Seattle Genetics; serves on the scientific advisory boards of Elucida and Harpoon; and reports personal fees from Bristol-Myers Squibb and Ipsen. GJR has research funding for his institution from Pfizer, Novartis, Takeda, and Roche. MDH receives research funding from Bristol-Myers Squibb; is a paid consultant to Merck, Bristol-Myers Squibb, AstraZeneca, Genentech/Roche, Janssen, Nektar, Syndax, Mirati, and Shattuck Labs; receives travel support/honoraria from AstraZeneca and Bristol-Myers Squibb; and a patent has been filed by MSK related to the use of tumor mutation burden to predict response to immunotherapy (PCT/US2015/062208), which has received licensing fees from PGDx. All other authors have declared no conflicts of interest.