Programmed Death-Ligand 1 Immunohistochemistry Assay Comparison Studies in NSCLC: Characterization of the 73-10 Assay.


Journal

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
ISSN: 1556-1380
Titre abrégé: J Thorac Oncol
Pays: United States
ID NLM: 101274235

Informations de publication

Date de publication:
08 2020
Historique:
received: 06 12 2019
revised: 06 04 2020
accepted: 07 04 2020
pubmed: 1 5 2020
medline: 7 1 2021
entrez: 1 5 2020
Statut: ppublish

Résumé

Several programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) assays have been developed independently within clinical programs for therapeutic anti-programmed cell death protein 1 (anti-PD-1) or PD-L1 antibodies, necessitating assessment of assay comparability. We characterized the Dako PD-L1 IHC 73-10 assay used in clinical trials of avelumab (anti-PD-L1) or bintrafusp alfa (M7824; bifunctional immunotherapy) and compared it with the Dako PD-L1 IHC 22C3 pharmDx assay, an approved companion diagnostic for pembrolizumab monotherapy in patients with advanced NSCLC. Formalin-fixed, paraffin-embedded NSCLC tumor samples from a commercial source and from the JAVELIN Solid Tumor phase 1 trial of avelumab (NCT01772004) were stained using the 73-10 and 22C3 IHC assays with a standard protocol. Both assays displayed expected PD-L1 staining patterns. In 148 commercial NSCLC samples, the 73-10 assay stained greater than or equal to 1%, greater than or equal to 50%, and greater than or equal to 80% of tumor cells as PD-L1+ in 64.2%, 36.5%, and 23.6% of the samples, respectively, whereas the 22C3 assay stained 20.3% of the samples as greater than or equal to 50% PD-L1+. In 83 NSCLC clinical trial samples, the 73-10 assay stained 79.5% and 31.3% of the samples as greater than or equal to 1% and greater than or equal to 80% PD-L1+, respectively, whereas the 22C3 assay stained 59.0% and 21.7% as greater than or equal to 1% and greater than or equal to 50% PD-L1+, respectively. Efficacy of avelumab was similar in the subgroups classified with the 73-10 and 22C3 assays using greater than or equal to 80% and greater than or equal to 50% PD-L1+ cutoffs, with objective response rates of 26.9% and 33.3%, respectively. The 73-10 assay demonstrated high sensitivity for PD-L1 staining, and staining was comparable between the greater than or equal to 80% cutoff of the 73-10 assay and greater than or equal to 50% cutoff of the 22C3 assay.

Identifiants

pubmed: 32353599
pii: S1556-0864(20)30327-0
doi: 10.1016/j.jtho.2020.04.013
pii:
doi:

Substances chimiques

B7-H1 Antigen 0
Biomarkers, Tumor 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1306-1316

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Auteurs

Hans Juergen Grote (HJ)

Merck KGaA, Darmstadt, Germany.

Zheng Feng (Z)

EMD Serono Research & Development Institute, Inc., Billerica, Massachusetts; a business of Merck KGaA, Darmstadt, Germany.

Michael Schlichting (M)

Merck KGaA, Darmstadt, Germany.

Christoph Helwig (C)

Merck KGaA, Darmstadt, Germany.

Mary Ruisi (M)

EMD Serono Research & Development Institute, Inc., Billerica, Massachusetts; a business of Merck KGaA, Darmstadt, Germany.

Hulin Jin (H)

Merck KGaA, Darmstadt, Germany.

Juergen Scheuenpflug (J)

Merck KGaA, Darmstadt, Germany.

Claudia-Nanette Gann (CN)

Merck KGaA, Darmstadt, Germany.

Zhen Su (Z)

EMD Serono Research & Development Institute, Inc., Rockland, Massachusetts; a business of Merck KGaA, Darmstadt, Germany.

Martin Reck (M)

Lung Clinic, Airway Research Center North, German Center for Lung Research (Deutsches Zentrum für Lungenforschung), Grosshansdorf, Germany.

Everett E Vokes (EE)

Department of Medicine, University of Chicago, Chicago, Illinois.

Keith M Kerr (KM)

Department of Pathology, Aberdeen University Medical School and Aberdeen Royal Infirmary, Aberdeen, United Kingdom. Electronic address: k.kerr@abdn.ac.uk.

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Classifications MeSH