Programmed Death-Ligand 1 Copy Number Loss in NSCLC Associates With Reduced Programmed Death-Ligand 1 Tumor Staining and a Cold Immunophenotype.


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:
05 2022
Historique:
received: 08 12 2021
revised: 18 01 2022
accepted: 20 01 2022
pubmed: 7 2 2022
medline: 27 4 2022
entrez: 6 2 2022
Statut: ppublish

Résumé

Programmed death-ligand 1 (PD-L1) copy number gains may be predictive of clinical response to immunotherapy in NSCLC. This study investigated PD-L1 copy number variations in tumor resection and bronchoscopy biopsies and its relationship with PD-L1 tumor cell staining and inflammatory gene expression. PD-L1 gene copy number and mRNA expression were evaluated by real-time polymerase chain reaction in surgically resected NSCLC tumor biopsies (n = 87) and control biopsies (n = 20). A second cohort (n = 15) of bronchoscopy-derived tumor biopsies was analyzed, including multiple biopsies from the same patient across different anatomical sites. PD-L1 mRNA levels strongly correlated with PD-L1 tumor staining (r = 0.55, p < 0.0001). Interferon-γ mRNA expression associated with PD-L1 immune cell staining, but not PD-L1 tumor cell staining. In contrast, PD-L1 copy number positively associated PD-L1 tumor staining, but not PD-L1 immune cell staining. PD-L1 copy number analysis detected loss (15 of 87 = 17%) and gain (5 of 87 = 7%) of copy number. Tumors with low PD-L1 copy number expressed significantly reduced levels of inflammatory (interferon-γ, interleukin [IL]-6, IL-1β, MMP-9) and immunosuppressive (IL-10, transforming growth factor β) mediators. Analysis of bronchoscopy-derived biopsies revealed low heterogeneity in copy number values across different anatomical sites, in contrast to more variable PD-L1 mRNA expression. Low PD-L1 copy number tumors display reduced PD-L1 expression, reduced PD-L1 tumor cell staining, and an immunologic cold tumor microenvironment. Because PD-L1 copy number values are highly stable across different tumor regions, its evaluation may represent a robust and complimentary biomarker for predicting response to immunotherapy, where low copy number may predict lack of response.

Identifiants

pubmed: 35124252
pii: S1556-0864(22)00082-X
doi: 10.1016/j.jtho.2022.01.013
pii:
doi:

Substances chimiques

B7-H1 Antigen 0
Biomarkers, Tumor 0
CD274 protein, human 0
RNA, Messenger 0
Interferon-gamma 82115-62-6

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

675-687

Commentaires et corrections

Type : CommentIn
Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2022 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Auteurs

Savreet Aujla (S)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia.

Christian Aloe (C)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia.

Amanda Vannitamby (A)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia.

Shona Hendry (S)

Department of Anatomical Pathology, St Vincent's Hospital, Melbourne, Australia.

Kanishka Rangamuwa (K)

Department of Respiratory Medicine & Sleep Medicine, Royal Melbourne Hospital, Melbourne, Australia.

Hao Wang (H)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia.

Ross Vlahos (R)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia.

Stavros Selemidis (S)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia.

Tracy Leong (T)

Department of Respiratory Medicine & Sleep Medicine, Austin Health, Heidelberg, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.

Daniel Steinfort (D)

Department of Respiratory Medicine & Sleep Medicine, Royal Melbourne Hospital, Melbourne, Australia; Faculty of Medicine, University of Melbourne, Parkville, Australia.

Steven Bozinovski (S)

School of Health & Biomedical Sciences, RMIT University, Bundoora, Australia. Electronic address: steven.bozinovski@rmit.edu.au.

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Classifications MeSH