Discovery of Biomarkers of Resistance to Immune Checkpoint Blockade in NSCLC Using High-Plex Digital Spatial Profiling.


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 2022
Historique:
received: 27 01 2022
revised: 17 04 2022
accepted: 20 04 2022
pubmed: 2 5 2022
medline: 10 8 2022
entrez: 1 5 2022
Statut: ppublish

Résumé

Despite the clinical efficacy of immune checkpoint inhibitors (ICIs) in NSCLC, only approximately 20% of patients remain disease-free at 5 years. Here, we use digital spatial profiling to find candidate biomarker proteins associated with ICI resistance. Pretreatment samples from 56 patients with NSCLC treated with ICI were analyzed using the NanoString GeoMx digital spatial profiling method. A panel of 71 photocleavable oligonucleotide-labeled primary antibodies was used for protein detection in four molecular compartments (tumor, leukocytes, macrophages, and immune stroma). Promising candidates were orthogonally validated with quantitative immunofluorescence. Available pretreatment samples from 39 additional patients with NSCLC who received ICI and 236 non-ICI-treated patients with operable NSCLC were analyzed to provide independent cohort validation. Biomarker discovery using the protein-based molecular compartmentalization strategy allows 284 protein variables to be assessed for association with ICI resistance by univariate analysis using continuous log-scaled data. Of the 71 candidate protein biomarkers, CD66b in the CD45+CD68 molecular compartment (immune stroma) predicted significantly shorter overall survival (OS) (hazard ratio [HR] 1.31, p = 0.016) and was chosen for validation. Orthogonal validation by quantitative immunofluorescence illustrated that CD66b was associated with resistance to ICI therapy but not prognostic for poor outcomes in untreated NSCLC (discovery cohort [OS HR 2.49, p = 0.026], validation cohort [OS HR 2.05, p = 0.046], non-ICI-treated cohort [OS HR 1.67, p = 0.06]). Using the technique, we have discovered that CD66b expression is indicative of resistance to ICI therapy in NSCLC. Given that CD66b identifies neutrophils, further studies are warranted to characterize the role of neutrophils in ICI resistance.

Identifiants

pubmed: 35490853
pii: S1556-0864(22)00212-X
doi: 10.1016/j.jtho.2022.04.009
pmc: PMC9356986
mid: NIHMS1802660
pii:
doi:

Substances chimiques

Antineoplastic Agents, Immunological 0
Biomarkers, Tumor 0
Immune Checkpoint Inhibitors 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

991-1001

Subventions

Organisme : NCI NIH HHS
ID : P30 CA016359
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA196530
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001863
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

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

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Auteurs

Myrto Moutafi (M)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Sandra Martinez-Morilla (S)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Prajan Divakar (P)

NanoString Technologies, Seattle, Washington.

Ioannis Vathiotis (I)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Niki Gavrielatou (N)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Thazin Nwe Aung (TN)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Vesal Yaghoobi (V)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Aileen I Fernandez (AI)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut.

Jon Zugazagoitia (J)

Section of Medical Oncology, Hospital Universitario 12 de Octubre, Madrid, Spain.

Roy S Herbst (RS)

Section of Oncology, Department of Medicine, Yale School of Medicine, New Haven, Connecticut.

Kurt A Schalper (KA)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut; Section of Oncology, Department of Medicine, Yale School of Medicine, New Haven, Connecticut.

David L Rimm (DL)

Department of Pathology, Yale School of Medicine, New Haven, Connecticut; Section of Oncology, Department of Medicine, Yale School of Medicine, New Haven, Connecticut. Electronic address: david.rimm@yale.edu.

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Classifications MeSH