Stromal FAP is an independent poor prognosis marker in non-small cell lung adenocarcinoma and associated with p53 mutation.


Journal

Lung cancer (Amsterdam, Netherlands)
ISSN: 1872-8332
Titre abrégé: Lung Cancer
Pays: Ireland
ID NLM: 8800805

Informations de publication

Date de publication:
05 2021
Historique:
received: 18 12 2020
revised: 12 02 2021
accepted: 20 02 2021
pubmed: 12 3 2021
medline: 22 6 2021
entrez: 11 3 2021
Statut: ppublish

Résumé

Fibroblasts regulate tumor growth and immune surveillance. Here, we study FAP, PDGFβR and α-SMA fibroblast markers in a well-annotated clinical cohort of non-small-cell lung cancer (NSCLC) for analyses of associations with immune cell infiltration, mutation status and survival. A well-annotated NSCLC cohort was subjected to IHC analyses of stromal expression of FAP, PDGFβR and α-SMA and of stromal CD8 density. Fibroblast markers-related measurements were analyzed with regard to potential associations with CD8 density, cancer genetic driver mutations, survival and PD-L1 expression in the whole NSCLC cohort and in subsets of patients. High stromal FAP expression was identified as an independent poor prognostic marker in the whole study population (HR 1.481; 95 % CI, 1.012-2.167, p = 0.023) and in the histological subset of adenocarcinoma (HR 1.720; 95 % CI, 1.126-2.627, p = 0.012). Among patients with adenocarcinoma, a particularly strong association of FAP with poor survival was detected in patients with low stromal CD8 infiltration, and in other subpopulations identified by specific clinical characteristics; elderly patients, females, non-smokers and patients with normal ECOG performance status. α-SMA expression was negatively associated with CD8 infiltration in non-smokers, but none of the fibroblast markers expression was associated with CD8 density in the whole study population. Significant associations were detected between presence of p53 mutations and high α-SMA (p = 0.003) and FAP expression (p < 0.001). The study identifies FAP intensity as a candidate independent NSCLC prognostic biomarker. The study also suggests continued analyses of the relationships between genetic driver mutations and the composition of tumor stroma, as well as continued probing of marker-defined fibroblasts as NSCLC subset-specific modifiers of immune surveillance and outcome.

Identifiants

pubmed: 33706022
pii: S0169-5002(21)00088-X
doi: 10.1016/j.lungcan.2021.02.028
pii:
doi:

Substances chimiques

Biomarkers, Tumor 0
Membrane Proteins 0
Tumor Suppressor Protein p53 0
Endopeptidases EC 3.4.-
fibroblast activation protein alpha EC 3.4.21.-

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

10-19

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

Auteurs

Pablo Moreno-Ruiz (P)

Karolinska Institutet, Cancer Center Karolinska, Department of Oncology-Pathology, Stockholm, Sweden.

Sara Corvigno (S)

Karolinska Institutet, Cancer Center Karolinska, Department of Oncology-Pathology, Stockholm, Sweden; Uppsala University, Genetics and Pathology, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.

Nienke C Te Grootenhuis (NC)

University of Groningen, University Medical Center Groningen, Department of Obstetrics and Gynecology, Groningen, The Netherlands.

Linnéa La Fleur (L)

Uppsala University, Genetics and Pathology, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.

Max Backman (M)

Uppsala University, Genetics and Pathology, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.

Carina Strell (C)

Karolinska Institutet, Cancer Center Karolinska, Department of Oncology-Pathology, Stockholm, Sweden.

Artur Mezheyeuski (A)

Karolinska Institutet, Cancer Center Karolinska, Department of Oncology-Pathology, Stockholm, Sweden; Uppsala University, Genetics and Pathology, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.

Gabriele Hoelzlwimmer (G)

Roche Innovation Center Munich Penzberg, Germany.

Christian Klein (C)

Roche Innovation Center Zurich, Schlieren, Switzerland.

Johan Botling (J)

Uppsala University, Genetics and Pathology, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.

Patrick Micke (P)

Uppsala University, Genetics and Pathology, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.

Arne Östman (A)

Karolinska Institutet, Cancer Center Karolinska, Department of Oncology-Pathology, Stockholm, Sweden. Electronic address: Arne.Ostman@ki.se.

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Classifications MeSH