Obesity-Associated Extracellular Matrix Remodeling Promotes a Macrophage Phenotype Similar to Tumor-Associated Macrophages.


Journal

The American journal of pathology
ISSN: 1525-2191
Titre abrégé: Am J Pathol
Pays: United States
ID NLM: 0370502

Informations de publication

Date de publication:
10 2019
Historique:
received: 19 07 2018
revised: 03 06 2019
accepted: 18 06 2019
pubmed: 20 7 2019
medline: 28 3 2020
entrez: 20 7 2019
Statut: ppublish

Résumé

Obesity is associated with adipose inflammation, defined by macrophages encircling dead adipocytes, as well as extracellular matrix (ECM) remodeling and increased risk of breast cancer. Whether ECM affects macrophage phenotype in obesity is uncertain. A better understanding of this relationship could be strategically important to reduce cancer risk or improve outcomes in the obese. Using clinical samples, computational approaches, and in vitro decellularized ECM models, this study quantified the relative abundance of pro-inflammatory (M1) and anti-inflammatory (M2) macrophages in human breast adipose tissue, determined molecular similarities between obesity and tumor-associated macrophages, and assessed the regulatory effect of obese versus lean ECM on macrophage phenotype. Our results suggest that breast adipose tissue contains more M2- than M1-biased macrophages across all body mass index categories. Obesity further increased M2-biased macrophages but did not affect M1-biased macrophage density. Gene Set Enrichment Analysis suggested that breast tissue macrophages from obese versus lean women are more similar to tumor-associated macrophages. These changes positively correlated with adipose tissue interstitial fibrosis, and in vitro experiments indicated that obese ECM directly stimulates M2-biased macrophage functions. However, mammographic density cannot be used as a clinical indicator of these changes. Collectively, these data suggest that obesity-associated interstitial fibrosis promotes a macrophage phenotype similar to tumor-associated macrophages, which may contribute to the link between obesity and breast cancer.

Identifiants

pubmed: 31323189
pii: S0002-9440(18)30607-2
doi: 10.1016/j.ajpath.2019.06.005
pmc: PMC6880774
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2019-2035

Subventions

Organisme : NCI NIH HHS
ID : R01 CA108539
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA210184
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Organisme : NIH HHS
ID : T32 OD011000
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA215797
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA210180
Pays : United States

Informations de copyright

Copyright © 2019 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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Auteurs

Nora L Springer (NL)

Field of Biological and Biomedical Sciences, Cornell University, Ithaca, New York; Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York; Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, Kansas.

Neil M Iyengar (NM)

Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York; Department of Medicine, Weill Cornell Medicine, New York, New York.

Rohan Bareja (R)

Caryl and Israel Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York.

Akanksha Verma (A)

Caryl and Israel Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York.

Maxine S Jochelson (MS)

Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York.

Dilip D Giri (DD)

Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.

Xi K Zhou (XK)

Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, New York.

Olivier Elemento (O)

Caryl and Israel Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York.

Andrew J Dannenberg (AJ)

Department of Medicine, Weill Cornell Medicine, New York, New York.

Claudia Fischbach (C)

Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York; Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, New York. Electronic address: cf99@cornell.edu.

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Classifications MeSH