Cell populations in human breast cancers are molecularly and biologically distinct with age

Aging is associated with increased breast cancer risk, and the oldest and youngest patients have worse outcomes, irrespective of subtype. It is unknown how age affects cells in the breast tumor microenvironment or how they contribute to age-related pathology. Here we discover age-associated differences in cell states in human estrogen receptor-positive and triple-negative breast cancers using analyses of existing bulk and single-cell transcriptomic data. We generate and apply an Age-Specific Program ENrichment (ASPEN) analysis pipeline, revealing age-related changes, including increased tumor cell epithelial-mesenchymal transition and cancer-associated fibroblast inflammatory responses in triple-negative breast cancer. Estrogen receptor-positive breast cancer displays increased ESR1 expression and reduced vascular and immune cell metabolism with age. Cell interactome analysis reveals candidate signaling pathways that drive age-related cell states. Spatial analyses across independent clinical cohorts support the computational findings. This work identifies potential targets for age-adapted therapeutic interventions for breast cancer.

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Publication Details

Journal
Nature Aging
Published
2025-11-04
DOI
https://doi.org/10.1038/s43587-025-00984-1
Citations
2
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.61

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article

Cell populations in human breast cancers are molecularly and biologically distinct with age

Peter van Galen, Elizabeth A. Mittendorf, Milos Spasic, Hanyun Zhang et al.
2 citations
Nature Aging
Single-cell and spatial transcriptomics
1.61
article

Cell populations in human breast cancers are molecularly and biologically distinct with age

Peter van Galen, Elizabeth A. Mittendorf, Milos Spasic, Hanyun Zhang, Alexander Swarbrick, Julia Chen, Esther Sauras-Colón, Busem Binboğa Kurt, Sandra S. McAllister, Rachel A. Freedman, Adrienne Parsons, Meghana Manjunath, Beyza Koca
article en
2 citations

Abstract

Aging is associated with increased breast cancer risk, and the oldest and youngest patients have worse outcomes, irrespective of subtype. It is unknown how age affects cells in the breast tumor microenvironment or how they contribute to age-related pathology. Here we discover age-associated differences in cell states in human estrogen receptor-positive and triple-negative breast cancers using analyses of existing bulk and single-cell transcriptomic data. We generate and apply an Age-Specific Program ENrichment (ASPEN) analysis pipeline, revealing age-related changes, including increased tumor cell epithelial-mesenchymal transition and cancer-associated fibroblast inflammatory responses in triple-negative breast cancer. Estrogen receptor-positive breast cancer displays increased ESR1 expression and reduced vascular and immune cell metabolism with age. Cell interactome analysis reveals candidate signaling pathways that drive age-related cell states. Spatial analyses across independent clinical cohorts support the computational findings. This work identifies potential targets for age-adapted therapeutic interventions for breast cancer.

Nature AgingVol. 5(12)
Broad Institute (US), Brigham and Women's Hospital (US), Harvard University (US), Garvan Institute of Medical Research (AU), UNSW Sydney (AU), Institut de Recerca Biomèdica Catalunya Sud (ES), Dana-Farber Cancer Institute (US), Dana-Farber/Harvard Cancer Center (US), Harvard Stem Cell Institute (US), Dana-Farber Brigham Cancer Center (US), Mass General Brigham (US)
U.S. Department of Defense, American Association for Cancer Research, Breast Cancer Research Foundation, Global Fund for Women, MPN Research Foundation, Edward P. Evans Foundation, Vera and Joseph Dresner Foundation, Pelotonia, National Breast Cancer Foundation, Petre Foundation, National Institutes of Health, Ludwig Center at Harvard, Medical Research Council, National Health and Medical Research Council, National Cancer Institute, Congressionally Directed Medical Research Programs
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
1.61
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