Single-cell RNA sequencing reveals different cellular states in malignant cells and the tumor microenvironment in primary and metastatic ER-positive breast cancer

Metastatic breast cancer remains largely incurable, and the mechanisms driving the transition from primary to metastatic breast cancer remain elusive. We analyzed the complex landscape of estrogen receptor (ER)-positive breast cancer primary and metastatic tumors using scRNA-seq data from twenty-three female patients with either primary or metastatic disease. By employing single-cell transcriptional profiling of unpaired patient samples, we sought to elucidate the genetic and molecular mechanisms underlying changes in the metastatic tumor ecosystem. We identified specific subtypes of stromal and immune cells critical to forming a pro-tumor microenvironment in metastatic lesions, including CCL2+ macrophages, exhausted cytotoxic T cells, and FOXP3+ regulatory T cells. Analysis of cell-cell communication highlights a marked decrease in tumor-immune cell interactions in metastatic tissues, likely contributing to an immunosuppressive microenvironment. In contrast, primary breast cancer samples displayed increased activation of the TNF-α signaling pathway via NF-kB, indicating a potential therapeutic target. Our study comprehensively characterizes the transcriptional landscape encompassing primary and metastatic breast cancer.

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Publication Details

Journal
npj Breast Cancer
Published
2025-08-26
DOI
https://doi.org/10.1038/s41523-025-00808-w
Citations
4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
3.22

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article

Single-cell RNA sequencing reveals different cellular states in malignant cells and the tumor microenvironment in primary and metastatic ER-positive breast cancer

Hisham Mohammed, Aaron R. Doe, Fariba Behbod, Aysegul Ors et al.
4 citations
npj Breast Cancer
Single-cell and spatial transcriptomics
3.22
article

Single-cell RNA sequencing reveals different cellular states in malignant cells and the tumor microenvironment in primary and metastatic ER-positive breast cancer

Hisham Mohammed, Aaron R. Doe, Fariba Behbod, Aysegul Ors, Mahnaz Janghorban, Matthew J. Rames, Tugba Y. Ozmen, Xi Li, Gordon B. Mills, Furkan Ozmen
article en
4 citations

Abstract

Metastatic breast cancer remains largely incurable, and the mechanisms driving the transition from primary to metastatic breast cancer remain elusive. We analyzed the complex landscape of estrogen receptor (ER)-positive breast cancer primary and metastatic tumors using scRNA-seq data from twenty-three female patients with either primary or metastatic disease. By employing single-cell transcriptional profiling of unpaired patient samples, we sought to elucidate the genetic and molecular mechanisms underlying changes in the metastatic tumor ecosystem. We identified specific subtypes of stromal and immune cells critical to forming a pro-tumor microenvironment in metastatic lesions, including CCL2+ macrophages, exhausted cytotoxic T cells, and FOXP3+ regulatory T cells. Analysis of cell-cell communication highlights a marked decrease in tumor-immune cell interactions in metastatic tissues, likely contributing to an immunosuppressive microenvironment. In contrast, primary breast cancer samples displayed increased activation of the TNF-α signaling pathway via NF-kB, indicating a potential therapeutic target. Our study comprehensively characterizes the transcriptional landscape encompassing primary and metastatic breast cancer.

npj Breast CancerVol. 11(1)
Oregon Health & Science University (US), University of Kansas Medical Center (US)
Breast Cancer Research Foundation, Georgia Clinical and Translational Science Alliance, National Institutes of Health, Knight Cancer Institute, Oregon Health and Science University, National Cancer Institute, National Center for Advancing Translational Sciences, Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health and Science University
Openalex Percentile: Top 8%
Single-cell and spatial transcriptomics
3.22
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