Development and External Validation of an M2 Macrophage-Related Prognostic Signature in Breast Cancer Using Multi-Omics Data and Machine Learning.
4 affiliations
- 1Department of Pathology, Mudanjiang Medical University, Mudanjiang, Heilongjiang, People's Republic of China.
- 2Department of Pathology, The Second People's Hospital of Mudanjiang City, Mudanjiang, Heilongjiang, People's Republic of China.
- 3Department of Orthopedic Surgery, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang, Heilongjiang, People's Republic of China.
- 4Key Laboratory of Cancer Prevention and Treatment of Heilongjiang Province, Mudanjiang Medical University, Mudanjiang, Heilongjiang, People's Republic of China.
Abstract
Purpose
Tumor-associated macrophages (TAMs), particularly the M2-like phenotype, are central regulators of breast cancer progression; however, clinically applicable models capturing their functional heterogeneity and biological mechanisms remain limited.Patients and methods
We integrated single-cell RNA sequencing, spatial transcriptomics, and bulk RNA-seq data to construct an M2 macrophage-centered gene landscape. A machine learning framework based on 10-fold cross-validation was used to develop a prognostic signature in the TCGA-BRCA cohort (training set), with external validation in the independent GSE96058 cohort. Immune infiltration, genomic instability, pathway activity, and cell-cell communication were analyzed. KLF4 was examined in breast cancer cells and macrophages using qRT-PCR, Western blotting, siRNA-mediated knockdown, and a Transwell co-culture system.Results
We identified a 16-gene M2 macrophage-related signature (M2MMS) that stratified patients into subgroups with distinct survival outcomes in both cohorts. High-risk tumors showed M2 macrophage enrichment, an immunosuppressive microenvironment, elevated genomic instability, and activation of E2F and MYC proliferative programs. Cell-cell communication analysis identified MDK-NCL as a dominant tumor-TME signaling axis. KLF4 was upregulated in breast cancer cells and in macrophages after co-culture, and silencing KLF4 attenuated CD206 induction, indicating that KLF4 is functionally involved in tumor cell-induced M2-like polarization in vitro.Conclusion
The M2MMS links M2 macrophage-driven immune remodeling to breast cancer prognosis and provides a basis for risk stratification and mechanistic investigation. KLF4 represents a regulatory node in tumor-macrophage interaction in vitro; its role in vivo and the clinical utility of the M2MMS require further validation.
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BibTeX
@article{liu2026development,
title = {{Development and External Validation of an M2 Macrophage-Related Prognostic Signature in Breast Cancer Using Multi-Omics Data and Machine Learning.}},
author = {Yang Liu and Ye Liu and Hongyan Wang and Ziyang Xiao and Xinyue Chang and Zitao Li and Sufen Guo},
journal = {Breast cancer (Dove Medical Press)},
year = {2026},
month = oct,
doi = {10.2147/bctt.s636369},
url = {https://europepmc.org/article/MED/42928788},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Development and External Validation of an M2 Macrophage-Related Prognostic Signature in Breast Cancer Using Multi-Omics Data and Machine Learning.
AU - Yang Liu
AU - Ye Liu
AU - Hongyan Wang
AU - Ziyang Xiao
AU - Xinyue Chang
AU - Zitao Li
AU - Sufen Guo
PY - 2026
DA - 2026/10/21
JO - Breast cancer (Dove Medical Press)
DO - 10.2147/bctt.s636369
UR - https://europepmc.org/article/MED/42928788
AB - Purpose Tumor-associated macrophages (TAMs), particularly the M2-like phenotype, are central regulators of breast cancer progression; however, clinically applicable models capturing their functional heterogeneity and biological mechanisms remain limited.Patients and methods We integrated single-cell RNA sequencing, spatial transcriptomics, and bulk RNA-seq data to construct an M2 macrophage-centered gene landscape. A machine learning framework based on 10-fold cross-validation was used to develop a prognostic signature in the TCGA-BRCA cohort (training set), with external validation in the independent GSE96058 cohort. Immune infiltration, genomic instability, pathway activity, and cell-cell communication were analyzed. KLF4 was examined in breast cancer cells and macrophages using qRT-PCR, Western blotting, siRNA-mediated knockdown, and a Transwell co-culture system.Results We identified a 16-gene M2 macrophage-related signature (M2MMS) that stratified patients into subgroups with distinct survival outcomes in both cohorts. High-risk tumors showed M2 macrophage enrichment, an immunosuppressive microenvironment, elevated genomic instability, and activation of E2F and MYC proliferative programs. Cell-cell communication analysis identified MDK-NCL as a dominant tumor-TME signaling axis. KLF4 was upregulated in breast cancer cells and in macrophages after co-culture, and silencing KLF4 attenuated CD206 induction, indicating that KLF4 is functionally involved in tumor cell-induced M2-like polarization in vitro.Conclusion The M2MMS links M2 macrophage-driven immune remodeling to breast cancer prognosis and provides a basis for risk stratification and mechanistic investigation. KLF4 represents a regulatory node in tumor-macrophage interaction in vitro; its role in vivo and the clinical utility of the M2MMS require further validation.
SN - 1179-1314
ER -