Metastatic Behavior of Breast Cancer Subtypes
Abstract
Purpose: Prognostic and predictive factors are well established in early-stage breast cancer, but less is known about which metastatic sites will be affected. Methods: Patients with early-stage breast cancer diagnosed between 1986 and 1992 with archival tissue were included. Subtypes were defined as luminal A, luminal B, luminal/human epidermal growth factor receptor 2 (HER2), HER2 enriched, basal-like, and triple negative (TN) nonbasal. Distant sites were classified as brain, liver, lung, bone, distant nodal, pleural/peritoneal, and other. Cumulative incidence curves were estimated for each site according to competing risks methods. Association between the site of relapse and subtype was assessed in multivariate models using logistic regression. Results: Median follow-up time among 3,726 eligible patients was 14.8 years. Median durations of survival with distant metastasis were 2.2 (luminal A), 1.6 (luminal B), 1.3 (luminal/HER2), 0.7 (HER2 enriched), and 0.5 years (basal-like; P < .001). Bone was the most common metastatic site in all subtypes except basal-like tumors. In multivariate analysis, compared with luminal A tumors, luminal/HER2 and HER2-enriched tumors were associated with a significantly higher rate of brain, liver, and lung metastases. Basal-like tumors had a higher rate of brain, lung, and distant nodal metastases but a significantly lower rate of liver and bone metastases. TN nonbasal tumors demonstrated a similar pattern but were not associated with fewer liver metastases. Conclusion: Breast cancer subtypes are associated with distinct patterns of metastatic spread with notable differences in survival after relapse.
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Woollie plausibly identified the most frequent sites of metastatic involvement otherwise known to be associated with the evaluated cancers (e.g., brain or bone metastases among the breast cancer cohort or hepatic metastases for colorectal cancer).
“Notably, Woollie plausibly identified the most frequent sites of metastatic involvement that are otherwise known to be associated with the evaluated cancers (e.g., brain or bone metastases among the cohort with breast cancer or hepatic metastases for those with colorectal cancer32,33).”
From Large language model trained on clinical oncology data predicts cancer progression (2025) · cites this paper as [32]
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- Authors
- Kennecke, H., Yerushalmi, R., Woods, R., Cheang, M. C. U., Voduc, D., Speers, C. H., Nielsen, T. O., & Gelmon, K.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- ORCID
- Venue
- Journal of Clinical Oncology
- Published
- 2010-07-10
- Volume
- 28
- Issue
- 20
- Pages
- 3271-3277
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2116760308
- Cited by
- 2,262
- References
- 52
- Citations by year
- 2026: 96 · 2025: 147 · 2024: 159 · 2023: 184 · 2022: 179 · 2021: 227 · 2020: 199 · 2019: 140 · 2018: 152 · 2017: 154 · 2016: 143 · 2015: 134 · 2014: 107 · 2013: 92 · 2012: 72
- FWCI
- 24.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Clinical Oncology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Metastasis and carcinoma case studies
- Keywords
- breast cancer subtypes, metastatic sites, early breast cancer, luminal A, luminal B, HER2-enriched breast cancer, basal-like, triple-negative breast cancer, brain metastases, liver metastasis, lung metastasis, bone metastasis, survival after relapse, competing risks
- MeSH terms
- Aged, Bone Neoplasms, Breast Neoplasms, Female, Follow-Up Studies, Humans, Middle Aged, Neoplasm Metastasis, Tissue Array Analysis, ErbB Receptors
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