Stromal VEGF-C expression predicts nodal metastasis: implications for axillary surgery de-escalation in breast cancer
6 affiliations
- 1Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden
- 2Lund University Cancer Centre, Lund University, Lund, Sweden
- 3Division of Oncology, Department of Clinical Sciences, Lund University, Lund, Sweden
- 4SciLifeLab, Department of Laboratory Medicine, Lund University, Lund, Sweden
- 5Department of Gastroenterology and Surgery, Skåne University Hospital, Malmö, Sweden
- 6CIRCE: Centre for Interdisciplinary Research on Cancer and Equity in Women, Lund University, Lund, Sweden
Abstract
Accurate preoperative prediction of lymph node metastasis (LNM) could facilitate more individualized axillary management in breast cancer by improving identification of patients at lower risk of nodal involvement while maintaining appropriate staging for those at higher risk. Yet, reliable molecular predictors of LNM remain lacking. VEGF-C, a key driver of lymphangiogenesis, is expressed in both cancer cell and stromal compartments, but its clinical utility is unclear. In a prospectively enrolled cohort, we assessed stromal and cancer cell VEGF-C expression by immunohistochemistry using both manual scoring and a novel automated image analysis script enabling objective, reproducible classification of stromal versus epithelial cells at scale. Stromal VEGF-C was independently associated with LNM after adjustment for established predictors (P = 0.004), with prediction models reaching AUCs of up to 0.784. Cancer cell VEGF-C added no predictive value. In exploratory analyses, stromal VEGF-C provided predictive information comparable to that of vascular invasion, a strong predictor of LNM that is generally unavailable preoperatively. These findings identify stromal VEGF-C as a potential preoperative biomarker for nodal risk stratification. However, given the observational and predictive nature of the present study, stromal VEGF-C should be considered complementary to, rather than a replacement for, established pathological predictors. Its potential contribution to future axillary surgery de-escalation strategies warrants prospective validation.
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BibTeX
@article{jeannot2026stromal,
title = {{Stromal VEGF-C expression predicts nodal metastasis: implications for axillary surgery de-escalation in breast cancer}},
author = {Pauline Jeannot and Emelie Edvardsson and Oscar Hernquist and Cornelia Brandt and Linnea Fischhaber and Anna-Maria Larsson and Beatrice Öhlund and Kristian Pietras and Pär-Ola Bendahl and Charlotte Rolny and Lisa Ryden},
journal = {NPJ Precision Oncology},
year = {2026},
month = nov,
doi = {10.1038/s41698-026-01770-x},
url = {https://doi.org/10.1038/s41698-026-01770-x},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Stromal VEGF-C expression predicts nodal metastasis: implications for axillary surgery de-escalation in breast cancer
AU - Pauline Jeannot
AU - Emelie Edvardsson
AU - Oscar Hernquist
AU - Cornelia Brandt
AU - Linnea Fischhaber
AU - Anna-Maria Larsson
AU - Beatrice Öhlund
AU - Kristian Pietras
AU - Pär-Ola Bendahl
AU - Charlotte Rolny
AU - Lisa Ryden
PY - 2026
DA - 2026/11/05
JO - NPJ Precision Oncology
DO - 10.1038/s41698-026-01770-x
UR - https://doi.org/10.1038/s41698-026-01770-x
AB - Accurate preoperative prediction of lymph node metastasis (LNM) could facilitate more individualized axillary management in breast cancer by improving identification of patients at lower risk of nodal involvement while maintaining appropriate staging for those at higher risk. Yet, reliable molecular predictors of LNM remain lacking. VEGF-C, a key driver of lymphangiogenesis, is expressed in both cancer cell and stromal compartments, but its clinical utility is unclear. In a prospectively enrolled cohort, we assessed stromal and cancer cell VEGF-C expression by immunohistochemistry using both manual scoring and a novel automated image analysis script enabling objective, reproducible classification of stromal versus epithelial cells at scale. Stromal VEGF-C was independently associated with LNM after adjustment for established predictors (P = 0.004), with prediction models reaching AUCs of up to 0.784. Cancer cell VEGF-C added no predictive value. In exploratory analyses, stromal VEGF-C provided predictive information comparable to that of vascular invasion, a strong predictor of LNM that is generally unavailable preoperatively. These findings identify stromal VEGF-C as a potential preoperative biomarker for nodal risk stratification. However, given the observational and predictive nature of the present study, stromal VEGF-C should be considered complementary to, rather than a replacement for, established pathological predictors. Its potential contribution to future axillary surgery de-escalation strategies warrants prospective validation.
SN - 2397-768X
ER -