Journal
HISTOPATHOLOGY
Volume 75, Issue 6, Pages 916-930Publisher
WILEY
DOI: 10.1111/his.13956
Keywords
breast cancer; inflammatory cells; matrix metalloproteinase 11; metastasis; prognosis
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Funding
- Consejeria de Economia y Empleo del Principado de Asturias [GRUPIN14-116] Funding Source: Medline
- Gobierno del Principado de Asturias [BP14-128] Funding Source: Medline
- Consejería de Economía y Empleo del Principado de Asturias [GRUPIN14-116] Funding Source: Medline
- Instituto de Salud Carlos III and co-funded by European Union (FEDER) [PI17/02236] Funding Source: Medline
- Instituto de Salud Carlos III and co-funded by European Union (ERDF) [PI17, 02236
- ] Funding Source: Medline
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Aims It is known that matrix metalloproteinase (MMP)-11 has a role in tumour development and progression, and also that immune cells can influence cancer cells to increase their proliferative and invasive properties. The aim of the present study was to propose the evaluation of MMP11 expression by intratumoral mononuclear inflammatory cells (MICs) as a useful biological marker for breast cancer prognosis. Methods and results This study comprised 246 women with invasive breast carcinoma, and a long follow-up period. Patients were stratified with regard to nodal status and to the development of metastatic disease. The median follow-up period in patients without metastasis was 146 months and in patients with metastatic disease 31 months. MMP11 was determined by immunohistochemistry. For relapse-free survival (RFS) and overall survival (OS) analysis we used the Cox's univariate method. Cox's regression model was used to examine the interactions between different prognostic factors in a multivariate analysis. Conclusions Our results showed that MMP11 expression by stromal cells was significantly associated with prognosis. MMP11 expression by cancer-associated fibroblasts (CAFs) was associated with both shortened RFS and OS, but MMP11 expression by MICs showed a stronger association with both shortened RFS and OS, therefore being the most potent and independent factor to predict RFS and OS.
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