Details

Autor(en) / Beteiligte

• Ramos, Edneia A S
• Silva, Camila T da
• Manica, Graciele C M
• Pereira, Isabela T
• Klassen, Liliane M B
• Ribeiro, Enilze M S F
• Cavalli, Iglenir J
• Braun-Prado, Karin
• Lima, Rubens S
• Urban, Cicero A
• Costa, Fabrício F
• Noronha, Lucia de
• Klassen, Giseli

Titel

Worse prognosis in breast cancer patients can be predicted by immunohistochemical analysis of positive MMP-2 and negative estrogen and progesterone receptors

Ist Teil von

• Revista da Associacao Medica Brasileira (1992), 2016-11, Vol.62 (8), p.774-781

Ort / Verlag

Brazil: Associação Médica Brasileira

Erscheinungsjahr

2016

Quelle

MEDLINE

Beschreibungen/Notizen

• Breast cancer is the most cause of death, and approximately 90% of these deaths are due to metastases. Matrix metalloproteinase-2 (MMP-2) gelatinase activity is able to degrade a major constituent of the tumor microenvironment, type IV collagen. Two well-established proteins used as markers in clinical practice for breast cancer are the receptors for estrogen (ER) and progesterone (PR). Although the presence of these receptors has been associated with a better prognosis, loss of these proteins can occur during tumor progression, with subsequent resistance to hormone therapy. To study the correlation among MMP-2, ER, and PR, as well as the establishment of the metastatic process in primary breast tumors. Breast cancer samples (n=44) were analyzed by immunohistochemistry for MMP-2, ER, and PR. We observed that 90% of patients who had metastases and died showed positive staining for MMP-2 (p=0.0082 for both). Using Kaplan-Meier analysis, we found that negative ER patients who were also positive for MMP-2 had even worse disease-free survival (DFS) and overall survival (OS) (p= 0.012 and p=0.005, respectively). Similar results were found in PR-negative patients for DFS (a trend p=0.077) and OS (p=0.038). Regardless of our small sample size (n=44), the data obtained strongly suggest that MMP-2 in combination with already well-established markers could help to predict the emergence of metastases and death in patients with breast cancer.