MMP-9 expression varies according to molecular subtypes of breast cancer

Background: In 2014, breast cancer remains a major cause of mortality worldwide mostly due to tumor relapse and metastasis. There is currently a great interest in identifying cancer biomarkers and signalling pathways mechanistically related to breast cancer progression. Matrix metalloproteinase-9 (MMP-9) is a member of matrix degrading enzymes involved in cancer development, invasion and metastasis. Our objective was to investigate MMP-9 expression in normal human breast tissue and to compare it to that of breast cancer of various histological grades and molecular subtypes. We also sought to correlate MMP-9 expression with the incidence of metastasis, survival rates and relapse in breast cancer patients. Methods: MMP-9 was first studied using in silico analysis on available DNA microarray and RNA sequencing data of human breast cancer tissues and human breast cancer cell lines. We next ascertained MMP-9 expression in both normal breast tissue and in human breast carcinoma tissue microarrays. Results: Significant increase in MMP-9 expression was found in breast cancer cells where compared to normal breast tissue. A positive correlation could also be established between elevated levels of MMP-9 and breast cancer of high histological grade. Furthermore, our results indicate that not only MMP-9 is differentially expressed between each molecular subset but also, more importantly MMP-9 overexpression revealed itself as a startling feature of triple-negative and HER2-positive breast cancers. Lastly, the clinical relevance of MMP-9 overexpression is strongly supported by its significant association with a higher incidence of metastasis and relapse. Conclusions: Differential expression of MMP-9 reflects the extent of cellular differentiation in breast cancer cells and is closely related to the most aggressive subtypes of breast cancer. Hence, MMP-9 is a promising prognostic biomarker of high-grade breast cancer. In our opinion, MMP-9 expression could help segregate subsets of aggressive breast cancer into clinically meaningful subtypes.