BackgroundIn 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.MethodsMMP-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.ResultsSignificant 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.ConclusionsDifferential 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2407-14-609) contains supplementary material, which is available to authorized users.

Supplemental Table 3A. Importantly, much like DP103, the highest levels of MMP9 were found in primary breast tumors that showed metastasis compared with nonmetastatic or benign tumors (Figure 3E). Importantly, the correlation between DP103 and MMP9 a strong positive clinical correlation between expression of DP103 and MMP9 (P < 0.001 in both cohorts). To further substantiate this finding, we next investigated whether a similar correlation between DP103 and MMP9 expression existed in the cohort from 1-3) or pBO-BI-DP103 (lanes 4-6) were either left untreated or treated with CPT (10 μM) for indicated times. Protein extracts analyzed by EMSA and Western blotting using anti-DP103 and anti-β-actin antibodies (top panel). (G) MDA-MB-231 cells transfected with either control siRNA (ctsi) or siRNA against DP103 and subjected to CPT (10 μM) stimulation at the indicated times. Cells were harvested and lysates evaluated by Western blotting for the indicated proteins. Fold difference in protein DNA binding indicated in E and F for EMSA and for protein expression changes indicated in G for Western blot.

Breast cancer is a heterogeneous disease comprising the estrogen receptor (ER)–positive luminal subtype which is subdivided into luminal A and luminal B and ER-negative breast cancer which includes the triple-negative subtype. This study has four aims: 1) to examine whether Minichromosome Maintenance (MCM)2, MCM4, and MCM6 can be used as markers to differentiate between luminal A and luminal B subtypes; 2) to study whether MCM2, MCM4, and MCM6 are highly expressed in triple-negative breast cancer, as there is an urgent need to search for surrogate markers in this aggressive subtype, for drug development purposes; 3) to compare the prognostic values of these markers in predicting relapse-free survival; and 4) to compare the three approaches used for scoring the protein expression of these markers by immunohistochemistry (IHC). MCM2, MCM4, MCM6, and MKI67 mRNA expression was first studied using in silico analysis of available breast cancer datasets. We next used IHC to evaluate their protein expression on tissue microarrays using three scoring methods. MCM2, MCM4, and MCM6 can help in distinction between luminal A and luminal B whose therapeutic management and clinical outcomes are different. MCM2, MCM4, MCM6, and Ki-67 are highly expressed in breast cancer of high histological grades that comprise clinically aggressive tumors such as luminal B, HER2-positive, and triple-negative subtypes. Low transcript expression of these markers is associated with increased probability of relapse-free survival. A positive relationship exists among the three scoring methods of each of the four markers. An independent validation cohort is needed to confirm their clinical utility.