Identification and characterization of new biomarkers in aggressive subtypes of breast cancer

In 2015, breast cancer remains a leading cause of death among women worldwide due to relapse and metastases. However, mammary tumors are known to be heterogeneous in terms of their clinical course and response to treatment, despite a seemingly similar phenotype. There is therefore an obvious need to identify and characterize new biomarkers of progression in breast cancers so that each tumor can be properly classified. Our hypothesis is that each breast cancer has its own set of genomic abnormalities or altered pattern of gene expression that can explain the aggressiveness of each tumor, its ability to metastasize and its response to chemotherapeutic agents or other forms of targeted therapies. In this study, our aim is to identify and characterize new biomarkers with prognostic value in aggressive subsets of breast cancer focusing primarily on triple-negative tumors and luminal B breast cancer.  To achieve those aims, we conducted an in silico search from public databases of DNA microchip and RNA sequencing data. We next constructed seven tissue microarrays (TMA) using paraffin blocks from human breast cancer along with normal breast to examine the differential expression of new putative markers: ANXA1, MMP-9, DP103 and MCM2. Expression levels measured by immunohistochemistry were then compared to other conventional markers of breast cancer (ER, PR, HER2, Ki-67, CK 5/6, FOXA1) and correlated with clinical data (overall survival and metastasis). By comparing the relative expression of these markers in human breast tumors we were able to pinpoint the important role of ANXA1, MMP-9, DP103, and MCM2 in aggressive tumor subtypes recognized for their poor clinical course. Firstly, we have shown that ANXA1 expression is severely deregulated in high-grade breast cancers including triple-negative and, to some extent, HER2-positive breast cancers. In addition, our results also indicated a possible role of ANXA1 in regulating EMT and breast cancer cell metastasis. Secondly, expression of MMP-9 was found to mirror the degree of tumor differentiation and to correlate with breast cancers of unfavorable outcome. This implies that MMP-9 can help better characterize the biology of breast carcinoma and to identify subgroups of high-risk breast tumors. In fact, we found that high levels of MMP-9 in tumors were associated with increased metastatic dissemination, early relapse and reduced survival.  Thirdly, we demonstrated that MCM2 is overexpressed in triple-negative, HER2 positive and luminal B breast cancer in comparison to luminal A breast cancer (p-value < 0.0001). Our findings support the notion that MCM2 can be used to distinguish luminal A from luminal B breast cancer based on a 40% index cut-point. However, an independent validation cohort is needed to confirm the clinical utility of MCM2. Lastly, our results suggest that ANXA1, MMP-9 and MCM2 are valuable genes/proteins candidate that can help better understand the mechanisms involved in tumor progression and metastasis. One may also envisage their use, alone or in combination with other genes, in the development of a multi-gene panel or multiplex proteomic assay to predict clinical outcome and guide therapeutic decisions.

Keyphrases: ANXA1, MMP-9, MCM2, Ki-67, Human breast cancer, Biomarker, In silico analysis, Tissue microarray