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      Expression of matrix metalloproteinases and their inhibitors in different immunohistochemical-based molecular subtypes of breast cancer

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          Abstract

          Background

          Metalloproteinases (MMPs) and their tissue inhibitors of metalloproteinases (TIMPs) are involved in several key pathways of tumor growth, invasion and metastasis, but little is known about their expression according to different molecular subtypes of breast cancer. The aims of this study were to assess the prevalence and clinical significance of MMP and TIMP expression in invasive breast cancer and to determine its association with immunohistochemical-based molecular classification.

          Methods

          Tissue microarray sections were immunostained for estrogen receptor-α (ER-α), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), cytokeratin (CK) 5/6, epidermal growth factor receptor (EGFR) and with specific antibodies against MMP-1, 2, 7, 9, 11, 13, and 14 and TIMP-1, 2, and 3. Based on the immunostaining data from five of the markers used (ER-α, PR, HER2, EGFR and CK5/6), three major subtypes (123 luminal A, 31 basal-like, and 17 HER2-overexpressing) were selected.

          Results

          Statistically significant differences in the expression of MMPs and TIMPs among the three subtypes were found in tumoral MMP7 ( P = 0.005), tumoral MMP-9 ( P = 0.000), tumoral MMP-13 ( P = 0.016) and stromal MMP-13 ( P = 0.016). The incidence of tumoral MMP-9 expression in the HER2-overexpressing subtype was significantly higher than in the luminal A subtype ( P = 0.021). Tumoral MMP-9 and stromal MMP-13 expression were significantly higher in the HER2-overexpressing subtype than in the basal-like subtype ( P = 0.000 and P = 0.016, respectively). Tumoral MMP-7 expression was significantly higher in the basal-like subtype compared to luminal A ( P = 0.007) and HER2-overexpressing subtype ( P = 0.004). Tumoral MMP-13 showed a higher expression in the basal-like subtype than in the HER2-overexpressing subtype ( P = 0.010). In multivariate analysis, stage and stromal MMP-1 expression were significantly related to overall survival. Stage was of independent prognostic significance for disease-free survival.

          Conclusion

          We found some variations in MMP and TIMP expression among the immunohistochemical-based molecular subtypes of breast carcinomas, suggesting differences in their tumor pathophysiology. Additional studies are needed to determine the mechanisms underlying the differences of MMP and TIMP expression in the molecular subtypes for the development of specific therapeutic targets for breast cancer subtypes.

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          Most cited references 48

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          Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.

          The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
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            Gene expression profiling predicts clinical outcome of breast cancer.

            Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.
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              Repeated observation of breast tumor subtypes in independent gene expression data sets.

              Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.
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                Author and article information

                Contributors
                roengreen3@hanmail.net
                jshinlee@hanmail.net
                drydchoi@chonnam.ac.kr
                azimmed@hanmail.net
                jhlee@chonnam.ac.kr
                jhnam@chonnam.ac.kr
                cchoi@chonnam.ac.kr
                succeedsoon@hanmail.net
                mhpark@chonnam.ac.kr
                jhyoon@chonnam.ac.kr
                ujingogo@paran.com
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                16 December 2014
                2014
                : 14
                : 1
                Affiliations
                [ ]Deparment of Pathology, Chonnam National University Medical School, Gwangju, Republic of Korea
                [ ]Department of Surgery, Chonnam National University Medical School, Gwangju, Republic of Korea
                [ ]Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea
                Article
                5143
                10.1186/1471-2407-14-959
                4301952
                25510449
                © Kim et al.; licensee BioMed Central. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

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