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Breast Cancer Res Treat. Author manuscript; available in PMC 2013 December 1.
Published in final edited form as:
PMCID: PMC3558527
NIHMSID: NIHMS418696

Plasma Matrix Metalloproteinases and Postmenopausal Breast Cancer Risk: A Nested Case-Control Study in the Multiethnic Cohort Study

Abstract

The survival of malignant breast cells depends upon remodeling of the extracellular matrix, including complex interactions with matrix metalloproteinases (MMPs). It has been hypothesized that circulating MMPs may serve as early indicators of breast cancer development in hospital-based case-control studies. A nested case-control study of the association of pre-diagnostic plasma levels of MMPs with the subsequent risk of postmenopausal breast cancer was conducted within the Multiethnic Cohort. During the follow-up period, 713 women with incident invasive breast cancer were identified and individually (1:1) matched to controls. Four types of MMPs (1, 2, 3, and 7) were analyzed by microsphere immunofluorescence assay. Mean plasma levels of MMPs did not differ significantly between cases and controls; nor were there differences in breast cancer risk by MMP level. No difference in the risk of breast cancer by plasma level of the MMPs was found within strata of age, or ethnicity, although MMP-1 levels were positively associated with breast cancer risk in obese women and women using hormone replacement medications (P Values for interaction < 0.05). Few significant differences in risk by levels of the MMPs were found by any of the clinical variables. Circulating MMPs were not associated with postmenopausal breast cancer risk.

Keywords: Breast cancer, matrix metalloproteinases, body mass index, hormone replacement therapy, neoplasm staging, nested case-control study

Breast cancer is the most common malignancy among women worldwide [1], but there are presently no validated, clinically useful circulating biomarkers for breast cancer [2]. Substantial interest has been generated in recent years regarding dysregulation of the extracellular matrix (ECM) as a critical component of malignant transformation and progression. Matrix metalloproteinases (MMPs) are a family of 23 known human enzymes capable of degrading essentially all macromolecules of the ECM [3, 4]. The importance of MMPs to cellular differentiation, proliferation, apoptosis, growth factor availability, tissue repair and remodeling is increasingly recognized [5]. MMPs have been linked to human disease development, chronic inflammation, and neurological disorders [3]. MMPs are more highly expressed in breast cancer tissue than in benign breast tissue [69]. Moreover, higher MMPs in serum or plasma have been associated with breast cancer risk [10, 11] and poor prognosis [1218]. However, no prospective studies or randomized trials have examined the role of circulating MMPs in the etiology of breast cancer.

We conducted a nested case-control study among women who contributed to the biospecimen repository of the Multiethnic Cohort study (MEC) to examine whether pre-diagnostic levels of MMPs were associated with the risk of postmenopausal breast cancer. MMPs can be divided into four groups based on domain structure and substrate specificity of the enzyme [5]. We selected one MMP in each group, among those which were suggested to be related with breast cancer in previous literatures [1020]. MMPs analyzed in this study were, the collagenase MMP-1, the gelatinase MMP-2, the stromelysin MMP-3, and the matrilysin MMP-7. We examined whether the associations of circulating MMPs with postmenopausal breast cancer incidence were independent of known risk factors for the disease and compared the relation of circulating MMPs levels to breast cancer risk within strata of clinical characteristics.

MATERIALS AND METHODS

Study population and data collection

A nested case-control study of postmenopausal breast cancer was conducted within the MEC, a prospective study established in Hawaii and Los Angeles between 1993 and 1996 [21]. More than 215,000 adults, ages 45 to 75 years, from five racial-ethnic groups (African-Americans, Native Hawaiians, Japanese-Americans, Latinos, and Whites), were enrolled in the cohort through completion of a detailed self-administered questionnaire regarding diet, lifestyle factors, and other potential disease determinants. A prospective biospecimen repository was developed during the follow-up period, largely between 2001 and 2006 among cohort members who agreed to provide a blood and urine specimen, along with a short interview form. Biospecimens were prospectively collected from 36,458 women. Blood samples were drawn and were processed within 4 hours of collection. Serum and plasma were processed to cryovials and stored at the vapor phase of liquid nitrogen (−186°C). About 95% of the participants contributing to the biorepository provided fasting (≥8 hours) blood samples. The MEC and the nested biospecimen study were approved by the Institutional Review Boards of the University of Hawaii and the University of Southern California.

Case ascertainment and control selection

Identification of incident, invasive breast cancer cases was accomplished through linkage to the population-based cancer registries covering Hawaii and California, participants in the Surveillance, Epidemiology, and End Results Program (SEER) of the National Cancer Institute in the United States and the National Program for Cancer Registries of the Centers for Disease Control and Prevention [22]. Breast cancer diagnoses were identified using the International Classification of Diseases for Oncology, Third Edition codes C50.0–C50.9 and were restricted to invasive malignancies [23]. Deaths were identified through linkage to death certificate files in Hawaii and California, as well as to the National Death Index. Incident breast cancer cases were verified through October, 2010, including 729 eligible postmenopausal women with a diagnosis of invasive breast cancer. Median follow-up from the date of blood draw to the date of breast cancer diagnosis was 4 years. One control per case was randomly selected from the pool of postmenopausal women in the biospecimen repository who were alive and free of breast cancer at the age of the case’s diagnosis and were matched to the case within strata of geographic location (Hawaii or California), race-ethnicity, birth year (±1 y), date of blood draw (±6 mo), time of blood draw (±2 h), hours fasting prior to blood draw (0–<6, 6–<8, 8–<10, and ≥10 h), and hormone replacement therapy use (HRT; as current versus not current) at the date blood was drawn. HRT use and fasting status were used as matching criteria to ensure that matched sets would be available for the assessment of analytes requiring fasting status or non-HRT use. We excluded 16 matched sets where either the case or control had MMP measurements below the limits of detection, leaving 713 matched pairs for statistical analysis.

Laboratory assays

Frozen heparin plasma samples were retrieved from the MEC biorepository for matched case-control sets. Laboratory personnel who thawed and analyzed the matched plasma were blinded to case-control status. Plasma and quality control samples were thawed immediately prior to use and assayed in duplicate after a 10-fold dilution. Concentrations of matrix metalloproteinases collagenase 1 (MMP-1), gelatinase A (MMP-2), stromelysin 1 (MMP-3) and matrilysin (MMP-7) were assayed in 50 uL diluted (1:10) plasma employing a microsphere immunofluorescence assay using fluorokine MAP multiplex kits which were commercially available (R&D Fluorokine® MAP, Minneapolis, MN, USA). These kits measured levels of complex form of pro-, mature and tissue inhibitor of MMP-1 (TIMP-1) for MMP-1, MMP-3, and MMP-7; and measured levels of pro- and mature complex of MMP-2. Fluorescent intensities were obtained with a dual-laser analyzer (Luminex® 200TM), and median fluorescence values were quantified against a standard curve using GraphPad Prism 5 software. Multiplexed analyses were performed according to the manufacturers’ instructions as previously described [24, 25]. Assays were conducted under yellow light to avoid sample and reagent degradation. Based on 47 duplicate and 23 triplet samples, between-batch coefficients of variation were 9.9% for MMP-1, 5.4% for MMP-2 and MMP-3, and 11.7% for MMP-7, and within-batch variation ranged from 3.7% to 7.9% for all analytes.

Statistical analyses

A preliminary examination of the data included comparisons of cases and controls with respect to several demographic characteristics and potential risk factors of interest. Geometric means of MMP levels were compared between cases and controls by the paired t-test. Pearson correlation coefficients were used to examine interrelations between the log-transformed plasma MMP levels. Conditional logistic regression of breast cancer incidence, with matched sets as strata, was used to explore the relationship with plasma MMPs. MMPs were modeled both as log continuous variables and as indicator variables representing quartiles based on the distribution of MMP levels among controls. Odds ratios (OR) and 95% confidence intervals (CI) were computed for a change in two standard deviations from the former model and for quartile categories from the latter model. Linear trends were evaluated by a Wald test of the parameter estimate for the log-transformed continuous variables.

Association with known/suggested risk factors for breast cancer and breast cancer risk were examined. The variables considered were, education level (≤12, >12 years, missing), body mass index (BMI) (<25.0, 25.0–29.9, ≥30.0 kg/m2), tobacco smoking (never, ever, missing), alcohol drinking (no, yes, missing), family history of breast cancer (no, yes, missing), age at menarche (≤12, >12 years, missing), age at menopause (<45, 45–49, ≥50 years, missing), and number of live births (never, 1, 2–3, ≥4, missing). Information on education, smoking, alcohol drinking, age at menarche, and number of live births were collected at the time upon cohort entry. Information on menopause, menopausal age, BMI and family history of breast cancer were updated at the time of blood collection. Based on the results, a fully adjusted statistical model was built by inclusion of potential confounders for postmenopausal breast cancer risk, which were BMI, number of live births, and family history of breast cancer. Separate estimates were created for subgroups defined by age, race/ethnicity, BMI, and HRT use at blood draw. Tests for interaction were based on the Wald statistic for cross-product terms between the corresponding variable and the logarithmic transformed MMP level. Unconditional logistic regression with adjustment for the matching variables was employed for statistical analyses in which the matched sets were broken.

Unconditional polychotomous logistic regression models, using all controls as a reference, were created to evaluate the homogeneity of the association of breast cancer with plasma MMP levels by clinical parameters, such as SEER stage, tumor size, axillary node status, grade, and estrogen and/or progesterone receptor status. Cases with clinical parameters that were unreported, unknown, or borderline for receptor status were excluded from this analysis. The test of heterogeneity from polychotomous logistic regression models were calculated using a two-sided likelihood ratio test.

All tests were two-sided and P < 0.05 was considered statistically significant. Analyses were conducted using SAS version 9.2 statistical software (SAS Institute, Inc., Cary, North Carolina).

RESULTS

The distribution of breast cancer cases and controls by matching variables, including age, ethnicity, and the use of hormone replacement therapy is shown in Table 1. Cases were less likely than were controls to have had ≥ 4 births; whereas controls were less likely than were cases to be overweight and obese or to have a family history of breast cancer. There were no significant differences between cases and controls in other potential risk factors for postmenopausal breast cancer.

Table 1
Baseline characteristics of postmenopausal breast cancer cases and controls a

Among cases and controls, Pearson correlations of the log-transformed MMPs ranged from 0.10 (MMP-1 and MMP-2; MMP-1 and MMP-3) to 0.34 (MMP-2 and MMP-7) (P Values <0.01 for all combinations, data not shown). No significant differences in the geometric mean plasma levels of any of the MMPs were found between breast cancer cases and controls (Table 2). The ORs for breast cancer were not significant and close to one whether we examined individual MMPs as continuous (log-transformed) variables or as quartiles. MMPs were not associated with breast cancer risk when the analyses were restricted to subjects followed within 2, 3, 4 or 5 years (data not shown).

Table 2
Adjusted odds ratio (OR) and 95% confidence intervals (CI) for postmenopausal breast cancer by plasma MMP levels

The OR for the association of MMP-1 with breast cancer increased with higher BMI in stratified models (P Value for interaction = 0.03) (Table 3). A significant positive association of plasma MMP-1 and breast cancer risk was found among case-control pairs of HRT users, but not among pairs who were not HRT users (P Value for interaction = 0.04).

Table 3
Odds ratio (OR) and 95% confidence intervals (CI) for the association of postmenopausal breast cancer with plasma MMP levels by subgroup of participant characteristics a

The plasma concentrations of MMP-1 were higher among women with metastatic breast cancer than among controls (OR: 2.62, 95% CI: 1.06–6.51, P Value for heterogeneity = 0.01), but this was based on only 20 cases (Table 4). Higher MMP-2, MMP-3, and MMP-7 were related with increased risks for distant metastatic breast cancer, but the associations were not statistically significant. The expression level of MMP-2 was associated with the highest grade of breast cancer (P Value for heterogeneity = 0.03).

Table 4
Odds ratio (OR) and 95% confidence intervals (CI) for the association of postmenopausal breast cancer with plasma MMP levels by clinical characteristics of the cases

DISCUSSION

Results from this nested case-control study within the Multiethnic Cohort study do not support an association of pre-diagnostic plasma levels of MMPs-1, -2, -3, or -7 with postmenopausal breast cancer risk. Only a few other studies have examined the association between MMPs and postmenopausal breast cancer risk, and these have been small, hospital-based, and retrospective in nature [10, 11, 15]. Serum levels of MMP-2 and MMP-9 had been found to be significantly higher among 60 women with breast cancer than among 40 women with benign breast disease or 60 normal ‘healthy’ women [10]. These results were consistent with those from an earlier study in which plasma levels of MMP-2 and MMP-9 were significantly higher in 88 breast cancer cases compared to 150 women with benign breast diseases or 107 healthy controls [11]. In a third study, serum levels of MMP-9 and TIMP-1 were significantly higher among 60 breast cancer cases compared to 18 women with benign breast diseases or 15 healthy controls [15]. It is possible that the positive results found in previous studies resulted from over-selection of advanced cases: advanced cancer cases comprised 25% (Stage III–IV) of the total in one study [15] and 54% (T4) in a second study [10], which is a higher proportion compared to that in this current study (3%). Information regarding stage among cases was not available from a third study [11].

MMPs are postulated to promote malignant invasion through degradation of the basement membrane and the interstitial connective tissue of the ECM [19]. MMP-1, the first identified matrix metalloproteinase, has been evaluated in relation to a variety of diseases because of its broad substrate specificity and its importance to the turnover of the extracellular matrix [3]. MMP-1 expression in epithelial and stromal tissues was found to be higher in breast cancer tissue than in benign breast tissue [9]. Moreover, MMP-1 expression appears elevated in the surrounding stromal cells of women with various molecular subtypes of breast cancer [6]. MMP-2, a gelatinase capable of degrading collagen and elastin, has chemotactic properties that assist in the regulation of inflammatory mediators, such as IL-1β, that may be involved in breast carcinogenesis [3]. Moreover, MMP-2, but not MMP-9 which also belongs to gelatinase, targets fibroblast growth factor receptors, degrades collagen in vascular basal membranes, and modulates mitogenic and angiogenic activities of fibroblast growth factor [3, 19, 20]. MMP-3 or stromelysin-1, degrades ECM proteins, facilitates mammary tissue involution in mice after lactation, and may enhance tumor invasiveness through shedding of E-cadherin [3, 26]. MMP-7, a matrilysin lacking the C-terminal hemopexin-like domain, has a role in human microbial defense through regulatory mechanisms within the innate and mucosal immune pathways [27]. MMP-7 is one of only a few metalloproteinases shown to be produced by tumor cells [28]. Cellular proliferation is induced by MMP-7 through a variety of pathways, including regulation of insulin-like growth factor levels via cleavage of insulin-like growth factor binding proteins [29]. Alteration of cell signaling through ‘ectodomain shedding’ or the proteolytic degradation of transmembrane molecules may facilitate tumor growth and metastasis by several types of MMPs [30].

Recent interest has emerged in a potential role for MMPs as blood-based or tissue-based prognostic tools for breast cancer and other malignancies [7, 8, 12, 1416, 3135]. Some breast cancer phenotypes appear to acquire the ability to co-opt MMP vascular remodeling functions to facilitate angiogenesis and lung metastasis [36]. Consistent with these tissue-based studies, a few retrospective investigations of breast cancer have reported significant associations of higher serologic concentrations of MMP-1 and MMP-2 with advanced stage and the presence of lymph node metastasis, higher grade, and reduced relapse-free survival [10]. In our study, although number of distant metastatic cases were small and/or the association was not statistically significant, higher MMPs (1,2,3 and 7) were related with higher risks of distant metastatic breast cancer. Nevertheless, the lack of an association of any of the MMPs with the clinical variables for the cases should not be surprising considering the complex biological activity of the MMPs, their inhibitors, and their receptors. It is possible that specific forms of MMPs (pro-, mature or TIMP-1), not a complex form of MMPs, is associated with more aggressive types of breast cancer [12, 33].

Plasma MMP levels were modestly correlated in the controls, consistent with results from 1,678 participants in the Atherosclerosis Risk in Communities cohort (ARIC) [37]. Nonetheless, circulating levels of MMPs may be sensitive to a variety of host and environment characteristics, including genetics, BMI, oxidative stress, and tobacco smoke exposure [37, 38]. Correlates of plasma MMPs-1, -2, -3, and -7 among participants in the Atherosclerosis Risk in Communities included components of the metabolic syndrome, such as cholesterol, BMI, C-reactive protein, hypertension, and diabetes mellitus [37]. Little is known about the relevance of steroid hormones to MMPs, although in vitro studies suggest that estrogens and progestogens up-regulate MMP-2 expression in breast cancer cell lines [39]; and MMP-2 and MMP-3 are known to influence rodent mammary development [27, 40]. Modest interactions of BMI and HRT on the association of MMP-1 with breast cancer risk are likely chance observations, but may also suggest interactions with estrogen levels [39, 41, 42], providing conditional leads for further research.

The study is strengthened by its multiethnic composition and relatively large size; however, no heterogeneity in breast cancer risk associated with circulating MMP levels was identified by race or ethnic group. Our power was limited to examine association in subgroup analysis of clinical characteristics.

In conclusion, results from this large nested case-control study within the Multiethnic Cohort study do not support an association of pre-diagnostic plasma levels of MMPs with overall postmenopausal breast cancer risk. The search for circulating biomarkers for breast cancer has yielded few clinically relevant candidates. The critical role of the MMPs in tissue remodeling provided the basis for this analysis. As release of MMPs into the circulation from incipient breast tumors may be poor or undetectable, the substantial biological rationale for an association of serologic level of MMPs with postmenopausal breast cancer risk prompts caution in the interpretation of our null results. Considerable advancement in our knowledge of the biology of breast cancer will be required to understand the potential role of MMPs in aggressive phenotypes.

Acknowledgements

The authors thank Jennifer F. Lai for the performance of the biochemical assays in the Analytical Biochemistry Share Resource of the University of Hawaii Cancer Center. This research was supported by NCI grants R37-CA54281, P01-CA33619, and P30-CA71789 from the National Cancer Institute.

Footnotes

Ethical Standards

The study was approved by the institutional review boards of the University of Hawaii and the University of Southern California.

Conflict of Interest

The authors declare that they have no conflict of interests.

REFERENCES

1. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61(2):69–90. [PubMed]
2. Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC. American Society of Clinical Oncology 2007 Update of Recommendations for the Use of Tumor Markers in Breast Cancer. J Clin Oncol. 2007;25(33):5287–5312. [PubMed]
3. Klein T, Bischoff R. Physiology and pathophysiology of matrix metalloproteases. Amino Acids. 2011;41(2):271–290. [PMC free article] [PubMed]
4. Visse R, Nagase H. Matrix Metalloproteinases and Tissue Inhibitors of Metalloproteinases. Circ Res. 2003;92(8):827–839. [PubMed]
5. Murphy G, Nagase H. Progress in matrix metalloproteinase research. Mol Aspects Med. 2008;29(5):290–308. [PMC free article] [PubMed]
6. Bostrom P, Soderstrom M, Vahlberg T, Soderstrom KO, Roberts PJ, Carpen O, Hirsimaki P. MMP-1 expression has an independent prognostic value in breast cancer. BMC Cancer. 2011;11:348. [PMC free article] [PubMed]
7. Perentes JY, Kirkpatrick ND, Nagano S, Smith EY, Shaver CM, Sgroi D, Garkavtsev I, Munn LL, Jain RK, Boucher Y. Cancer cell-associated MT1-MMP promotes blood vessel invasion and distant metastasis in triple-negative mammary tumors. Cancer Res. 2011;71(13):4527–4538. [PubMed]
8. Ranogajec I, Jakic-Razumovic J, Puzovic V, Gabrilovac J. Prognostic value of matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9) and aminopeptidase N/CD13 in breast cancer patients. Med Oncol. 2011 [PubMed]
9. Steude JS, Maskarinec G, Erber E, Verheus M, Hernandez BY, Killeen J, Cline JM. Mammographic Density and Matrix Metalloproteinases in Breast Tissue. Cancer Microenviron. 2010;3:57–65. [PMC free article] [PubMed]
10. Patel S, Sumitra G, Koner BC, Saxena A. Role of serum matrix metalloproteinase-2 and -9 to predict breast cancer progression. Clin Biochem. 2011;44(10–11):869–872. [PubMed]
11. Somiari SB, Somiari RI, Heckman CM, Olsen CH, Jordan RM, Russell SJ, Shriver CD. Circulating MMP2 and MMP9 in breast cancer—Potential role in classification of patients into low risk, high risk, benign disease and breast cancer categories. Int J Cancer. 2006;119(6):1403–1411. [PubMed]
12. Lee JH, Choi JW, Kim YS. Serum TIMP-1 Predicts Survival Outcomes of Invasive Breast Carcinoma Patients: A Meta-analysis. Arch Med Res. 2011 [PubMed]
13. Lipton A, Leitzel K, Chaudri-Ross HA, Evans DB, Ali SM, Demers L, Hamer P, Brown-Shimer S, Pierce K, Gaur V, et al. Serum TIMP-1 and Response to the Aromatase Inhibitor Letrozole Versus Tamoxifen in Metastatic Breast Cancer. J Clin Oncol. 2008;26(16):2653–2658. [PubMed]
14. Talvensaari-Mattila A, Turpeenniemi-Hujanen T. High preoperative serum TIMP-1 is a prognostic indicator for survival in breast carcinoma. Breast Cancer Res Treat. 2005;89:29–34. [PubMed]
15. Wu Z-S, Wu Q, Yang J-H, Wang H-Q, Ding X-D, Yang F, Xu X-C. Prognostic significance of MMP-9 and TIMP-1 serum and tissue expression in breast cancer. Int J Cancer. 2008;122(9):2050–2056. [PubMed]
16. Würtz SØ, Møller S, Mouridsen H, Hertel PB, Friis E, Brünner N. Plasma and Serum Levels of Tissue Inhibitor of Metalloproteinases-1 Are Associated with Prognosis in Node-negative Breast Cancer. Molecular & Cellular Proteomics. 2008;7(2):424–430. [PubMed]
17. Song N, Sung H, Choi JY, Han S, Jeon S, Song M, Lee Y, Park CB, Park SK, Lee KM, et al. Preoperative serum levels of matrix metalloproteinase-2 (MMP-2) and survival of breast cancer among Korean women. Cancer Epidemiol Biomarkers Prev. 2012 [PubMed]
18. Sung H, Choi JY, Lee SA, Lee KM, Han S, Jeon S, Song M, Lee Y, Park SK, Yoo KY, et al. The association between the preoperative serum levels of lipocalin-2 and matrix metalloproteinase-9 (MMP-9) and prognosis of breast cancer. BMC Cancer. 2012;12(1):193. [PMC free article] [PubMed]
19. Duffy MJ, Maguire TM, Hill A, McDermott E, O'Higgins N. Metalloproteinases: role in breast carcinogenesis, invasion and metastasis. Breast Cancer Res. 2000;2(4):252–257. [PMC free article] [PubMed]
20. Levi E, Fridman R, Miao HQ, Ma YS, Yayon A, Vlodavsky I. Matrix metalloproteinase 2 releases active soluble ectodomain of fibroblast growth factor receptor 1. Proceedings of the National Academy of Sciences. 1996;93(14):7069–7074. [PubMed]
21. Kolonel LN, Henderson BE, Hankin JH, Nomura AM, Wilkens LR, Pike MC, Stram DO, Monroe KR, Earle ME, Nagamine FS. A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics. Am J Epidemiol. 2000;151(4):346–357. [PubMed]
22. Howlader N, Noone A, Krapcho M, Neyman N, Aminou R, Waldron W, Altekruse S, Kosary C, Ruhl J, Tatalovich Z, et al., editors. SEER Cancer Statistics Review, 1975–2008. Bethesda, MD: National Cancer Institute; 2011. based on November 2010 SEER data submission, posted to the SEER web site; http://seer.cancer.gov/csr/1975_2008/
23. International Classification of Diseases for Oncology Third Edition (ICD-O-3) Available at http://seer.cancer.gov/icd-o-3/.
24. Ognjanovic S, Yamamoto J, Saltzman B, Franke A, Ognjanovic M, Yokochi L, Vogt T, Decker R, Le Marchand L. Serum CRP and IL-6, genetic variants and risk of colorectal adenoma in a multiethnic population. Cancer Causes Control. 2010;21(7):1131–1138. [PubMed]
25. Maskarinec G, Woolcott C, Steude JS, Franke AA, Cooney RV. The relation of leptin and adiponectin with breast density among premenopausal women. Eur J Cancer Prev. 2010;19(1):55–60. [PMC free article] [PubMed]
26. Mercapide J, Lopez De Cicco R, Castresana JS, Klein-Szanto AJP. Stromelysin-1/matrix metalloproteinase-3 (MMP-3) expression accounts for invasive properties of human astrocytoma cell lines. Int J Cancer. 2003;106(5):676–682. [PubMed]
27. Page-McCaw A, Ewald AJ, Werb Z. Matrix metalloproteinases and the regulation of tissue remodelling. Nat Rev Mol Cell Biol. 2007;8(3):221–233. [PMC free article] [PubMed]
28. Overall CM, Kleifeld O. Tumour microenvironment - opinion: validating matrix metalloproteinases as drug targets and anti-targets for cancer therapy. Nat Rev Cancer. 2006;6(3):227–239. [PubMed]
29. Nakamura M, Miyamoto S, Maeda H, Ishii G, Hasebe T, Chiba T, Asaka M, Ochiai A. Matrix metalloproteinase-7 degrades all insulin-like growth factor binding proteins and facilitates insulin-like growth factor bioavailability. Biochem Biophys Res Commun. 2005;333(3):1011–1016. [PubMed]
30. Ii M, Yamamoto H, Adachi Y, Maruyama Y, Shinomura Y. Role of Matrix Metalloproteinase-7 (Matrilysin) in Human Cancer Invasion, Apoptosis, Growth, and Angiogenesis. Exp Biol Med. 2006;231(1):20–27. [PubMed]
31. Lynch CC. Matrix metalloproteinases as master regulators of the vicious cycle of bone metastasis. Bone. 2011;48(1):44–53. [PubMed]
32. Maquoi E, Assent D, Detilleux J, Pequeux C, Foidart JM, Noel A. MT1-MMP protects breast carcinoma cells against type I collagen-induced apoptosis. Oncogene. 2011 [PubMed]
33. Muller V, Riethdorf S, Rack B, Janni W, Fasching PA, Solomayer E, Aktas B, Kasimir-Bauer S, Zeitz J, Pantel K, et al. Prospective evaluation of serum tissue inhibitor of metalloproteinase 1 and carbonic anhydrase IX in correlation to circulating tumor cells in patients with metastatic breast cancer. Breast Cancer Res. 2011;13(4):R71. [PMC free article] [PubMed]
34. Mannello F. What does matrix metalloproteinase-1 expression in patients with breast cancer really tell us? BMC Med. 2011;9:95. [PMC free article] [PubMed]
35. Gialeli C, Theocharis AD, Karamanos NK. Roles of matrix metalloproteinases in cancer progression and their pharmacological targeting. FEBS Journal. 2011;278(1):16–27. [PubMed]
36. Gupta GP, Nguyen DX, Chiang AC, Bos PD, Kim JY, Nadal C, Gomis RR, Manova-Todorova K, Massague J. Mediators of vascular remodelling co-opted for sequential steps in lung metastasis. Nature. 2007;446(7137):765–770. [PubMed]
37. Gaubatz JW, Ballantyne CM, Wasserman BA, He M, Chambless LE, Boerwinkle E, Hoogeveen RC. Association of Circulating Matrix Metalloproteinases With Carotid Artery Characteristics. Arterioscler Thromb Vasc Biol. 2010;30(5):1034–1042. [PMC free article] [PubMed]
38. Zhou P, Du LF, Lv GQ, Yu XM, Gu YL, Li JP, Zhang C. Current evidence on the relationship between four polymorphisms in the matrix metalloproteinases (MMP) gene and breast cancer risk: a meta-analysis. Breast Cancer Res Treat. 2011;127(3):813–818. [PubMed]
39. Abdallah MA, Abdullah HI, Kang S, Taylor DD, Nakajima ST, Gercel-Taylor C. Effects of the components of hormone therapy on matrix metalloproteinases in breast-cancer cells: an in vitro study. Fertil Steril. 2007;87(4):978–981. [PubMed]
40. Wiseman BS, Sternlicht MD, Lund LR, Alexander CM, Mott J, Bissell MJ, Soloway P, Itohara S, Werb Z. Site-specific inductive and inhibitory activities of MMP-2 and MMP-3 orchestrate mammary gland branching morphogenesis. J Cell Biol. 2003;162(6):1123–1133. [PMC free article] [PubMed]
41. Lekontseva O, Jiang Y, Davidge ST. Estrogen replacement increases matrix metalloproteinase contribution to vasoconstriction in a rat model of menopause. J Hypertens. 2009;27(8):1602–1608. [PubMed]
42. Lewandowski KC, Komorowski J, Mikhalidis DP, Bienkiewicz M, Tan BK, O'Callaghan CJ, Lewinski A, Prelevic G, Randeva HS. Effects of hormone replacement therapy type and route of administration on plasma matrix metalloproteinases and their tissue inhibitors in postmenopausal women. J Clin Endocrinol Metab. 2006;91(8):3123–3130. [PubMed]