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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2010 April 1.
Published in final edited form as:
PMCID: PMC2701308
NIHMSID: NIHMS100865

No Association between MMP-1 or MMP-3 Polymorphisms and Breast Cancer Susceptibility: A report from the Shanghai Breast Cancer Study

Introduction

Matrix metalloproteinase (MMP)-1 (interstitial collagenase) and MMP-3 (stromelysin) are structurally related multifunctional enzymes that are involved in physiological and pathological tissue remodeling 1;2. Known to contribute to breast cancer invasion and metastasis 35, roles in breast tumor initiation and progression have also been suggested 610. Expression of these MMPs is often coordinately regulated; the two genes are adjacent on chromosome 11q22.3 and have several similar promoter elements 11;12. Functional polymorphisms resulting from the insertion or deletion of a single nucleotide have been identified in both gene promoters 1315; MMP-1 -1607 1G/2G (rs1799750) and MMP-3 -1612 (also known as -1171) 5A/6A (rs3025058) are in linkage disequilibrium (LD) 16;17. Previous studies have evaluated these single nucleotide polymorphisms (SNPs) in relation to breast cancer risk with both positive 18;19 and null findings 2022, however, other genetic variation in these genes may also contribute to expression differences 11;12;23. This study was therefore undertaken to comprehensively assess individual genetic variation across MMP-1 and MMP-3, and evaluate associations with breast cancer risk among participants of the Shanghai Breast Cancer Study (SBCS).

Methods

Study subjects were participants of the SBCS, a large, two-phase, population-based, case-control study of women in urban Shanghai 2426. Briefly, 1,459 (91.1%) cases and 1,556 (90.3%) controls from Phase 1, and 1,989 cases (83.7%) and 1,989 controls (70.4%) from Phase 2 completed in-person interviews. Blood or buccal cell samples were donated by 1,193 cases (81.8%) and 1,310 controls (84.2%) from Phase 1 and 1,932 (97.1%) cases and 1,857 (93.4%) controls from Phase 2. Approval was granted from relevant review boards in both China and the United States; all included subjects gave informed consent.

Haplotype tagging SNPs (htSNPs) were selected from Han Chinese data from the HapMap Project 27 using the Tagger program 28 to capture SNPs with a minimum minor allele frequency (MAF) of 0.05 in either MMP-1 or MMP-3 (± 5kb) with an r2 of 0.90 or greater. Seventeen MMP-1 and seven MMP-3 SNPs were selected; fourteen and six SNPs, respectively, were successfully designed and genotyped in 2006 for 1,062 cases and 1,069 controls from Phase 1, using a Targeted Genotyping System (Affymetrix, Santa Clara, CA) 26.

Two insertion/deletion polymorphisms reported to be functional 1315 were chosen for genotyping using the Sequenom MassARRAY System (Sequenom, Inc., San Diego, CA) for 1,495 cases and 1,437 controls from Phase 2. Blinded duplicate samples and negative controls were included; concordance rates between duplicates were ≥ 99.4%.

To increase the density of genetic markers in this study, data from our recently completed Affymetrix Genome-Wide Human SNP Array 6.0 (Affymetrix) was included for an additional 11 MMP-1 (± 10kb) and 9 MMP-3 (± 10kb) SNPs for 2,994 participants, including 1,082 cases and 1,085 controls from Phase 1, and 416 cases and 411 controls from Phase 2.

Hardy-Weinberg equilibrium (HWE) was tested by comparing the observed and expected genotype frequencies of the controls (χ2-test). Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were determined by logistic regression analyses using additive models that included adjustment for age, education, and study phase if appropriate. Linkage disequilibrium was assessed by Haploview 29. All statistical tests were two-tailed, and p-values were considered to be statistically significant when ≤ 0.05.

Results

A total of 6,023 women were included in the current study: 2,279 Phase 1 participants and 3,744 Phase 2 participants. Women in both study phases were generally comparable (data not shown). As expected, breast cancer cases were found to differ from controls in regards to known breast cancer risk factors; cases were more likely to have earlier age at menarche, older age at first live birth, a history of breast fibroadenomas, a history of breast cancer among a first degree relative, a higher BMI and/or WHR, and less likely to participate in regular physical activity than controls (data not shown).

SNPs included in the current study are listed in Table 1; their order corresponds to the open reading frames of the genes on the negative strand of chromosome 11. Based on the genotype distribution among controls, three SNPs were found to have MAFs of less than 1% (rs3025079, rs12295590, and rs11600510), and three SNPs were found to deviate from HWE (rs2071231, rs7945189, and rs7127735). Associations with breast cancer were calculated among 1,062 cases and 1,069 controls from Phase 1 for 20 htSNPs, among 1,495 cases and 1,437 controls from Phase 2 for 2 functional SNPs, and among 1,082 cases and 1,085 controls from Phase 1 and 416 cases and 411 controls from Phase 2 for the additional 17 SNPs. None of these 39 SNPs were found to be significantly associated with breast cancer risk in additive models that included adjustment for age, education, and study phase when appropriate. Further, no significant associations were identified under dominant or recessive models (data not shown). The linkage disequilibrium (LD) structure of these 39 polymorphic loci is shown in Figure 1.

Figure 1
LD Structure of MMP-1 and MMP-3 Polymorphisms
Table 1
MMP-1 and MMP-3 SNPs and Breast Cancer Risk, The Shanghai Breast Cancer Study

Discussion

Known to be involved in cancer invasion and metastasis, MMP-1 and MMP-3 have also been implicated in breast cancer development and progression. MMP-3 expression was found to promote malignant transformation in vitro and the development of spontaneous malignant lesions in mammary glands of mice 68. MMP-1 expression was necessary for breast tumor growth in nude mice 9, and was determined to be positively regulated by Her-2/neu induced Ets-1 in breast cancer cells 10. In humans, both genes were found to be expressed in breast cancer tissues 30. Promoter polymorphisms that influence gene expression have been identified for both MMP-1 and MMP-3 13;15;25. Previous studies on MMP-1-1607 1G/2G (rs1799750) and MMP-3 -1612 (aka -1171) 5A/6A (rs3025058) and breast cancer risk have had mixed results 1822. In the current study, neither the two previously reported functional SNPs, nor other genetic variation in or around MMP-1 or MMP-3, were found to be associated with breast cancer risk. Given the size of our study population, this analysis had greater than 77% power to detect an OR of 1.3 for a SNP with a MAF of 10%, greater than 85% power to detect an OR of 1.25 for a SNP with a MAF of 20%, and greater than 79% power to detect an OR of 1.2 for a SNP with a MAF of 30%. In summary, a total of 42 MMP-1 and MMP-3 polymorphisms were evaluated among a total of 3,016 cases and 3,007 controls in the Shanghai Breast Cancer Study; no associations with breast cancer risk were observed.

Acknowledgments

This research was supported by USPHS grants R01CA64277, R01CA90899 and R01CA124558. Genotyping assays, using Affymetrix arrays, were conducted at the Vanderbilt Microarray Shared Resource which is supported in part by the Vanderbilt Ingram Cancer Center (P30CA68485).

This research was supported by USPHS grants R01CA64277, R01CA90899 and R01CA124558. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health. The authors wish to thank the participants and research staff of the Shanghai Breast Cancer Study for their contributions and commitment to this project, and Brandy Venuti for assistance with the preparation of this manuscript. Genotyping assays using Affymetrix arrays were conducted at the Vanderbilt Microarray Shared Resource which is supported in part by the Vanderbilt Ingram Cancer Center (P30CA68485). Sequenom assays were performed by Proactive Genomics (Winstom-Salem, North Carolina).

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