Matrix metalloproteinase (MMP)-1 (interstitial collagenase) and MMP-3 (stromelysin) are structurally related multifunctional enzymes that are involved in physiologic and pathologic tissue remodeling (1, 2). Known to contribute to breast cancer invasion and metastasis (3-5), roles in breast tumor initiation and progression have also been suggested (6-10). 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 (13-15); MMP-1-1607 1G/2G (rs1799750) and MMP-3-1612 (also known as-1171) 5A/6A (rs35068180 and rs3025058) are in linkage disequilibrium (16, 17). Previous studies have evaluated these single nucleotide polymorphisms (SNP) in relation to breast cancer risk with both positive (18, 19) and null findings (20-22); 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.

Study subjects were participants of the Shanghai Breast Cancer Study, a large, two-phase, population-based, case-control study of women in urban Shanghai (24-26). 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 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 (±5 kb) with an r2 of 0.90 or greater. Seventeen MMP-1 and 7 MMP-3 SNPs were selected; 14 and 6 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; ref. 26).

Two insertion/deletion polymorphisms reported to be functional (13-15) were chosen for genotyping using the Sequenom MassARRAY System (Sequenom, Inc.) 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 (±10 kb) and 9 MMP-3 (±10 kb) 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 was tested by comparing the observed and expected genotype frequencies of the controls (χ2 test). Odds ratios (OR) and corresponding 95% confidence intervals 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.

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 with regard 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 body mass index and/or waist-to-hip ratio, 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, 3 SNPs were found to have MAFs of <1% (rs3025079, rs12295590, and rs11600510), and 3 SNPs were found to deviate from Hardy-Weinberg equilibrium (rs2071231, rs7945189, and rs7127735). Associations with breast cancer were calculated among 1,062 cases and 1,069 controls from phase 1 for 20 haplotype tagging SNPs, 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. Furthermore, no significant associations were identified under dominant or recessive models (data not shown). The linkage disequilibrium structure of these 39 polymorphic loci is shown in Fig. 1.

Table 1.

MMP-1 and MMP-3 SNPs and breast cancer risk, the Shanghai Breast Cancer Study

OR (95% CI)‡
Gene SNPAllelesRegionGenotyping*MAF†AB‡BB‡P value‡
MMP-3        
    rs615098 C/A Promoter Affy 6.0 14.5% 0.9 (0.7-1.1) 1.2 (0.7-2.1) 0.449 
    rs613804 C/T Promoter Affy 6.0 11.4% 0.9 (0.7-1.1) 1.3 (0.7-2.4) 0.488 
    rs17361668 T/A Promoter Affy 6.0 2.8% 1.0 (0.7-1.4) NA NA 
    rs610950 T/C Promoter Affy 6.0 10.5% 0.9 (0.7-1.1) 1.6 (0.8-3.2) 0.811 
    rs645419 G/A Promoter Targeted 32.3% 1.0 (0.9-1.2) 1.1 (0.9-1.5) 0.441 
    rs35068180 6A/5A Promoter Sequenom 15.4% 1.1 (1.0-1.4) 0.9 (0.6-1.4) 0.292 
    rs632478 C/A Promoter Targeted 32.4% 1.0 (0.8-1.2) 1.1 (0.8-1.5) 0.510 
    rs522616 A/G Promoter Targeted 38.7% 1.0 (0.8-1.2) 1.0 (0.8-1.3) 0.909 
    rs679620 G/A Exon 2 Targeted 32.5% 1.0 (0.8-1.2) 1.2 (0.9-1.6) 0.492 
    rs650108 A/G Intron 8 Targeted 39.5% 1.0 (0.9-1.3) 1.0 (0.8-1.3) 0.757 
    rs655403 C/T Intron 8 Targeted 6.9% 0.9 (0.7-1.2) 1.6 (0.4-5.6) 0.587 
    rs639752 T/G Intron 9 Affy 6.0 31.5% 1.1 (0.9-1.3) 1.1 (0.9-1.5) 0.311 
    rs2155013 C/T 3′ FR§ Affy 6.0 31.6% 1.1 (0.9-1.2) 1.1 (0.9-1.5) 0.315 
    rs473238 C/T 3′ FR§ Affy 6.0 6.9% 0.9 (0.7-1.1) 1.5 (0.4-5.4) 0.414 
    rs502588 T/A 3′ FR§ Affy 6.0 38.5% 1.0 (0.9-1.2) 1.0 (0.8-1.3) 0.831 
    rs7926920 G/A 3′ FR§ Affy 6.0 32.1% 1.0 (0.9-1.2) 1.1 (0.9-1.4) 0.423 
MMP-1        
    rs484915 A/T promoter Targeted 33.6% 0.9 (0.8-1.1) 1.1 (0.9-1.5) 0.757 
    rs1155764 T/G Promoter Targeted 20.1% 1.0 (0.9-1.3) 0.8 (0.5-1.3) 0.895 
    rs509332 A/G Promoter Targeted 12.8% 0.9 (0.7-1.1) 1.4 (0.8-2.7) 0.545 
    rs470206 G/A Promoter Targeted 12.7% 0.9 (0.7-1.1) 1.3 (0.7-2.5) 0.458 
    rs1799750 2G/1G Promoter Sequenom 34.9% 1.1 (0.9-1.3) 1.0 (0.8-1.3) 0.446 
    rs2075847 T/C Promoter Targeted 24.2% 1.0 (0.9-1.2) 1.1 (0.7-1.5) 0.713 
    rs498186 A/C Promoter Targeted 45.9% 1.0 (0.8-1.2) 1.0 (0.8-1.2) 0.735 
    rs475007 T/A Promoter Targeted 35.7% 1.1 (1.0-1.4) 0.9 (0.7-1.2) 0.773 
    rs996999 T/C Intron 4 Targeted 49.2% 1.0 (0.8-1.2) 1.0 (0.8-1.3) 0.792 
    rs470558 G/A Exon 5 Targeted 11.4% 1.1 (0.9-1.3) 1.0 (0.5-2.0) 0.579 
    rs2071232 C/T Intron 6 Affy 6.0 49.6% 1.0 (0.9-1.3) 1.0 (0.8-1.2) 0.689 
    rs7125062 C/T Intron 6 Targeted 29.7% 1.0 (0.8-1.1) 1.0 (0.7-1.3) 0.736 
    rs1938901 T/C Intron 8 Targeted 43.9% 0.9 (0.8-1.1) 1.0 (0.8-1.2) 0.634 
    rs470747 T/C Intron 8 Affy 6.0 8.8% 0.9 (0.8-1.1) 0.9 (0.3-2.1) 0.774 
    rs2071231 T/G Intron 9 Targeted 21.1% 1.1 (0.9-1.3) 0.7 (0.5-1.1) 0.982 
    rs470215 A/G 3′ UTR Affy 6.0 8.8% 0.9 (0.8-1.1) 0.9 (0.4-2.1) 0.376 
    rs5854 C/T 3′ UTR Affy 6.0 8.3% 1.0 (0.8-1.2) 0.7 (0.2-2.1) 0.675 
    rs7945189 C/T 3′ FR§ Targeted 7.1% 1.1 (0.9-1.5) 0.7 (0.3-1.8) 0.638 
    rs470504 C/T 3′ FR§ Targeted 12.8% 1.1 (0.9-1.3) 1.0 (0.6-2.0) 0.519 
    rs1939008 A/G 3′ FR§ Affy 6.0 43.1% 1.0 (0.8-1.1) 1.0 (0.8-1.2) 0.769 
    rs11225422 A/G 3′ FR§ Affy 6.0 20.3% 1.0 (0.9-1.2) 1.1 (0.8-1.5) 0.631 
    rs470226 G/A 3′ FR§ Affy 6.0 11.9% 1.0 (0.8-1.2) 0.7 (0.4-1.3) 0.519 
    rs7127735 A/G 3′ FR§ Affy 6.0 21.4% 1.1 (0.9-1.3) 1.1 (0.8-1.4) 0.414 
OR (95% CI)‡
Gene SNPAllelesRegionGenotyping*MAF†AB‡BB‡P value‡
MMP-3        
    rs615098 C/A Promoter Affy 6.0 14.5% 0.9 (0.7-1.1) 1.2 (0.7-2.1) 0.449 
    rs613804 C/T Promoter Affy 6.0 11.4% 0.9 (0.7-1.1) 1.3 (0.7-2.4) 0.488 
    rs17361668 T/A Promoter Affy 6.0 2.8% 1.0 (0.7-1.4) NA NA 
    rs610950 T/C Promoter Affy 6.0 10.5% 0.9 (0.7-1.1) 1.6 (0.8-3.2) 0.811 
    rs645419 G/A Promoter Targeted 32.3% 1.0 (0.9-1.2) 1.1 (0.9-1.5) 0.441 
    rs35068180 6A/5A Promoter Sequenom 15.4% 1.1 (1.0-1.4) 0.9 (0.6-1.4) 0.292 
    rs632478 C/A Promoter Targeted 32.4% 1.0 (0.8-1.2) 1.1 (0.8-1.5) 0.510 
    rs522616 A/G Promoter Targeted 38.7% 1.0 (0.8-1.2) 1.0 (0.8-1.3) 0.909 
    rs679620 G/A Exon 2 Targeted 32.5% 1.0 (0.8-1.2) 1.2 (0.9-1.6) 0.492 
    rs650108 A/G Intron 8 Targeted 39.5% 1.0 (0.9-1.3) 1.0 (0.8-1.3) 0.757 
    rs655403 C/T Intron 8 Targeted 6.9% 0.9 (0.7-1.2) 1.6 (0.4-5.6) 0.587 
    rs639752 T/G Intron 9 Affy 6.0 31.5% 1.1 (0.9-1.3) 1.1 (0.9-1.5) 0.311 
    rs2155013 C/T 3′ FR§ Affy 6.0 31.6% 1.1 (0.9-1.2) 1.1 (0.9-1.5) 0.315 
    rs473238 C/T 3′ FR§ Affy 6.0 6.9% 0.9 (0.7-1.1) 1.5 (0.4-5.4) 0.414 
    rs502588 T/A 3′ FR§ Affy 6.0 38.5% 1.0 (0.9-1.2) 1.0 (0.8-1.3) 0.831 
    rs7926920 G/A 3′ FR§ Affy 6.0 32.1% 1.0 (0.9-1.2) 1.1 (0.9-1.4) 0.423 
MMP-1        
    rs484915 A/T promoter Targeted 33.6% 0.9 (0.8-1.1) 1.1 (0.9-1.5) 0.757 
    rs1155764 T/G Promoter Targeted 20.1% 1.0 (0.9-1.3) 0.8 (0.5-1.3) 0.895 
    rs509332 A/G Promoter Targeted 12.8% 0.9 (0.7-1.1) 1.4 (0.8-2.7) 0.545 
    rs470206 G/A Promoter Targeted 12.7% 0.9 (0.7-1.1) 1.3 (0.7-2.5) 0.458 
    rs1799750 2G/1G Promoter Sequenom 34.9% 1.1 (0.9-1.3) 1.0 (0.8-1.3) 0.446 
    rs2075847 T/C Promoter Targeted 24.2% 1.0 (0.9-1.2) 1.1 (0.7-1.5) 0.713 
    rs498186 A/C Promoter Targeted 45.9% 1.0 (0.8-1.2) 1.0 (0.8-1.2) 0.735 
    rs475007 T/A Promoter Targeted 35.7% 1.1 (1.0-1.4) 0.9 (0.7-1.2) 0.773 
    rs996999 T/C Intron 4 Targeted 49.2% 1.0 (0.8-1.2) 1.0 (0.8-1.3) 0.792 
    rs470558 G/A Exon 5 Targeted 11.4% 1.1 (0.9-1.3) 1.0 (0.5-2.0) 0.579 
    rs2071232 C/T Intron 6 Affy 6.0 49.6% 1.0 (0.9-1.3) 1.0 (0.8-1.2) 0.689 
    rs7125062 C/T Intron 6 Targeted 29.7% 1.0 (0.8-1.1) 1.0 (0.7-1.3) 0.736 
    rs1938901 T/C Intron 8 Targeted 43.9% 0.9 (0.8-1.1) 1.0 (0.8-1.2) 0.634 
    rs470747 T/C Intron 8 Affy 6.0 8.8% 0.9 (0.8-1.1) 0.9 (0.3-2.1) 0.774 
    rs2071231 T/G Intron 9 Targeted 21.1% 1.1 (0.9-1.3) 0.7 (0.5-1.1) 0.982 
    rs470215 A/G 3′ UTR Affy 6.0 8.8% 0.9 (0.8-1.1) 0.9 (0.4-2.1) 0.376 
    rs5854 C/T 3′ UTR Affy 6.0 8.3% 1.0 (0.8-1.2) 0.7 (0.2-2.1) 0.675 
    rs7945189 C/T 3′ FR§ Targeted 7.1% 1.1 (0.9-1.5) 0.7 (0.3-1.8) 0.638 
    rs470504 C/T 3′ FR§ Targeted 12.8% 1.1 (0.9-1.3) 1.0 (0.6-2.0) 0.519 
    rs1939008 A/G 3′ FR§ Affy 6.0 43.1% 1.0 (0.8-1.1) 1.0 (0.8-1.2) 0.769 
    rs11225422 A/G 3′ FR§ Affy 6.0 20.3% 1.0 (0.9-1.2) 1.1 (0.8-1.5) 0.631 
    rs470226 G/A 3′ FR§ Affy 6.0 11.9% 1.0 (0.8-1.2) 0.7 (0.4-1.3) 0.519 
    rs7127735 A/G 3′ FR§ Affy 6.0 21.4% 1.1 (0.9-1.3) 1.1 (0.8-1.4) 0.414 

Abbreviation: UTR, untranslated region.

*

Genotyping: Affymetrix Targeted Genotyping among 1,062 cases and 1,069 controls from phase 1 (Targeted); Sequenom Targeted Genotyping among 1,495 cases and 1,437 controls from phase 2 (Sequenom); or Affymetrix 6.0 genotyping among 1,082 cases and 1,085 controls from phase 1, and 416 cases and 411 controls from phase 2 (Affy 6.0).

†

MAF among genotyped controls.

‡

Odds Ratio (OR) and corresponding 95% Confidence Interval (CI) for the risk of breast cancer, adjusted for age, education, and study phase (if appropriate); AA major allele homozygotes (reference group); AB heterozygotes; BB minor allele homozygotes; P value for trend from additive model.

§

3′ FR, downstream flanking region, 3′ of the gene.

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Figure 1.
Figure 1. Linkage disequilibrium structure of MMP-1 and MMP-3 SNPs among 3,007 Chinese women. Value shown is r2.
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Linkage disequilibrium structure of MMP-1 and MMP-3 SNPs among 3,007 Chinese women. Value shown is r2.

Figure 1.
Figure 1. Linkage disequilibrium structure of MMP-1 and MMP-3 SNPs among 3,007 Chinese women. Value shown is r2.
View largeDownload slide

Linkage disequilibrium structure of MMP-1 and MMP-3 SNPs among 3,007 Chinese women. Value shown is r2.

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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 (6-8). 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 (rs35068180 and rs3025058) and breast cancer risk have had mixed results (18-22). 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 >77% power to detect an OR of 1.3 for a SNP with a MAF of 10%, >85% power to detect an OR of 1.25 for a SNP with a MAF of 20%, and >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.

No potential conflicts of interest were disclosed.

Grant support: United States Public Health Service 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 NIH.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We 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. DNA sample preparation and genotyping assays were conducted in part at the Vanderbilt Survey and Biospecimen and Microarray Shared Resources which are supported in part by the Vanderbilt Ingram Cancer Center (P30CA68485). Sequenom assays were done by Proactive Genomics.

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