Purpose: Polymorphisms within the promoter region of several matrix metalloproteinase (MMP) genes have been linked to alterations in the level of transcription. We hypothesized that an individual's MMP genotype and haplotype will influence breast tumor progression and help predict prognosis.

Experimental Design: This study has evaluated the association between single-nucleotide polymorphisms (SNP) in the promoter regions of MMP-1, MMP-3, MMP-7, MMP-9, MMP-12, and MMP-13 and metastatic spread of breast cancer in 128 lymph node–negative and 93 lymph node–positive patients. The study cohort was of mixed ethnicity, with Caucasian patients comprising 65%. Associations between genotype and lymph node status were estimated by logistic regression and with overall survival using the method of Kaplan-Meier and log-rank test. Associations between haplotype and lymph node status were also investigated.

Results: The data show a significant and independent association of the C/T genotype for MMP-9 [mixed ethnicities odds ratio 3.6, 95% confidence interval (95% CI) 1.2-11.1; Caucasian odds ratio 9.1, 95% CI 1.7-48.4] and the 2G/2G genotype for MMP-1 (mixed ethnicities odds ratio 3.9, 95% CI 1.7-9.4; Caucasian odds ratio 2.6, 95% CI 1.0-6.9) with lymph node–positive disease. MMP-1 2G/2G was associated with reduced survival (hazard ratio 3.1, 95% CI 1.1-8.7), although this is dependent on lymph node status. Two haplotypes, driven by the MMP-1 2G allele, were significantly associated with lymph node–positive disease and survival.

Conclusions: These results suggest that MMP single-nucleotide polymorphisms influence breast cancer behavior and that the MMP-1 2G/2G genotype increases the risk of lymph node metastasis and predicts poor prognosis.

Breast cancer is the most common female cancer in the Western world and constitutes ∼30% of all cancers diagnosed in women. Although breast cancer–related deaths have decreased by >20% since 1995, predicting outcome still is a major challenge. Breast cancer is a very heterogeneous disease (1), and there is a continuing need to predict those patients who are likely to have more aggressive disease and to tailor treatment accordingly. As a result, intensive research is currently under way to identify the genetic determinants that may prove to be important for both classification and prognosis prediction.

Matrix metalloproteinases (MMP) are a multifunctional family, comprising >28 endoproteinases, that are involved in the degradation of extracellular matrix and basement membrane barriers (24). Members of the family have been implicated in the promotion of tumor growth, angiogenesis, invasion, and metastasis (57). Elevated levels of MMPs have been described in many tumors wherein MMPs are associated with tumor spread and poor patient prognosis (3, 810). MMP gene expression is regulated primarily at the transcriptional level and in many solid tumors, particularly breast cancer; the major source of MMPs is the host microenvironment in response to tumor cell–derived signals (11). Thus, factors which influence the host response may play a role in determining tumor behavior in an individual.

Over recent years, single-nucleotide polymorphisms (SNP), constituting insertions (e.g., MMP-1, G at position −1,607 bp), deletions (e.g., MMP-3, A at position −1,171 bp), or substitutions (e.g., MMP-7, A to G substitution at −181 bp; MMP-9, C to T substitution at −1,562 bp; MMP-12, A to G substitution at −82 bp; MMP-13, A to G substitution at −77 bp) of single bases upstream of the transcriptional start site of MMP genes have been described and shown to affect transcriptional activity, leading to alterations in gene expression (12). Thus, the MMP-1 2G allele creates a binding site for the Ets transcription factor, enhancing transcriptional activity (13), whereas the MMP-3 6A allele exhibits weaker transcriptional activity than the 5A allele, possibly due to enhanced binding of a transcriptional repressor (14). The MMP-7 G allele, the MMP-9 T allele, the MMP-12 A allele, and the MMP-13 G allele all have been shown and predicted to generate higher levels of gene transcription and hence enzyme activity (1518). These polymorphisms have been variably linked to disease susceptibility (19), tumor invasive capacity (20), and patient prognosis (21) in other cancer types.

Given the role of MMPs in breast cancer progression and the association of high levels of MMPs with poor patient prognosis, we hypothesized that individuals carrying high-expressing MMP genotypes may be more susceptible to tumor spread compared with those patients lacking these alleles. This study therefore aimed to investigate the relationship between functional SNPs in MMP-1, MMP-3, MMP-7, MMP-9, MMP-12, and MMP-13 and tumor behavior in a cohort of patients with breast cancer. We further hypothesized that the joint effects of these SNPs may exert a greater risk than the individual effect of each SNP; therefore, we analyzed the relationship between gene haplotypes and tumor behavior.

Patient samples and cohort selection. A total of 221 patients with breast cancer presenting between 1990 and 2006 to St. Bartholomew's Hospital, London (95% from 1999 onwards) were included in this study, following ethics approval from the North East London LREC. From each year of recruitment, all lymph node–positive cases and approximately equal numbers of grade-matched lymph node–negative cases were selected. The cases before 1999 had presented with recurrence during the main study period of 1999 to 2006, but the original diagnosis was between 1990 and 1998. The original histology was reviewed, and details regarding tumor grade, type, and lymph node status were recorded. All patients underwent segmental or total mastectomy plus an axillary node procedure. This was level 1 clearance before 2001, and sentinel node biopsy plus sample (minimum of four nodes) from 2001. All lymph nodes were assessed on single H&E alone, and micrometastasis was excluded from the study. Data were available for estrogen receptor and progesterone receptor status. Patient ethnicity details were retrieved from the clinical records, and for the purpose of this study, individuals were recorded as Caucasian or other. Patient outcome data were retrieved from the clinical records, with a median follow-up of 60 months (range, 2-180 months). MMP SNP genotype and haplotype were related to disease-free survival and overall survival. Only breast cancer–specific deaths were considered, with data from patients who died from other causes being censored.

DNA preparation. Nontumor DNA was isolated from formalin-fixed paraffin-embedded noninvolved lymph node. Eight serial sections (5 μm) were taken from selected lymph node blocks, placed into a 1.5-mL tube, and deparaffinized using xylene. DNA was extracted using the QIAamp DNA minikit (Qiagen) following manufacturer's instructions.

MMP PCR. PCR was carried out in a 25 μL volume containing 25 ng of genomic DNA, 1 μL of each primer (2 mmol/L stock), 2 μL of 2.5 mmol/L deoxynucleotide triphosphate mix (Invitrogen), 2.5 μL of 10× PCR buffer, MgCl2 (1.25 μL of a 50 mmol/L stock for MMP-7, MMP-12, and MMP-13 or 2.5 μL of a 50 mmol/L stock for MMP-1 and MMP-3), 0.2 μL of Platinum Taq DNA polymerase (5 units/μL; Invitrogen), and sterile deionized H2O up to a final volume of 25 μL.

PCR conditions were as follows: initial denaturation for 2 min at 95°C; 40 cycles of denaturing for 30 s at 94°C, annealing for 30 s at a primer-specific temperature [MMP-1, forward 5′ TCGTGAGAATGTCTTCCCATT 3′ (HEX tagged)/reverse 5′ TTATCACTTCAGCACCTTATGGT 3′; MMP-7, forward 5′ CTGAATGATACCTATGAGAGCAGT 3′/reverse 5′ GCAGGAAGCACACAATGAATT 3′; the underlined base refers to an engineered base change in the primer, which substitutes a T for an A, thus generating an EcoRI restriction site; MMP-12, forward 5′ TGCTTGAGTGATGGACTAGAT 3′/reverse 5′ TTCTAGCCTAAGTTCCTGAACTGT 3′; MMP-13, forward 5′ TCGCCACGTAAGCATGTTTACCT 3′/reverse 5′ GACAAATCATCTTCATCACC 3′ all at 55°C; MMP-3, forward 5′ GGAATTCACATCACTGCCACCACT 3′ (FAM tagged)/reverse 5′ AGTGCTAGGATTACAGACATGGGTCA 3′ at 64°C; MMP-9, forward 5′ TGGTCAACGTAGTGAAACCCCATCT 3′/reverse 5′ TCCAGGCCCAATTATCACACTTAT 3′ at 67°C] and elongation for 30 s at 72°C; then 10 min at 72°C.

Genotyping. Genotype information for each gene is shown in Table 1. The MMP-1 and MMP-3 genotypes were determined by studying PCR product length by fluorescent genotyping. The forward PCR primers for MMP-1 and MMP-3 were labeled fluorescently with HEX and FAM, respectively. Each PCR product was diluted to 40 pg/μL; 2 μL of this was then added to 8 μL of Hi-Di and Rox size standard (ratio, 50:1; Applied Biosystems). The resulting 10 μL was then loaded onto an ABI 3700 automated sequencer, and the results were analyzed using Genescan and Genotyper packages (Applied Biosystems).

Table 1.

MMP polymorphism information

Gene namePolymorphismSNP IDPCR product size (bp)Screening methodRestriction enzyme*Recognition sequenceWild fragment size (bp)Mutant fragment size (bp)
MMP-1 Insertion of guanine residue at −1,607 bp rs1799750 132 or 133 Fluorescent genotyping   132 133 
MMP-3 Deletion of an adenine residue at −1,171 bp rs3025058 188 or 189 Fluorescent genotyping   189 188 
MMP-7 A to G substitution at −181 bp rs11568818 134 PCR-RFLP EcoRI 5′ G/AATTC 3′ 134 102 and 32 
      3′ CTTAA/G 5′   
MMP-9 C to T substitution at −1,562 bp rs3918242 386 PCR-RFLP Sph5′ GCATG/C 3′ 386 320 and 66 
      3′ C/GATCG 5′   
MMP-12 A to G substitution at −82 bp rs2276109 185 PCR-RFLP HpyCH4III 5′ ACN/GT 3′ 163 and 22 101, 62, and 22 
      3′ TG/NCA 5′   
MMP-13 A to G substitution at −77 bp rs2252070 233 PCR-RFLP Bsr5′ ACTGGN/3′ 233 168 and 65 
      3′ TGAC/CN 5′   
Gene namePolymorphismSNP IDPCR product size (bp)Screening methodRestriction enzyme*Recognition sequenceWild fragment size (bp)Mutant fragment size (bp)
MMP-1 Insertion of guanine residue at −1,607 bp rs1799750 132 or 133 Fluorescent genotyping   132 133 
MMP-3 Deletion of an adenine residue at −1,171 bp rs3025058 188 or 189 Fluorescent genotyping   189 188 
MMP-7 A to G substitution at −181 bp rs11568818 134 PCR-RFLP EcoRI 5′ G/AATTC 3′ 134 102 and 32 
      3′ CTTAA/G 5′   
MMP-9 C to T substitution at −1,562 bp rs3918242 386 PCR-RFLP Sph5′ GCATG/C 3′ 386 320 and 66 
      3′ C/GATCG 5′   
MMP-12 A to G substitution at −82 bp rs2276109 185 PCR-RFLP HpyCH4III 5′ ACN/GT 3′ 163 and 22 101, 62, and 22 
      3′ TG/NCA 5′   
MMP-13 A to G substitution at −77 bp rs2252070 233 PCR-RFLP Bsr5′ ACTGGN/3′ 233 168 and 65 
      3′ TGAC/CN 5′   
*

Backslash (/) characters indicate the location that the restriction enzyme cuts in the sequence.

The MMP-7 (EcoRI), MMP-9 (SphI), MMP-12 (HpyCH4III), and MMP-13 (BsrI) genotypes were determined by PCR-RFLP assays. The restriction enzymes used for each gene are displayed in parentheses. All enzymes were obtained from New England Biosciences, and digestion was done in a 30-μL reaction volume following the manufacturer's instructions. After digestion, the products were resolved by electrophoresis on a 4% agarose gel and stained with ethidium bromide.

To determine the genotyping false call rate a 10% sample of randomly selected patients were regenotyped for each of the six MMPs (22).

Statistical analysis. Power and sample size was calculated using QUANTO version 1.2.1 (23). For the genes examined, in the Caucasian-only population, a sample size of 116 gives 80% power and a 0.05 level of significance. Differences in patients' characteristics and pathologic factors stratified by lymph node status were evaluated using χ2 test. The associations between MMP genotype frequencies and lymph node status were estimated by computing odds ratios and 95% confidence intervals (95% CI) from both univariate and multivariate logistic regression analyses with adjustment for tumor grade. The association between genotype and disease-free and overall survival was investigated using the method of Kaplan-Meier and was estimated using the log-rank test. Cox regression models were used to adjust for potential confounders. All statistical analyses were two-sided and done using Minitab release 14.20 and STATA 9.2. We used Chaplin 1.2.2 (24, 25) and HAPSTAT (26, 27) to identify haplotypes that were associated with lymph node metastasis and Thesias (28, 29) to identify haplotypes that were associated with survival.

Cohort characteristics. We analyzed MMP promoter polymorphisms in a cohort of 221 patients, comprising 128 lymph node–negative and 93 lymph node–positive patients. This cohort consisted of mixed ethnicities, with Caucasian patients comprising 65% of the study group. The remaining 35% comprised 1 Pakistani, 1 Arabic, 2 Muslim, 2 Greek, 3 Turkish, 4 Asian, 4 Jewish, 18 African, and 47 other patients for whom ethnicity was not reported. Owing to the heterogeneous nature of the group, the cohort was analyzed as two groups: Caucasian-only and mixed ethnicity, which included all patients. Patient tumors were grade matched, with the exception of the grade I tumors, which were underrepresented in the lymph node–positive cases. Patients were also matched for estrogen receptor/progesterone receptor status and age. At the time of breast cancer diagnosis, lymph node–negative patients were between ages 33 and 88 years (mean, 61 ± 12) and lymph node–positive patients were between ages 36 and 77 years (mean, 57 ± 11). No associations were observed between estrogen receptor/progesterone receptor status or age and the occurrence of lymph node metastasis. Higher grade tumors were associated with a lymph node–positive status (P < 0.001), and there was a significant relationship between lymph node–positive status and reduced survival (P < 0.001). Characteristics of the study population are summarized in Table 2.

Table 2.

Characteristics and pathologic factors by lymph node status and population group

CharacteristicsCaucasian
Mixed ethnicity (all subjects)
Node-positive, n (%)Node-negative, n (%)P*Node-positive, n (%)Node-negative, n (%)P*
Age (y)   0.07   0.07 
    ≤60 31 (58) 38 (43)  46 (58) 53 (45)  
    >60 22 (42) 51 (57)  33 (42) 65 (55)  
Tumor grade   0.001   0.001 
    1 1 (2) 18 (20)  2 (3) 25 (21)  
    2 25 (49) 42 (48)  32 (42) 55 (47)  
    3 24 (47) 28 (32)  42 (55) 37 (32)  
Unknown 1 (2) 0 (0)  1 (1) 0 (0)  
Estrogen receptor status   0.54   0.61 
    Positive 7 (13) 15 (17)  10 (13) 20 (18)  
    Negative 45 (87) 71 (83)  67 (87) 94 (82)  
Progesterone receptor status   0.39   0.90 
    Positive 16 (33) 20 (26)  20 (27) 27 (26)  
    Negative 33 (67) 58 (74)  54 (73) 76 (74)  
CharacteristicsCaucasian
Mixed ethnicity (all subjects)
Node-positive, n (%)Node-negative, n (%)P*Node-positive, n (%)Node-negative, n (%)P*
Age (y)   0.07   0.07 
    ≤60 31 (58) 38 (43)  46 (58) 53 (45)  
    >60 22 (42) 51 (57)  33 (42) 65 (55)  
Tumor grade   0.001   0.001 
    1 1 (2) 18 (20)  2 (3) 25 (21)  
    2 25 (49) 42 (48)  32 (42) 55 (47)  
    3 24 (47) 28 (32)  42 (55) 37 (32)  
Unknown 1 (2) 0 (0)  1 (1) 0 (0)  
Estrogen receptor status   0.54   0.61 
    Positive 7 (13) 15 (17)  10 (13) 20 (18)  
    Negative 45 (87) 71 (83)  67 (87) 94 (82)  
Progesterone receptor status   0.39   0.90 
    Positive 16 (33) 20 (26)  20 (27) 27 (26)  
    Negative 33 (67) 58 (74)  54 (73) 76 (74)  
*

Two-sided χ2 test.

Association between individual genotypes and tumor spread. The genotype distributions of all MMPs in the mixed ethnicity group and for the selected Caucasian group of patients are shown in Table 3. All data were adjusted for tumor grade. The presence of polymorphisms within the promoters of MMP-1 and MMP-3, resulting from the insertion/deletion of a G or A, respectively, was determined by fluorescent genotyping. The SNPs for MMP-7, MMP-9, MMP-12, and MMP-13, wherein the SNP generated or eliminated a restriction enzyme recognition site, were identified by PCR-RFLP. The application of these approaches permitted the determination of an individual's genotype for each of these loci. The average genotyping success rate for the 221 patients was >90%, with a false call rate of <1%. With the exception of MMP-13, the distribution of genotypes did not deviate from Hardy-Weinberg equilibrium, which suggests that this patient cohort did not deviate genetically from the general population of the United Kingdom. In the whole cohort, regression analyses showed that patients carrying the 2G/2G genotype for MMP-1 showed a significant 3.9-fold (95% CI, 1.7-9.4; P < 0.001) increased risk of lymph node metastasis compared with subjects carrying the 1G/1G genotype (Table 3). Subjects carrying the C/T genotype for MMP-9 had a significant 3.6-fold (95% CI, 1.0-11.1; P < 0.001) increased risk of lymph node metastasis compared with C/C carriers (Table 3). There were no patients with T/T genotype. To minimize possible confounding issues due to allele frequency variation by race, separate analyses were done on the Caucasian-only group. This strengthened the association of the MMP-9 genotype with nodal status with the C/T genotype exhibiting a significant 9.1-fold (95% CI, 1.7-48.4; P = 0.01) increased risk of nodal invasion, whereas the association between the 2G/2G MMP-1 genotype and nodal status showed a borderline-significant increased risk of metastasis (2.6-fold; 95% CI, 1.0-6.9; P < 0.06). The genotype frequencies for MMP-3, MMP-7, MMP-12, and MMP-13 were not significantly different between node-negative and node-positive patients in either the mixed ethnicity or Caucasian-only group. Separate analyses were not done on individual ethnic groups because the numbers in each group were too small.

Table 3.

Analysis of association between MMPs and the risk of lymph node metastasis by population group

GenotypeMixed ethnicity
Caucasian
No. patientsNode-negative, n (%)Node-positive, n (%)Crude OR [95% CI] (P)Adjusted* OR [95% CI] (P)No. patientsNode-negative, n (%)Node-positive, n (%)Crude OR [95% CI] (P)Adjusted* OR [95% CI] (P)
MMP-1           
    1G/1G 52 35 (27.8) 17 (18.5) 1.0 1.0 38 26 (29.5) 12 (23) 1.0 1.0 
    1G/2G 101 64 (50.8) 37 (40.2) 1.2 [0.6-2.4] (0.63) 1.2 [0.5-2.6] (0.75) 63 43 (48.9) 20 (38.5) 1.01 [0.3-2.4] (0.98) 0.9 [0.4-2.3] (0.83) 
    2G/2G 65 27 (21.4) 38 (41.3) 2.9 [1.4-6.2] (0.01) 3.9 [1.7-9.4] (0.001) 39 19 (21.6) 20 (38.5) 2.3 [0.9-5.8] (0.08) 2.6 [1.0-6.9] (0.06) 
MMP-3           
    5A/5A 49 26 (20.9) 23 (25.5) 1.0 1.0 39 23 (27) 16 (32) 1.0 1.0 
    5A/6A 114 70 (56.5) 44 (49) 0.7 [0.4-1.4] (0.32) 1.1 [0.5-2.3] (0.88) 73 44 (51.8) 29 (58) 1.0 [0.4-2.1] (0.89) 1.1 [0.5-2.4] (0.92) 
    6A/6A 51 28 (22.6) 23 (25.5) 0.9 [0.4-2.0] (0.85) 0.8 [0.3-2.0] (0.63) 23 18 (21.2) 5 (10) 0.4 [0.1-1.3] (0.40) 0.3 [0.1-1.2] (0.10) 
MMP-7           
    A/A 70 37 (31.4) 33 (37.9) 1.0 1.0 47 30 (37) 17 (34.7) 1.0 1.0 
    A/G 96 60 (50.8) 36 (41.4) 0.7 [0.4-1.3] (0.21) 0.6 [0.3-1.2] (0.17) 59 39 (48) 20 (42.5) 0.9 [0.4-2.0] (0.81) 0.7 [0.3-1.7] (0.54) 
    G/G 39 21 (17.8) 18 (20.7) 1.0 [0.4-2.1] (0.92) 0.7 [0.3-1.7] (0.40) 24 12 (15) 12 (22.8) 1.8 [0.7-4.8] (0.26) 1.3 [0.4-3.7] (0.65) 
MMP-9           
    C/C 167 105 (93.7) 62 (81.6) 1.0 1.0 109 74 (97.3) 35 (81.3) 1.0 1.0 
    C/T 21 7 (6.3) 14 (18.4) 3.4 [1.3-8.9] (0.01) 3.6 [1.2. 11.1] (0.001) 10 2 (2.7) 8 (19.7) 8.5 [1.7-41.9] (0.01) 9.1 [1.7-48.4] (0.01) 
MMP-12           
    A/A 168 98 (80.3) 70 (82.4) 1.0 1.0 107 67 (80.7) 40 (83.3) 1.0 1.0 
    A/G 39 24 (19.7) 15 (17.6) 0.9 [0.4-1.8] (71) 1.2 [0.5-2.8] (0.63) 24 16 (19.3) 8 (16.7) 0.8 [0.3-2.1] (0.71) 1.1 [0.4-2.8] (0.91) 
MMP-13           
    A/A 105 62 (54.9) 43 (53.8) 1.0 1.0 71 44 (56.4) 27 (61.4) 1.0 1.0 
    A/G 83 47 (41.6) 36 (45) 1.1 [0.6-2.0] (0.74) 1.2 [0.6-2.3] (0.62) 49 32 (41) 17 (38.6) 0.8 [0.4-1.6] (0.74) 0.9 [0.4-2.0] (0.79) 
    G/G 4 (3.5) 1 (1.2) 0.4 [0.0-3.3] (0.36) 0.6 [0.1-6.2] (0.71) 2 (2.6) 0 (0.0) 
GenotypeMixed ethnicity
Caucasian
No. patientsNode-negative, n (%)Node-positive, n (%)Crude OR [95% CI] (P)Adjusted* OR [95% CI] (P)No. patientsNode-negative, n (%)Node-positive, n (%)Crude OR [95% CI] (P)Adjusted* OR [95% CI] (P)
MMP-1           
    1G/1G 52 35 (27.8) 17 (18.5) 1.0 1.0 38 26 (29.5) 12 (23) 1.0 1.0 
    1G/2G 101 64 (50.8) 37 (40.2) 1.2 [0.6-2.4] (0.63) 1.2 [0.5-2.6] (0.75) 63 43 (48.9) 20 (38.5) 1.01 [0.3-2.4] (0.98) 0.9 [0.4-2.3] (0.83) 
    2G/2G 65 27 (21.4) 38 (41.3) 2.9 [1.4-6.2] (0.01) 3.9 [1.7-9.4] (0.001) 39 19 (21.6) 20 (38.5) 2.3 [0.9-5.8] (0.08) 2.6 [1.0-6.9] (0.06) 
MMP-3           
    5A/5A 49 26 (20.9) 23 (25.5) 1.0 1.0 39 23 (27) 16 (32) 1.0 1.0 
    5A/6A 114 70 (56.5) 44 (49) 0.7 [0.4-1.4] (0.32) 1.1 [0.5-2.3] (0.88) 73 44 (51.8) 29 (58) 1.0 [0.4-2.1] (0.89) 1.1 [0.5-2.4] (0.92) 
    6A/6A 51 28 (22.6) 23 (25.5) 0.9 [0.4-2.0] (0.85) 0.8 [0.3-2.0] (0.63) 23 18 (21.2) 5 (10) 0.4 [0.1-1.3] (0.40) 0.3 [0.1-1.2] (0.10) 
MMP-7           
    A/A 70 37 (31.4) 33 (37.9) 1.0 1.0 47 30 (37) 17 (34.7) 1.0 1.0 
    A/G 96 60 (50.8) 36 (41.4) 0.7 [0.4-1.3] (0.21) 0.6 [0.3-1.2] (0.17) 59 39 (48) 20 (42.5) 0.9 [0.4-2.0] (0.81) 0.7 [0.3-1.7] (0.54) 
    G/G 39 21 (17.8) 18 (20.7) 1.0 [0.4-2.1] (0.92) 0.7 [0.3-1.7] (0.40) 24 12 (15) 12 (22.8) 1.8 [0.7-4.8] (0.26) 1.3 [0.4-3.7] (0.65) 
MMP-9           
    C/C 167 105 (93.7) 62 (81.6) 1.0 1.0 109 74 (97.3) 35 (81.3) 1.0 1.0 
    C/T 21 7 (6.3) 14 (18.4) 3.4 [1.3-8.9] (0.01) 3.6 [1.2. 11.1] (0.001) 10 2 (2.7) 8 (19.7) 8.5 [1.7-41.9] (0.01) 9.1 [1.7-48.4] (0.01) 
MMP-12           
    A/A 168 98 (80.3) 70 (82.4) 1.0 1.0 107 67 (80.7) 40 (83.3) 1.0 1.0 
    A/G 39 24 (19.7) 15 (17.6) 0.9 [0.4-1.8] (71) 1.2 [0.5-2.8] (0.63) 24 16 (19.3) 8 (16.7) 0.8 [0.3-2.1] (0.71) 1.1 [0.4-2.8] (0.91) 
MMP-13           
    A/A 105 62 (54.9) 43 (53.8) 1.0 1.0 71 44 (56.4) 27 (61.4) 1.0 1.0 
    A/G 83 47 (41.6) 36 (45) 1.1 [0.6-2.0] (0.74) 1.2 [0.6-2.3] (0.62) 49 32 (41) 17 (38.6) 0.8 [0.4-1.6] (0.74) 0.9 [0.4-2.0] (0.79) 
    G/G 4 (3.5) 1 (1.2) 0.4 [0.0-3.3] (0.36) 0.6 [0.1-6.2] (0.71) 2 (2.6) 0 (0.0) 

NOTE: Values in bold indicate significant results.

Abbreviation: OR, odds ratio.

*

Adjusted for tumor grade.

Association between individual genotypes and overall survival and disease-free survival. Using the Cox regression model (Table 4A), only the presence of the 2G/2G genotype for MMP-1 compared with the presence of the 1G/1G genotype was predictive of a shorter patient survival time [crude hazard ratio (CHR) for overall survival, 3.1; 95% CI, 1.1-8.7; P = 0.03; Fig. 1A]. None of the other MMP polymorphisms was associated significantly with survival. After adjusting for tumor grade and lymph node status, the MMP-1 polymorphism was no longer significantly associated with overall survival (adjusted hazard ratio for overall survival, 2.4; 95% CI, 0.8-6.6; P = 0.1; Fig. 1B; Table 4A). There was no significant association between individual MMP SNPs and disease-free survival (Table 4B).

Table 4.

Multivariate analysis of overall survival and disease-free survival

A. Multivariate analysis of overall survival
GenotypenAlive, n (%)Dead, n (%)CHR [95% CI] (P)Adjusted hazard ratio [95% CI] (P)*
MMP-1      
    1G/1G 36 31 (29.8) 5 (15.6) 1.0 1.0 
    1G/2G 63 51 (49) 12 (37.5) 1.7 [0.6-4.7] (0.34) 1.3 [0.5-3.8] (0.60) 
    2G/2G 37 22 (21.2) 15 (46.9) 3.1 [1.1-8.7] (0.03) 2.4 [0.8-6.6] (0.10) 
MMP-3      
    5A/5A 39 26 (25.5) 13 (43.3) 1.0 1.0 
    5A/6A 71 58 (56.9) 13 (43.3) 0.5 [0.2-1.1] (0.07) 0.6 [0.3-1.2] (0.14) 
    6A/6A 22 18 (17.6) 4 (13.4) 0.4 [0.1-1.2] (0.11) 0.6 [0.2-2.0] (0.45) 
MMP-7      
    A/A 45 36 (36.4) 9 (28.1) 1.0 1.0 
    A/G 59 45 (45.5) 14 (43.8) 1.2 [0.5-2.9] (0.61) 1.1 [0.5-2.6] (0.80) 
    G/G 24 15 (18.1) 9 (28.1) 1.9 [0.8-4.8] (0.17) 1.4 [0.5-3.7] (0.46) 
MMP-9      
    C/C 105 81 (93.1) 24 (85.7) 1.0 1.0 
    C/T 10 6 (6.9) 4 (14.3) 1.6 [0.6-4.7] (0.37) 0.5 [0.2-1.5] (0.22) 
MMP-12      
    A/A 103 77 (79.4) 26 (86.7) 1.0 1.0 
    A/G 24 20 (20.6) 4 (13.3) 0.6 [0.2-1.7] (0.34) 0.9 [0.3-2.6] (0.80) 
MMP-13      
    A/A 70 51 (56.7) 19 (63.3) 1.0 1.0 
    A/G 48 37 (41.1) 11 (36.7) 0.8 [0.4-1.6] (0.47) 0.8 [0.4-1.7] (0.61) 
    G/G 2 (2.2) 0 (0%) 
      
B. Multivariate analysis of disease-free survival
 
     
Genotype
 
n
 
Disease-free survival, n (%)
 
Recurrence n (%)
 
CHR [95% CI] (P)
 
Adjusted hazard ratio [95% CI] (P)*
 
MMP-1      
    1G/1G 34 28 (28.9) 6 (20.7) 1.0 1.0 
    1G/2G 59 49 (50.5) 10 (34.3) 1.2 [0.4-3.2] (0.76) 1.0 [0.4-3.0] (0.89) 
    2G/2G 33 20 (20.6) 13 (44.8) 2.3 [0.9-6.1] (0.09) 1.7 [0.7-4.8] (0.24) 
MMP-3      
    5A/5A 33 23 (24.7) 9 (30) 1.0 1.0 
    5A/6A 69 54 (53.1) 15 (50) 0.8 [0.4-1.9] (0.63) 0.9 [0.4-2.0] (0.74) 
    6A/6A 22 16 (17.2) 6 (20) 0.9 [0.3-2.4] (0.76) 1.3 [0.4-3.6] (0.67) 
MMP-7      
    A/A 44 34 (39.1) 10 (32.3) 1.0 1.0 
    A/G 55 39 (44.8) 16 (51.6) 1.3 [0.6-2.8] (0.55) 1.3 [0.6-2.8] (0.54) 
    G/G 19 14 (16.1) 5 (16.1) 1.0 [0.3-2.8] (0.94) 0.9 [0.30-2.6] (0.83) 
MMP-9      
    C/C 98 74 (93.7) 24 (85.7) 1.0 1.0 
    C/T 5 (6.3) 4 (19.3) 1.6 [0.56-4.6] (0.38) 0.67 [0.22-2.07] (0.45) 
MMP-12      
    A/A 96 70 (78.7) 26 (83.9) 1.0 1.0 
    A/G 24 19 (21.3) 5 (16.1) 0.7 [0.23-1.9] (0.54) 0.8 [0.31-2.2] (0.70) 
MMP-13      
    A/A 62 45 (54.9) 17 (63) 1.0 1.0 
    A/G 45 35 (42.7) 10 (37) 0.78 [0.36-1.7] (0.54) 0.78 [0.36-1.7] (0.54) 
    G/G 2 (2.4) 
A. Multivariate analysis of overall survival
GenotypenAlive, n (%)Dead, n (%)CHR [95% CI] (P)Adjusted hazard ratio [95% CI] (P)*
MMP-1      
    1G/1G 36 31 (29.8) 5 (15.6) 1.0 1.0 
    1G/2G 63 51 (49) 12 (37.5) 1.7 [0.6-4.7] (0.34) 1.3 [0.5-3.8] (0.60) 
    2G/2G 37 22 (21.2) 15 (46.9) 3.1 [1.1-8.7] (0.03) 2.4 [0.8-6.6] (0.10) 
MMP-3      
    5A/5A 39 26 (25.5) 13 (43.3) 1.0 1.0 
    5A/6A 71 58 (56.9) 13 (43.3) 0.5 [0.2-1.1] (0.07) 0.6 [0.3-1.2] (0.14) 
    6A/6A 22 18 (17.6) 4 (13.4) 0.4 [0.1-1.2] (0.11) 0.6 [0.2-2.0] (0.45) 
MMP-7      
    A/A 45 36 (36.4) 9 (28.1) 1.0 1.0 
    A/G 59 45 (45.5) 14 (43.8) 1.2 [0.5-2.9] (0.61) 1.1 [0.5-2.6] (0.80) 
    G/G 24 15 (18.1) 9 (28.1) 1.9 [0.8-4.8] (0.17) 1.4 [0.5-3.7] (0.46) 
MMP-9      
    C/C 105 81 (93.1) 24 (85.7) 1.0 1.0 
    C/T 10 6 (6.9) 4 (14.3) 1.6 [0.6-4.7] (0.37) 0.5 [0.2-1.5] (0.22) 
MMP-12      
    A/A 103 77 (79.4) 26 (86.7) 1.0 1.0 
    A/G 24 20 (20.6) 4 (13.3) 0.6 [0.2-1.7] (0.34) 0.9 [0.3-2.6] (0.80) 
MMP-13      
    A/A 70 51 (56.7) 19 (63.3) 1.0 1.0 
    A/G 48 37 (41.1) 11 (36.7) 0.8 [0.4-1.6] (0.47) 0.8 [0.4-1.7] (0.61) 
    G/G 2 (2.2) 0 (0%) 
      
B. Multivariate analysis of disease-free survival
 
     
Genotype
 
n
 
Disease-free survival, n (%)
 
Recurrence n (%)
 
CHR [95% CI] (P)
 
Adjusted hazard ratio [95% CI] (P)*
 
MMP-1      
    1G/1G 34 28 (28.9) 6 (20.7) 1.0 1.0 
    1G/2G 59 49 (50.5) 10 (34.3) 1.2 [0.4-3.2] (0.76) 1.0 [0.4-3.0] (0.89) 
    2G/2G 33 20 (20.6) 13 (44.8) 2.3 [0.9-6.1] (0.09) 1.7 [0.7-4.8] (0.24) 
MMP-3      
    5A/5A 33 23 (24.7) 9 (30) 1.0 1.0 
    5A/6A 69 54 (53.1) 15 (50) 0.8 [0.4-1.9] (0.63) 0.9 [0.4-2.0] (0.74) 
    6A/6A 22 16 (17.2) 6 (20) 0.9 [0.3-2.4] (0.76) 1.3 [0.4-3.6] (0.67) 
MMP-7      
    A/A 44 34 (39.1) 10 (32.3) 1.0 1.0 
    A/G 55 39 (44.8) 16 (51.6) 1.3 [0.6-2.8] (0.55) 1.3 [0.6-2.8] (0.54) 
    G/G 19 14 (16.1) 5 (16.1) 1.0 [0.3-2.8] (0.94) 0.9 [0.30-2.6] (0.83) 
MMP-9      
    C/C 98 74 (93.7) 24 (85.7) 1.0 1.0 
    C/T 5 (6.3) 4 (19.3) 1.6 [0.56-4.6] (0.38) 0.67 [0.22-2.07] (0.45) 
MMP-12      
    A/A 96 70 (78.7) 26 (83.9) 1.0 1.0 
    A/G 24 19 (21.3) 5 (16.1) 0.7 [0.23-1.9] (0.54) 0.8 [0.31-2.2] (0.70) 
MMP-13      
    A/A 62 45 (54.9) 17 (63) 1.0 1.0 
    A/G 45 35 (42.7) 10 (37) 0.78 [0.36-1.7] (0.54) 0.78 [0.36-1.7] (0.54) 
    G/G 2 (2.4) 

NOTE: Values in bold indicate significant results.

*

Adjusted for tumor grade and node status.

Fig. 1.

Kaplan-Meier curves for MMP-1. A, displays the crude results for all Caucasian patients, the presence of the 2G/2G (15 of 37 patients with this genotype died; CHR for overall survival, 4.1; 95% CI, 1.1-8.7) genotype for MMP-1 was predictive of a shorter survival compared with the presence of the 1G/1G (5 of 36 patients with this genotype died) or 1G/2G (12 of 63 patients with this genotype died). B, displays the adjusted results for all Caucasian patients. For node-negative patients, 1 of 25 patients with the 1G/1G genotype died, 4 of 43 patients with the 1G/2G genotype died, and 4 of 17 patients with the 2G/2G genotype died. For node positive patients, 4 of 11 patients with the 1G/1G genotype died, 8 of 20 patients with the 1G/2G genotype died, and 11 of 20 patients with the 2G/2G genotype died The association of genotype and overall survival was no longer significant after adjusting for tumor grade and lymph node status (adjusted hazard ratio for overall survival, 2.4; 95% CI, 0.8-6.6).

Fig. 1.

Kaplan-Meier curves for MMP-1. A, displays the crude results for all Caucasian patients, the presence of the 2G/2G (15 of 37 patients with this genotype died; CHR for overall survival, 4.1; 95% CI, 1.1-8.7) genotype for MMP-1 was predictive of a shorter survival compared with the presence of the 1G/1G (5 of 36 patients with this genotype died) or 1G/2G (12 of 63 patients with this genotype died). B, displays the adjusted results for all Caucasian patients. For node-negative patients, 1 of 25 patients with the 1G/1G genotype died, 4 of 43 patients with the 1G/2G genotype died, and 4 of 17 patients with the 2G/2G genotype died. For node positive patients, 4 of 11 patients with the 1G/1G genotype died, 8 of 20 patients with the 1G/2G genotype died, and 11 of 20 patients with the 2G/2G genotype died The association of genotype and overall survival was no longer significant after adjusting for tumor grade and lymph node status (adjusted hazard ratio for overall survival, 2.4; 95% CI, 0.8-6.6).

Close modal

Association between MMP haplotype and tumor behavior. Because MMP-1, MMP-3, MMP-7, MMP-12, and MMP-13 genes are clustered on chromosome 11q22.3, we addressed whether there were any associations between specific haplotypes and tumor behavior. Eleven common haplotypes were identified among both node-negative and node-positive patients, with the distribution of most being similar between the two patient groups (Table 5). However, two haplotypes did exhibit a significant association with lymph node metastasis: 2G-5A-A-A-A (2% frequency in lymph node–negative patients versus 10% in lymph node–positive; P = 0.02) and 2G-5A-G-A-A (8% in lymph node–negative patients versus 20% in lymph node–positive; P = 0.02). In addition, these two haplotypes (2G-5A-A-A-A: CHR 2.5, 95% CI 1.2-5.2, P = 0.02; 2G-5A-G-A-A: CHR 4.5, 95% CI 2.3-8.8, P = 0.00001) also showed a significant association with overall survival. After adjusting for tumor grade and lymph node status, the 2G-5A-G-A-A haplotype (adjusted hazard ratio, 2.6; 95% CI, 1.3-5.0; P = 0.006) was still associated with overall survival.

Table 5.

Analysis of the association between haplotype and node status

Haplotype*Frequencies
Wald test (P)AIC
Node-negativeNode-positive
1G-5A-A-A-A 19.4 13.2 1.07 (0.28) 1,095.92 
1G-5A-G-A-A 9.7 11.2 0.11 (0.91) 1,097.14 
1G-6A-A-A-A 6.3 4.6 1.12 (0.26) 1,095.58 
1G-6A-A-G-A 1.1 2.1 0.42 (0.68) 1,096.98 
2G-5A-A-A-A 2.3 9.7 2.35 (0.02) 1,090.56 
2G-5A-A-A-G 2.5 4.6 1.07 (0.28) 1,094.96 
2G-5A-G-A-A 8.3 19.2 2.24 (0.02) 1,092.56 
2G-6A-A-A-A 16.5 13.5 0.36 (0.72) 1,097.02 
2G-6A-A-A-G 1.7 1.9 0.18 (0.85) 1,097.07 
2G-6A-A-G-A 1.1 2.4 0.35 (0.73) 1,097.03 
2G-6A-G-A-A 6.8 2.9 0.99 (0.32) 1,095.96 
Haplotype*Frequencies
Wald test (P)AIC
Node-negativeNode-positive
1G-5A-A-A-A 19.4 13.2 1.07 (0.28) 1,095.92 
1G-5A-G-A-A 9.7 11.2 0.11 (0.91) 1,097.14 
1G-6A-A-A-A 6.3 4.6 1.12 (0.26) 1,095.58 
1G-6A-A-G-A 1.1 2.1 0.42 (0.68) 1,096.98 
2G-5A-A-A-A 2.3 9.7 2.35 (0.02) 1,090.56 
2G-5A-A-A-G 2.5 4.6 1.07 (0.28) 1,094.96 
2G-5A-G-A-A 8.3 19.2 2.24 (0.02) 1,092.56 
2G-6A-A-A-A 16.5 13.5 0.36 (0.72) 1,097.02 
2G-6A-A-A-G 1.7 1.9 0.18 (0.85) 1,097.07 
2G-6A-A-G-A 1.1 2.4 0.35 (0.73) 1,097.03 
2G-6A-G-A-A 6.8 2.9 0.99 (0.32) 1,095.96 

NOTE: Values in bold indicate significant results.

Abbreviation: AIC, Akaike's information criteria.

*

Haplotype order MMP-1 (1G or 2G), MMP-3 (5A or 6A), MMP-7 (A or G), MMP-12 (A or G), and MMP-13 (A or G).

Tests whether an independent variable has a statistically significant relationship with a dependent variable.

The AIC is a goodness-of-fit measure.

The haplotype 2G-5A-G-A-A was associated with disease-free survival in the unadjusted analysis (CHR, 2.7; 95% CI, 1.08-6.70; P = 0.03) but was no longer significant after adjusting for lymph node status and grade (CHR, 1.9; 95% CI, 0.68-5.45; P = 0.21).

MMPs have been implicated in tumor progression, and high levels of expression have been related to more aggressive tumor behavior and poorer patient prognosis (20, 21). This study, therefore, investigated the association between functional SNPs in MMP genes, previously implicated in breast cancer, and breast cancer spread and patient survival. In the genotype analysis, wherein each MMP SNP was studied separately in the mixed ethnicity patient cohort, the 2G/2G genotype of MMP-1, which generates an increased level of gene expression (13), was more frequent in the lymph node–positive patients and conferred a 3.9-fold increased risk of lymph node metastasis. The C/T genotype of MMP-9 was found to confer a 3.6-fold increased occurrence of lymph node metastasis. Interestingly, there is a change in the association pattern when analysis is restricted to the Caucasian-only group, with the MMP-1 2G/2G genotype risk decreasing to 2.6-fold, whereas the MMP-9 C/T genotype confers a 9.1-fold increase in risk of metastasis in this group. Such differences between different ethnic groups may, in some part, explain the discrepancies reported between associations in the literature and the work described herein. Thus, although Przybylowska et al. (3) reported a similar association between MMP-1 2G/2G genotype and lymph node metastasis in patients with breast cancer, they showed no such association with the MMP-9 T allele. This could be a consequence of variation in the ethnicity of the patients from the two cohorts. In our study, when the Caucasian patients were subtracted from the ethnically mixed group, and the latter analyzed, there was no association between the T allele and node status when corrected for grade (P = 0.96; odds ratio, 1.05; 95% CI, 0.18-5.93). Similarly, in colorectal cancer, whereas a relationship between the MMP-1 2G/2G genotype and poor prognosis has been identified in an Italian cohort of patients with colorectal cancer (30), no such relationship was identified in a recent large Australian study (31).

Previous studies have identified links between promoter polymorphisms in MMP-1 and MMP-9 (15, 32) and increased expression of enzyme levels. In addition, increased expression for both MMP-1 and MMP-9 has been associated with lymph node metastasis (33) and poor prognosis (3, 34, 35) in breast cancer. In keeping with this, our data and others' point to the potential prognostic role of MMP-1 and MMP-9 polymorphisms in identifying patients at risk of more aggressive disease.

Having identified a link between genotype and node status, the analysis was extended to determine any association between genotype, disease-free survival, and overall survival. Previous studies have identified such links for both MMP-2 (36) and MMP-12 (37) in non–small cell lung cancer, between MMP-7 and gastric cancer (38) and between MMP-1 and colorectal cancer (39). In this study, analysis was restricted to the Caucasian-only group. No association between MMP genotype and disease-free survival was identified; however, initial analysis showed a significant association between the MMP-1 2G/2G genotype and overall survival. However, after adjustment for node status, this association was lost. This is in keeping with our hypothesis that elevated levels of MMPs promote spread of breast cancer. Thus, the high-expressing MMP-1 2G/2G genotype promotes lymph node metastasis, and prognosis is dependent on this facet of tumor behavior. Interestingly, even when adjusted for lymph node status, there remains a trend for decreased overall survival in patients with the 2G/2G genotype compared with 1G/2G or 1G/1G, which suggests that the enzyme may play a role in distant tumor dissemination. There was no association between MMP-9 T allele and overall survival despite the relationship between this allele and lymph node metastasis, which is difficult to explain, apart from acknowledging that this attests to the complexity of function of these enzymes and the process of tumor spread.

Given the likely multifaceted role of MMPs in tumor progression and the involvement of different enzymes at different stages of the disease (6, 34), it is plausible that the combined effect of multiple high-expressing MMP alleles may provide a stronger predictor of prognosis than individual SNPs. We therefore investigated disease behavior with MMP SNP haplotypes. This identified two haplotypes, 2G-5A-A-A-A and 2G-5A-G-A-A, linked to increased incidence of lymph node metastasis. The 2G-5A-A-A-A haplotype was shown to have a dominant effect (subjects with one copy of the haplotype have the same risk of lymph node metastasis as those subjects with two copies), whereas the 2G-5A-G-A-A haplotype exhibited a multiplicative effect, such that subjects with one copy of the haplotype are at an intermediate risk of lymph node metastasis, with respect to those subjects with zero or two copies. Furthermore, the 2G-5A-G-A-A haplotype was also associated with overall survival even after adjustment for lymph node status. Whereas this haplotype was associated with disease-free survival in unadjusted analysis, this relationship was lost when adjusted for lymph node status. In keeping with the genotype data, these haplotype associations are driven by the MMP-1 2G allele. The haplotypes also reflect the previously described linkage disequilibrium between the MMP-1 2G allele and the MMP-3 5A allele (40).

Polymorphisms in the promoters of MMPs have a functional role and have been shown to exhibit allelotypic effects on levels of gene transcript (15, 32). Although the lifelong effects of altered transcription are unclear, overexpression of MMPs caused by promoter polymorphisms may enhance cancer progression by virtue of their role in degradation of the ECM, thereby generating an environment that favors tumor cell migration. Modulation of the microenvironment is emerging as a critical factor in determining tumor cell behavior (41, 42), and changes in the stroma, such as those mediated through proteolytic remodeling, can have a major influence on tumor cell function (43). Thus, the altered expression of MMPs generated through functional SNPs and the consequent effect on tumor microenvironment may contribute to the patient-to-patient variability in breast cancer susceptibility and outcome. In patients with breast cancer, knowledge of the MMP SNP genotype and/or haplotype, as shown here, could contribute to identification of patients at higher risk and therefore influence treatment decisions.

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.

1
Beckmann MW, Niederacher D, Schnurch HG, Gusterson BA, Bender HG. Multistep carcinogenesis of breast cancer and tumour heterogeneity.
J Mol Med
1997
;
75
:
429
–39.
2
Belkin AM, Akimov SS, Zaritskaya LS, Ratnikov BI, Deryugina EI, Strongin AY. Matrix-dependent proteolysis of surface transglutaminase by membrane-type metalloproteinase regulates cancer cell adhesion and locomotion.
J Biol Chem
2001
;
276
:
18415
–22.
3
Przybylowska K, Kluczna A, Zadrozny M, et al. Polymorphisms of the promoter regions of matrix metalloproteinases genes MMP-1 and MMP-9 in breast cancer.
Breast Cancer Res Treat
2006
;
95
:
65
–72.
4
Savinov AY, Remacle AG, Golubkov VS, et al. Matrix metalloproteinase 26 proteolysis of the NH2-terminal domain of the estrogen receptor β correlates with the survival of breast cancer patients.
Cancer Res
2006
;
66
:
2716
–24.
5
Egeblad M, Werb Z. New functions for the matrix metalloproteinases in cancer progression.
Nat Rev Cancer
2002
;
2
:
161
–74.
6
Folgueras AR, Pendas AM, Sanchez LM, Lopez-Otin C. Matrix metalloproteinases in cancer: from new functions to improved inhibition strategies.
Int J Dev Biol
2004
;
48
:
411
–24.
7
Lemaitre V, D'Armiento J. Matrix metalloproteinases in development and disease.
Birth Defects Res Part C Embryo Today
2006
;
78
:
1
–10.
8
Murray GI, Duncan ME, O'Neil P, Melvin WT, Fothergill JE. Matrix metalloproteinase-1 is associated with poor prognosis in colorectal cancer.
Nat Med
1996
;
2
:
461
–2.
9
Jones JL, Glynn P, Walker RA. Expression of MMP-2 and MMP-9, their inhibitors, and the activator MT1-MMP in primary breast carcinomas.
J Pathol
1999
;
189
:
161
–8.
10
Sier CF, Kubben FJ, Ganesh S, et al. Tissue levels of matrix metalloproteinases MMP-2 and MMP-9 are related to the overall survival of patients with gastric carcinoma.
Br J Cancer
1996
;
74
:
413
–7.
11
Heppner KJ, Matrisian LM, Jensen RA, Rodgers WH. Expression of most matrix metalloproteinase family members in breast cancer represents a tumor-induced host response.
Am J Pathol
1996
;
149
:
273
–82.
12
Nishioka Y, Sagae S, Nishikawa A, Ishioka S, Kudo R. A relationship between Matrix metalloproteinase-1 (MMP-1) promoter polymorphism and cervical cancer progression.
Cancer Lett
2003
;
200
:
49
–55.
13
Rutter JL, Mitchell TI, Buttice G, et al. A single nucleotide polymorphism in the matrix metalloproteinase-1 promoter creates an Ets binding site and augments transcription.
Cancer Res
1998
;
58
:
5321
–5.
14
Ye S, Eriksson P, Hamsten A, Kurkinen M, Humphries SE, Henney AM. Progression of coronary atherosclerosis is associated with a common genetic variant of the human stromelysin-1 promoter which results in reduced gene expression.
J Biol Chem
1996
;
271
:
13055
–60.
15
Zhang B, Ye S, Herrmann SM, et al. Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis.
Circulation
1999
;
99
:
1788
–94.
16
Zhang J, Jin X, Fang S, et al. The functional polymorphism in the matrix metalloproteinase-7 promoter increases susceptibility to esophageal squamous cell carcinoma, gastric cardiac adenocarcinoma and non-small cell lung carcinoma.
Carcinogenesis
2005
;
26
:
1748
–53.
17
Yoon S, Kuivaniemi H, Gatalica Z, et al. MMP13 promoter polymorphism is associated with atherosclerosis in the abdominal aorta of young Black males.
Matrix Biol
2002
;
21
:
487
–98.
18
Jormsjo S, Ye S, Moritz J, et al. Allele-specific regulation of matrix metalloproteinase-12 gene activity is associated with coronary artery luminal dimensions in diabetic patients with manifest coronary artery disease.
Circ Res
2000
;
86
:
998
–1003.
19
Fang S, Jin X, Wang R, et al. Polymorphisms in the MMP1 and MMP3 promoter and non-small cell lung carcinoma in North China.
Carcinogenesis
2005
;
26
:
481
–6.
20
Matsumura S, Oue N, Nakayama H, et al. A single nucleotide polymorphism in the MMP-9 promoter affects tumor progression and invasive phenotype of gastric cancer.
J Cancer Res Clin Oncol
2005
;
131
:
19
–25.
21
Six L, Grimm C, Leodolter S, et al. A polymorphism in the matrix metalloproteinase-1 gene promoter is associated with the prognosis of patients with ovarian cancer.
Gynecol Oncol
2006
;
100
:
506
–10.
22
Bonin A, Bellemain E, Bronken Eidesen P, Pompanon F, Brochmann C, Taberlet P. How to track and assess genotyping errors in population genetics studies.
Mol Ecol
2004
;
13
:
3261
–73.
23
Gauderman WJ. Sample size requirements for association studies of gene-gene interaction.
Am J Epidemiol
2002
;
155
:
478
–84.
24
Lin DY, Zeng D, Millikan R. Maximum likelihood estimation of haplotype effects and haplotype-environment interactions in association studies.
Genet Epidemiol
2005
;
29
:
299
–312.
25
Epstein MP, Satten GA. Inference on haplotype effects in case-control studies using unphased genotype data.
Am J Hum Genet
2003
;
73
:
1316
–29.
26
Satten GA, Epstein MP. Comparison of prospective and retrospective methods for haplotype inference in case-control studies.
Genet Epidemiol
2004
;
27
:
192
–201.
27
Zeng D, Lin DY, Avery CL, North KE, Bray MS. Efficient semiparametric estimation of haplotype-disease associations in case-cohort and nested case-control studies.
Biostatistics
2006
;
7
:
486
–502.
28
Tregouet DA, Escolano S, Tiret L, Mallet A, Golmard JL. A new algorithm for haplotype-based association analysis: the Stochastic-EM algorithm.
Ann Hum Genet
2004
;
68
:
165
–77.
29
Tregouet DA, Ricard S, Nicaud V, et al. In-depth haplotype analysis of ABCA1 gene polymorphisms in relation to plasma ApoA1 levels and myocardial infarction.
Arterioscler Thromb Vasc Biol
2004
;
24
:
775
–81.
30
Ghilardi G, Biondi ML, Mangoni J, et al. Matrix metalloproteinase-1 promoter polymorphism 1G/2G is correlated with colorectal cancer invasiveness.
Clin Cancer Res
2001
;
7
:
2344
–6.
31
Hettiaratchi A, Hawkins NJ, McKenzie G, et al. The collagenase-1 (MMP-1) gene promoter polymorphism - 1607/2G is associated with favourable prognosis in patients with colorectal cancer.
Br J Cancer
2007
;
96
:
783
–92.
32
McCready J, Broaddus WC, Sykes V, Fillmore HL. Association of a single nucleotide polymorphism in the matrix metalloproteinase-1 promoter with glioblastoma.
Int J Cancer
2005
;
117
:
781
–5.
33
Nakopoulou L, Giannopoulou I, Gakiopoulou H, Liapis H, Tzonou A, Davaris PS. Matrix metalloproteinase-1 and -3 in breast cancer: correlation with progesterone receptors and other clinicopathologic features.
Hum Pathol
1999
;
30
:
436
–42.
34
Vizoso FJ, Gonzalez LO, Corte MD, et al. Study of matrix metalloproteinases and their inhibitors in breast cancer.
Br J Cancer
2007
;
96
:
903
–11.
35
Pellikainen JM, Ropponen KM, Kataja VV, Kellokoski JK, Eskelinen MJ, Kosma VM. Expression of matrix metalloproteinase (MMP)-2 and MMP-9 in breast cancer with a special reference to activator protein-2, HER2, and prognosis.
Clin Cancer Res
2004
;
10
:
7621
–8.
36
Rollin J, Regina S, Vourc'h P, et al. Influence of MMP-2 and MMP-9 promoter polymorphisms on gene expression and clinical outcome of non-small cell lung cancer.
Lung Cancer
2007
;
56
:
273
–80.
37
Heist RS, Marshall AL, Liu G, et al. Matrix metalloproteinase polymorphisms and survival in stage I non-small cell lung cancer.
Clin Cancer Res
2006
;
12
:
5448
–53.
38
Kubben FJ, Sier CF, van Duijn W, et al. Matrix metalloproteinase-2 is a consistent prognostic factor in gastric cancer.
Br J Cancer
2006
;
94
:
1035
–40.
39
Zinzindohoue F, Lecomte T, Ferraz JM, et al. Prognostic significance of MMP-1 and MMP-3 functional promoter polymorphisms in colorectal cancer.
Clin Cancer Res
2005
;
11
:
594
–9.
40
Hinoda Y, Okayama N, Takano N, et al. Association of functional polymorphisms of matrix metalloproteinase (MMP)-1 and MMP-3 genes with colorectal cancer.
Int J Cancer
2002
;
102
:
526
–9.
41
Allinen M, Beroukhim R, Cai L, et al. Molecular characterization of the tumor microenvironment in breast cancer.
Cancer Cell
2004
;
6
:
17
–32.
42
Kenny PA, Bissell MJ. Tumor reversion:correction of malignant behavior by microenvironmental cues.
Int J Cancer
2003
;
107
:
159
–70.
43
Hintermann E, Quaranta V. Epithelial cell motility on laminin-5: regulation by matrix assembly, proteolysis, integrins and erbB receptors.
Matrix Biol
2004
;
23
:
75
–85.