Conceived and designed the experiments: YB KY DL HG. Performed the experiments: DL HG. Analyzed the data: DL HG XX. Contributed reagents/materials/analysis tools: DL YL XX. Wrote the paper: DL HG. Software used in analysis: DL HG YL XX. Revising the article critically for important intellectual content: DL HG KY YB.
The authors have declared that no competing interests exist.
A variety of studies have evaluated the associations between polymorphisms in the promoter regions of Matrix metalloproteinases (MMPs) and cancer metastasis. However, the results remain inconclusive. To better understand the roles of MMP polymorphisms in metastasis, we conducted a comprehensive meta-analysis.
Electronic databases were searched (from January 2000 to June 2011) for any MMP genetic association studies in metastasis. Overall and subgroup analyses were performed. Odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the associations between MMP polymorphisms and metastasis. Statistical analysis was performed with Review Manager 5.0 and STATA11.0.
Thirty-three studies addressing five MMP polymorphisms were analyzed among 10,516 cancer cases (4,059 metastasis-positive cases and 6,457 metastasis-negative cases). For
Our investigations demonstrate that polymorphisms in the promoter regions of
The lethal outcome of the vast majority of cancers is due to the dissemination of metastatic tumor cells and the outgrowth of secondary tumors at distant sites. Several steps occur in cancer metastasis and invasion: dissociation of tumor cells at the primary site, local invasion, angiogenesis, intravasation into the vasculature or lymphatic systems, extravasation and proliferation at a distant site
Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases, which play critical roles in cancer progression and metastasis
MMP1 and MMP3 are two important members in MMPs family. They are neighbors located on 11q22 and play important roles in cancer development and metastasis. MMP1 is one of the widely expressed MMPs that can degrade type I, II and III collagens. MMP3 is produced by connective tissue, which can activate other MMPs and release cell surface molecules. It can degrade numerous extracellular substrates, including collagens III and IV
A variety of molecular epidemiological studies have focused on the associations between MMP polymorphisms and cancer susceptibility. Some functional single nucleotide polymorphisms, including
Electronic databases of PubMed, ISI Web of Knowledge, Medline, Embase and Google Scholar Search were used to identify all published case-control studies that evaluate the associations between MMP polymorphisms and metastasis (between January 2000 and June 2011). The Medical Subject Headings and key words used for search were “metastasis”, and (“MMPs” or “matrix metalloproteinase”) and “polymorphism” and (“cancer” or “neoplasm”). The references of all identified publications were hand-searched for additional studies. Authors were contacted directly regarding crucial data not reported in original articles. Abstracts, unpublished reports and articles written in non-English languages were not included.
The inclusion criteria were as follows: (1) independent case-control design was used to evaluate the association between MMP polymorphism and cancer in each study; (2) for each study, the score of quality evaluation was over 6 (
The exclusion criteria were as follows: (1) studies with insufficient information were excluded, for example, genotype frequency or number not reported, or histopathological diagnosis of cancer not confirmed; (2) if the same population was included in previous studies, only the most recent or complete study was included after careful examination.
To minimize the bias and improve the reliability, two researchers extracted data with the inclusion and exclusion criteria independently and reached a consensus.
Information such as the first author, publication year, country origin, cancer type, ethnicity of study population, genotyping method, number of metastasis-positive/negative cases and adjusting factors was collected from each study. For studies including subjects of different ethnicities, data were extracted separately and categorized as Asians and Europeans (Caucasians). If one study involved different cancer types, each cancer type was listed as a separate study.
According to the TNM classification standardizations, cancer patients were assigned to two subgroups named metastasis-positive and metastasis-negative based on the presence/absence of detectable lymph nodes or distant metastasis at the time of diagnosis or follow-up.
Associations between MMP polymorphisms and metastasis were evaluated by odds ratio (OR) and 95% confidence interval (CI). In addition to overall comparison, we performed stratification analysis based on cancer type (if one type contained less than two individual studies, it was combined into the ‘other cancers’ group) and ethnicity of study population. Heterogeneity between studies was assessed using
To ensure reliability and accuracy of the results, two researchers entered the data into the software program independently and reached a consensus.
By the inclusion and exclusion criteria, 195 articles were found, but only 48 studies were preliminarily identified for further evaluation. After carefully evaluating the quality of the 48 remained articles, we excluded 15 studies, of which 1 study had overlapped data and 14 studies did not report detailed genotype data or genotype frequency information for metastasis-positive/negative cases. Finally, 33 relevant studies
Information including cancer type, publication year, country, ethnicity, genotyping method, genotype data, average age of cases and controls, sample size (case/control), Hardy-Weinberg equilibrium of controls, adjusting factors, determination of cancer and metastasis positive or negative group was listed in
Gene | Cancer type | Country | Ethnicity | Metastasis(+) | Metastasis(−) | ||||||
|
AA | AB | BB |
|
AA | AB | BB | ||||
|
|||||||||||
Cao 2005 | head/neck | China | Asian | 67 | 27 |
40 | 29 | 14 |
15 | ||
Hashimoto 2004 | head/neck | Japan | Asian | 43 | 20 |
23 | 86 | 40 |
46 | ||
Kondo 2005 | head/neck | Japan/Taiwan | Asian | 40 | 6 | 34 |
43 | 4 | 39 |
||
Nasr 2007 | head/neck | Tunisia | European | 118 | 5 | 37 | 76 | 56 | 8 | 26 | 22 |
O-charoenrat 2006 | head/neck | Thailand | Asian | 181 | 75 |
106 | 119 | 76 |
43 | ||
Shimizu 2008 | head/neck | Japan | Asian | 19 | 9 |
10 | 50 | 23 |
27 | ||
Kouhkan 2008 | colorectal | Iran | European | 69 | 31 |
38 | 81 | 60 |
21 | ||
Ghilardi 2001 | colorectal | Italy | European | 17 | 6 |
11 | 43 | 31 |
12 | ||
Woo 2006 | colorectal | Korea | Asian | 79 | 2 | 23 | 54 | 106 | 5 | 31 | 70 |
Jin 2005 | gastric | China | Asian | 46 | 2 | 16 | 28 | 48 | 7 | 16 | 25 |
Matsumura 2004 | gastric | Japan | Asian | 89 | 11 | 42 | 36 | 126 | 15 | 46 | 65 |
Hughes 2007 | breast | London | European | 52 | 12 | 20 | 20 | 88 | 26 | 43 | 19 |
Przybylowska2006 | breast | Poland | European | 141 | 33 | 57 | 51 | 129 | 44 | 58 | 27 |
Fang 2005 | NSCLC |
China | Asian | 123 | 13 | 41 | 69 | 74 | 8 | 24 | 42 |
Fong 2004 | chondrosarcoma | Taiwan | Asian | 14 | 6 | 8 | 0 | 53 | 12 | 26 | 15 |
Jin 2005 | ESCC |
China | Asian | 59 | 6 | 24 | 29 | 72 | 12 | 29 | 31 |
Lai 2005 | cervical | Taiwan | Asian | 51 | 12 | 22 | 17 | 89 | 8 | 38 | 43 |
Albayrak 2007 | prostate | Turkey | European | 10 | 3 | 7 |
45 | 7 | 38 |
||
|
|||||||||||
Cotignola 2007 | melanoma | USA | European | 129 | 86 | 39 | 4 | 866 | 543 | 281 | 42 |
O-charoenrat 2006 | head/neck | Thailand | Asian | 152 | 140 | 12 |
87 | 66 | 21 |
||
Lei2007 | breast | Sweden | European | 230 | 121 | 86 | 23 | 559 | 317 | 203 | 39 |
Wu2007 | gastric | Taiwan | Asian | 93 | 83 | 7 | 3 | 118 | 88 | 26 | 4 |
|
|||||||||||
Hughes 2007 | breast | London | European | 50 | 16 | 29 | 5 | 85 | 23 | 44 | 18 |
Ghilardi 2002 | breast | Italy | European | 40 | 15 | 25 |
46 | 9 | 37 |
||
Krippl 2004 | breast | Austria | European | 216 | 59 | 103 | 54 | 259 | 43 | 146 | 70 |
Fang 2005 | NSCLC |
China | Asian | 123 | 7 | 41 | 75 | 73 | 0 | 17 | 56 |
Cotignola 2008 | melanoma | USA | European | 129 | 21 | 69 | 39 | 853 | 148 | 428 | 277 |
Tu 2007 | head/neck | Taiwan | Asian | 59 | 12 |
47 | 91 | 20 |
71 | ||
Zhang 2004 | ESCC |
China | Asian | 59 | 1 | 26 | 32 | 72 | 0 | 20 | 52 |
Zhang 2004 | GCA |
China | Asian | 46 | 2 | 11 | 33 | 48 | 1 | 12 | 35 |
Smolarz 2003 | ovarian | Poland | European | 61 | 17 | 24 | 20 | 57 | 20 | 22 | 15 |
|
|||||||||||
Hughes 2007 | breast | London | European | 49 | 17 | 20 | 12 | 81 | 30 | 39 | 12 |
Zhang 2005 | ESCC |
China | Asian | 68 | 61 | 7 |
87 | 74 | 13 |
||
Zhang 2005 | GCA |
China | Asian | 46 | 36 | 10 |
63 | 56 | 7 |
||
Zhang 2005 | NSCLC |
China | Asian | 123 | 101 | 22 |
74 | 60 | 14 |
||
Wu 2011 | cervical | China | Asian | 39 | 17 | 14 | 8 | 178 | 96 | 70 | 12 |
|
|||||||||||
Nasr 2007 | head/neck | Tunisia | European | 118 | 96 | 20 | 2 | 56 | 43 | 12 | 1 |
Woo 2006 | colorectal | Korea | Asian | 79 | 67 | 11 | 1 | 106 | 88 | 17 | 1 |
Xing 2007 | colorectal | China | Asian | 46 | 29 | 17 |
87 | 71 | 16 |
||
Hughes 2007 | breast | London | European | 43 | 35 | 8 |
76 | 74 | 2 |
||
Przybylowska2006 | breast | Poland | European | 141 | 83 | 56 | 2 | 129 | 90 | 38 | 1 |
Lei 2007 | breast | Sweden | European | 230 | 164 | 61 | 5 | 555 | 392 | 143 | 20 |
Wang 2005 | NSCLC |
China | Asian | 123 | 89 | 34 |
74 | 59 | 15 |
||
Matsumura 2005 | gastric | Japan | Asian | 63 | 44 | 16 | 3 | 114 | 89 | 22 | 3 |
Awakura 2006 | renal | Japan | Asian | 154 | 106 | 48 |
25 | 20 | 5 |
||
Park 2011 | colorectal | Korea | Asian | 132 | 107 | 24 | 1 | 201 | 163 | 37 | 1 |
represents the number of AA+AB genotype,
represents the number of BB+AB genotype (A represents the major allele, B represents the minor allele),
NSCLC represents non-small cell lung carcinoma,
ESCC represents esophageal squamous cell carcinoma.
GCA represents gastric cardiac adenocarcinoma.
Different genotyping methods were used in these studies, including the classical polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in 21 of 33 studies
Seventeen studies investigating
A random-effects model was used. The
Variables |
|
Dominant genetic model |
|
Recessive genetic model | ||||
OR(95%CI) |
|
|
OR(95%CI) |
|
|
|||
|
||||||||
Tumor site | ||||||||
head/neck | 219–20 | 1.53 |
76 | 0.04 | 517–18,20–22 | 1.88(1.39–2.53) | 48 | 0.1 |
colorectal | 125 | 1.91(0.36–10.09) | — | — | 323–25 | 2.45 |
75 | 0.02 |
gastric | 226–27 | 1.33(0.65–2.74) | 54 | 0.14 | 226–27 | 0.82(0.52–1.29) | 61 | 0.11 |
breast | 228–29 | 1.59(1.02–2.48) | 0 | 0.69 | 228–29 | 2.18(1.40–3.40) | 0 | 0.9 |
other | 526,30–32.46 | 0.89 |
62 | 0.03 | 426,30–32 | 0.81(0.56–1.17) | 47 | 0.13 |
Ethnicity | ||||||||
Asian | 719,25–27,30–32 | 0.90(0.62–1.32) | 41 | 0.1 | 1017–18,21–22,25–27,30–32 | 1.06 |
57 | 0.01 |
European | 420,28–29,46 | 1.86(1.25–2.78) | 0 | 0.42 | 520,23–24,28–29 | 2.68(1.96–3.66) | 0 | 0.68 |
Total | 11 | 1.24 |
49 | 0.03 | 15 | 1.44 |
68 | <0.0001 |
|
||||||||
Tumor site | ||||||||
All | 47,33–35 | 0.61 |
83 | 0.0005 | 333–35 | 1.17(0.75–1.83) | 8 | 0.34 |
Ethnicity | ||||||||
Asian | 27,35 | 0.31(0.18–0.54) | 0 | 0.63 | 135 | 0.95(0.21–4.35) | — | — |
European | 233–34 | 1.03(0.81–1.32) | 44 | 0.18 | 233–34 | 1.19(0.75–1.90) | 52 | 0.15 |
|
||||||||
Tumor site | ||||||||
breast | 328,36–37 | 0.56(0.39–0.79) | 0 | 0.53 | 228,37 | 0.80(0.55–1.17) | 44 | 0.18 |
other | 430,33,39–40 | 0.99(0.67–1.46) | 5 | 0.38 | 530,33,38–40 | 0.80(0.62–1.03) | 34 | 0.18 |
Ethnicity | ||||||||
Asian | 230,39 | 0.21(0.04–1.02) | 0 | 0.72 | 330,38–39 | 0.64(0.44–0.92) | 27 | 0.25 |
European | 528,33,36–37,40 | 0.76(0.58–0.99) | 52 | 0.08 | 428,33,37,40 | 0.89(0.69–1.16) | 4 | 0.37 |
Total | 7 | 0.72(0.56–0.93) | 35 | 0.15 | 7 | 0.80(0.64–0.99) | 25 | 0.23 |
|
||||||||
Total | 328,45,47 | 1.17(0.81–1.67) | 0 | 0.45 | 228,47 | 2.43(1.25–4.73) | 0 | 0.33 |
|
||||||||
Tumor site | ||||||||
colorectal | 325,41,48 | 1.07(0.81–1.38) | 43 | 0.15 | 225,48 | 1.43(0.26–10.26) | 0 | 0.95 |
breast | 328–29,34 | 1.23 |
77 | 0.01 | 229,34 | 0.70(0.29–1.70) | 0 | 0.4 |
other | 420,42–44 | 1.32(0.90–1.94) | 0 | 0.45 | 220,43 | 0.89(0.44–1.80) | 0 | 0.76 |
Ethnicity | ||||||||
Asian | 625,41–44,48 | 1.37(1.02–1.83) | 5 | 0.38 | 325,43,48 | 1.66(0.47–5.84) | 0 | 0.98 |
European | 420,28–29,34 | 1.33 |
69 | 0.02 | 320,29,34 | 0.72(0.31–1.65) | 0 | 0.68 |
Total | 10 | 1.25(1.03–1.51) | 43 | 0.07 | 6 | 0.92(0.47–1.82) | 0 | 0.85 |
Number of comparisons.
Random effect model was used.
In the stratified analysis based on ethnicity of study population, there was a strong association between metastasis and
Eight studies investigated
A fixed-effects model was used. A indicates the result under the dominant model (
In the stratified analysis by ethnicity, European individuals with genotype
Ten studies evaluated
A fixed-effects model was used. The
Four studies evaluated
A fixed-effects model was used. A indicates the result under the dominant model (
For
The results of meta-regression for
For
Genotype data of study
For
Publication bias was assessed by performing funnel plot and Egger's regression test under the dominant and recessive models. If the number of included studies was small, it is unnecessary to perform publication bias analysis. After combining all the cancer types, a little asymmetry was observed for
In our comprehensive meta-analysis,
MMP1 is implicated in cancer susceptibility and metastasis in a variety of cancers. A single nucleotide polymorphism at −1607 bp in the
The promoter region of
MMP9 is the most complex member of MMPs, which plays an important role in metastasis. The
An
Results for different MMP polymorphisms in metastasis are inconsistent, which can be explained by several reasons. First, the study population in each report comes from different areas and races. Different genetic backgrounds and environmental factors could influence the results. Second, the small sample size in some studies might influence the overall effect. It is necessary to gather studies with larger sample sizes to decrease the possibility of false positive and negative. Third, different MMP regulation mechanisms and microenvironments in different cancers may explain why MMP polymorphisms play different roles in cancer metastasis. Fourth, some cases are gynaecological cancers. The development and metastasis of gynaecological cancers could be influenced by some environmental factors and other factors including oestrogen, pregnancy and coitus.
Heterogeneity is an important problem when interpreting the results of our meta-analysis. In this study, significant heterogeneity was found in three of the five polymorphisms. For these polymorphisms, the heterogeneity disappeared after excluding several studies. Results of meta-regression demonstrate that cancer type and ethnicity of the studied population are the major source of the heterogeneity. Because the genotype data of studies
There are some limitations in our analysis. First, although we collected all the eligible studies, the sample size of the included studies was not large enough, which could increase the likehood of type I and type II errors. Therefore, there was a lack of statistical power to better evaluate the association between MMP polymorphisms and metastasis, especially in subgroup analysis. Second, we showed the results by combining all cancers, however, the results in subgroup analysis were more meaningful. We only analyzed the data based on different cancer types and ethnicity of the studied population due to the limited data. Third, gene-gene and gene-environment interactions were not analyzed. It is possible that specific environmental and lifestyle factors may alter those associations between gene polymorphisms and metastasis. Therefore, it is necessary to evaluate the roles of some special environment factors and lifestyles such as diet, alcohol consumption and smoking status in metastasis. Fourth, although the funnel plot and Egger's test did not show any publication bias, the influence of bias in the present analysis could not be completely excluded. For example, studies with positive results are more easily published than those with negative results, and only studies published in English are included. Finally, as we only focused on the associations of MMP polymorphisms with cancer metastasis in the present study, the significance was limited. To ensure the validity and reliability of the conclusions, it is important to perform a meta-analysis on the associations between metastasis positive cases vs. healthy controls and negative cases vs. healthy controls in the future study.
In conclusion, the results in our meta-analysis demonstrate that the polymorphisms of
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