A Meta-Analysis of Association Between the MMP-13 rs2252070 Promoter Polymorphism and Cancer Risk


 Background

Originally detected in breast cancer tissue, MMP-13 has been showed to be closely related to cancer development. Increasing evidence has also suggested that rs2252070, one of its SNP, can profoundly influence cancer risk by regulating the expression while the conclusion still remained controversial. Therefore, this meta-analysis was conducted to assess the carcinogenesis effect of this SNP quantitatively.

Methods

Studies about association between rs2252070 polymorphism and cancer risk by March 15, 2020 had been collected in PubMed, Web of Science, Cochrane Library and CNKI. R scripts and STATA software were applied to calculate estimates. Pooled ORs and corresponding 95% CIs were used to evaluate the strength of association.

Results

Twenty studies meeting pre-defined criteria were retrieved for the final statistical analysis, including 8,215 cancer patients and 8,480 healthy controls. The pooled estimates revealed no statistical significance for the association between this polymorphism and the risk of cancer in all 5 genetic models. Similarly, no significance had been detected in stratified analyses by region, cancer type, sample size and genotyping method.

Conclusion

The association between MMP-13 rs2252070 and carcinogenesis was not statistically significant. To elucidate this conclusion, future studies including gene-gene and gene-environment interaction are needed to verify the study results.


Statistics Analysis
Association between cancer risk and rs2252070 polymorphism were analyzed by pooling odds ratio (ORs) and corresponding 95% con dence interval (CIs) in ve genetic models including allele model (G vs A), dominant model (AG + GG vs AA), recessive model (G vs AG+AA), heterozygous model (AG vs AA) and homozygous model (GG vs AA). Cochran's Q test was performed to assess the state of heterogeneity between studies, with a signi cance level of 0.10.
Between-study heterogeneity was not considered to be signi cant when P h < 0.10, and the data would be pooled by the xed effects (Mantel-Haenszel) algorithm [14]. Otherwise, random effects (DerSimonian and Laird) model would be adopted to calculate and 95% con dence interval [15]. Galbraith plot was generated to directly nd out which studies signi cantly contribute to the overall heterogeneity [16]. Moreover, in order to explore the source of heterogeneity further, subgroup analyses were performed for cancer type (lung cancer, digestive system cancer or others), region (Asian or others), sample size (greater than 1000 or not), and method of genotyping (PCR-RFLP or others).To evaluate the potential publication bias quantitatively, Begg's test and Egger's test were both conducted and the threshold set as 0.05 [17,18]. Also, corresponding funnel plots were applied to demonstrate the degree of publication bias visually. (Studies with larger sample population and higher-quality were distributed at the bottom of funnel, whereas those with smaller sample population and lower precision were located closer to the horizontal axis). Additionally, the sensitivity analysis was carried out to make sure the stableness of our study by using the leaveone-out method. All statistical tests were performed by applying our pre-developed R script (version 3.5.2) and STATA software (version 14.2).

Characteristics of Included Studies
A total of 139 publications were preliminarily obtained by applying our searching strategy in ve databases. Twenty-two studies were remained for further examination after the duplication removal and initial screening. While performing the nal eligibility checking, we found that three ovarian cancer datasets from the Fourth People's Hospital of Hebei Medical University overlapped. According to our strategy, the two studies published earlier with smaller sample sizes were excluded, and the latest research data from December 2001 to December 2008 were retained [19].
Finally, 20 publications were quali ed for the statistical analyses, including 4 in Chinese and 16 in English   Table 1.

Main Analysis Results
As demonstrated in Table 2, all the 95% con dence interval of the combined estimates contained OR = 1, indicating no statistically signi cant association Subsequently, subgroup analyses for cancer type, origin area, genotyping method and sample size had been conducted to assess the impact of rs2252070 on cancer risk further. When strati ed by cancer types, no signi cant association had been detected in the digestive system cancer group. Similarly, it revealed no signi cance in both lung cancer group and other cancer group. Next, in the analyses based on origin area and genotyping method, the pooled results also showed that this polymorphism had no signi cant effect on cancer incidence. Finally, we assessed the associations in sample size subgroups and set cut-off at 200, 400, 500, 600, 800 and 1000 respectively. However, the effect of rs2252070 polymorphism on cancer risk was still not statistically signi cant by applying all cut-offs.

Publication Analysis and Sensitivity Analysis
In order to validate the robustness of our study, the sensitivity analysis was conducted by leave-one-out method ( Figure 3). By removing one certain study each time and re-calculating the summary statistic successively, the pooled ORs did not materially altered, showing that our results were not subject to any certain research.
In addition, when applying Begg's test for appraisal of the publication bias, no signi cance in all genetic models had been detected. While when Egger's test was used, there was signi cant publication bias in homozygous model (P = 0.030, Figure 4) and recessive model (P = 0.019, Figure 5). Asymmetric distribution was also observed in the corresponding funnel diagram. Using trim-ll method, four suppositional studies were added in homozygous model and ve were added in recessive model severally.

Discussion
Based on the key role of MMP-13 gene and the inconsistency of existing evidence, the current meta-analysis was conducted to systematically assess the relationship between rs2252070 gene polymorphism of MMP-13 and cancer susceptibility.16695 samples (including 8215 cases and 8480 controls) from 20 related datasets were analyzed. The results suggested that the association between rs2252070 polymorphism and the risk of cancer is insigni cant.
Heterogeneity plays an important role in evaluating the strength of a meta-analysis and it should be eliminated as much as possible to avoid erroneous interpretation of analysis results. For our study, signi cant between-study heterogeneity had been detected in all ve genetic models. Therefore, we performed subgroup analyses by cancer type, region, sample size and genotyping method. In subgroup analyses of cancer type, because of the diversity of included cancer types, we combined colorectal, esophageal, gastric cardia and oral cancer studies as digestive cancer subgroup. And except for lung cancer researches, the remaining ones were converged as another group. While there was still no signi cant differential cancer susceptibility between wild type and mutant type in none of the subgroups. In addition, considering that most of the included samples were from Asian area and even the same SNP can have a totally different effect among different races, we strati ed the overall population according to geological source area and the results suggested no statistical difference had been found. As for strati ed analyses based on genotyping method, no statistical signi cance in association between rs2252070 and cancer risk had been detected. Similarly, no signi cant associations were found in neither subgroup when strati ed according to sample size.
It should be noted that there were several limitations in our analysis. Firstly, only Chinese and English databases had been involved in the literature searching and screening process and this may lead the exclusion of other pertinent studies. On the other hand, most of the available studies we found were about Chinese populations, which restricted us to investigate potential biases caused by racial genetic differences. Secondly, another major limitation of the systematic review was the statistical heterogeneity between involved studies, which limited the ability to evaluate the size of the effects in a more precise way. Finally, due to data limitations, this study did not take the possible SNP-SNP and gene-gene interactions into consideration. Also, we didn't evaluate the impact of other confounding factors like alcohol or cigarette using.
In spite of the limitations mentioned above, the main superiority of high-quality meta-analysis was the methodology. No matter in the process of literature search, study screening, data extraction or result interpretation, we all adhered to the system evaluation and Meta-Analysis Guide (PRISMA) strictly [40].
Moreover, by integrating the data sets of previously published studies, the sample size of the study was expanded and possible small-sample-effect had been eliminated, which improved the statistical power greatly. Last but not least, by performing sensitivity analyses and publication bias analyses, the results of this meta-analysis were proved to be stable and reliable.

Conclusion
The results of this meta-analysis showed that there was no statistically signi cant association between MMP-13 rs2252070 and cancer susceptibility, suggesting the inappropriateness of listing this polymorphism as a biomarker for cancer risk. However, this is only a preliminary conclusion. Further designed studies with larger sample size are needed to clarify the relationship between rs2252070 polymorphism and cancer risk.

Avaliability of data and materials
Not applicable.

Competing interests
The authors declare that they have no competing interests.