The SULT1A1 Arg213His (rs9282861) polymorphism is reported to be associated with many kinds of cancer risk. However, the findings are conflicting. For better understanding this SNP site and cancer risk, we summarized available data and performed this meta-analysis.
Data were collected from the following electronic databases: PubMed, Web of Knowledge and CNKI. The association was assessed by odd ratio (OR) and the corresponding 95% confidence interval (95% CI).
A total of 53 studies including 16733 cancer patients and 23334 controls based on the search criteria were analyzed. Overall, we found SULT1A1 Arg213His polymorphism can increase cancer risk under heterozygous (OR = 1.09, 95% CI = 1.01–1.18, P = 0.040), dominant (OR = 1.10, 95% CI = 1.01–1.19, P = 0.021) and allelic (OR = 1.08, 95% CI = 1.02–1.16, P = 0.015) models. In subgroup analyses, significant associations were observed in upper aero digestive tract (UADT) cancer (heterozygous model: OR = 1.62, 95% CI = 1.11–2.35, P = 0.012; dominant model: OR = 1.63, 95% CI = 1.13–2.35, P = 0.009; allelic model: OR = 1.52, 95% CI = 1.10–2.11, P = 0.012) and Indians (recessive model: OR = 1.93, 95% CI = 1.22–3.07, P = 0.005) subgroups. Hospital based study also showed marginally significant association. In the breast cancer subgroup, ethnicity and publication year revealed by meta-regression analysis and one study found by sensitivity analysis were the main sources of heterogeneity. The association between SULT1A1 Arg213His and breast cancer risk was not significant. No publication bias was detected.
The present meta-analysis suggests that SULT1A1 Arg213His polymorphism plays an important role in carcinogenesis, which may be a genetic factor affecting individual susceptibility to UADT cancer. SULT1A1 Arg213His didn't show any association with breast cancer, but the possible risk in Asian population needs further investigation.
Citation: Xiao J, Zheng Y, Zhou Y, Zhang P, Wang J, Shen F, et al. (2014) Sulfotransferase SULT1A1 Arg213His Polymorphism with Cancer Risk: A Meta-Analysis of 53 Case-Control Studies. PLoS ONE 9(9): e106774. https://doi.org/10.1371/journal.pone.0106774
Editor: Qing-Yi Wei, Duke Cancer Institute, United States of America
Received: March 10, 2014; Accepted: July 30, 2014; Published: September 16, 2014
Copyright: © 2014 Xiao et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All data are included within the paper and its Supporting Information files.
Funding: This work was supported by the grants from the National Natural Science Foundation of China (Grant numbers 81071957 and 81000938), (http://www.nsfc.gov.cn/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Sulfotransferase (SULT) enzymes catalyze the sulfate conjugation of a broad range of substrates and play an important role in metabolism of endogenous and exogenous compounds including thyroid and steroid hormones, neurotransmitters, drugs and procarcinogens , . There are many isoforms of the SULTs supergene family, each with different amino acid sequence identity and substrate specificity . SULT1A1 is an important member of the sulfotransferase family involving in the pathogenic process of various cancers –.
The SULT1A1 gene is located on chromosome 16p12.1–p11.2 . Previous study indicated that exon 7 of the SULT1A1 gene contained a G to A transition at codon 213 (rs9282861) that causes an Arg to His amino acid substitution . Some studies have shown that this genetic polymorphism leads to a decrease in enzymatic activity of SULT1A1 and the sulfonation efficiency thus associating with susceptibility to several cancers , . Although the specific role of SULT1A1 Arg213His polymorphism in carcinogenesis has been investigated in numerous case-control studies, the results have been inconclusive, even conflictive. In order to give a comprehensive and precise result, we performed this meta-analysis study to analyze the association between this polymorphism and cancer risk.
Materials and Methods
Identification of eligible studies
The meta-analysis was conducted following the criteria of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Checklist S1). In this study, we did an exhaustive literature search on studies that examined the association of the SULT1A1 gene polymorphisms with cancer risks. All eligible studies were identified by searching the following databases: PubMed, Web of Knowledge and China National Knowledge Infrastructure (CNKI, http://www.cnki.net/). The following terms were utilized: “sulfotransferase, SULT or SULT1A1”, “polymorphism, variation, variant or mutation” and “cancer or carcinoma”. In the CNKI database, we searched with these corresponding key words in Chinese characters. Included studies should meet the following criteria: (1) evaluating the association between SULT1A1 Arg213His polymorphism and cancer risk; (2) study designed as case-control; (3) sufficient data available to estimate an odd ratio (OR) with its 95% confidence interval (95% CI).
Two investigators extracted data independently and reached consensus on the following characteristics of the selected studies: first author's name, the year of publication, ethnicity of the study population, matching criteria, number of participants, genotype distribution and control source.
Hardy-Weinberg equilibrium was assessed by Chi-square test. Crude odd ratio (OR) and 95% confidence interval (CI) were used to estimate the association between SULT1A1 polymorphism and cancer susceptibility under the dominant model (Arg/His+His/His vs. Arg/Arg), recessive model (His/His vs. Arg/Arg+Arg/His), homozygous model (His/His vs. Arg/Arg), heterozygous model (His/Arg vs. Arg/Arg) and allelic model (His vs. Arg). The heterogeneity among the studies was evaluated by Q-test and I2 value ranging from 0% to 100% to describe the percentage of between-study variation caused by heterogeneity. P value for the Q-test less than 0.10 indicates existing heterogeneity among studies. And then the pooled OR was measured by a random effect model (the DerSimonian-Laird method). Otherwise, a fixed effect model (the Mantel-Haenszel method) was chosen.
Subgroup analyses were performed according to cancer type (breast cancer, colorectal cancer, urothelial cancer, prostate cancer, lung cancer, upper aero digestive tract (UADT) cancer, ovarian cancer and gastric cancer), ethnicity (Caucasian, East Asian, Indian and African) and source of controls (hospital based and population based). When heterogeneity was detected, a multivariable meta-regression analysis including cancer type, ethnicity, control source and year of publication to explore potential source of heterogeneity and sensitivity analysis were performed.
The potential publication bias was estimated using Egger's linear regression test by visual inspection of the funnel plot. P<0.05 was considered statistically significant, and all P values were two-sided. Analyses were performed using the software Review Manager 5.3 (Cochrane Collaboration), R software (www.r-project.org) and STATA 12.0 software (StataCrop).
Characteristics of eligible studies
The flow diagram of literature search was given in Figure 1. A total of 91 studies focusing the association between the SULT1A1 Arg213His polymorphism and cancer risks were identified. 25 of them were ruled out because of unavailable data or repeated data. Thus, the allele and genotype frequencies of the SULT1A1 Arg213His polymorphism were extracted from 66 articles. However, 18 articles didn't meet with Hardy-Weinberg equilibrium and were abandoned (Excluded list S1). As a result, 53 studies of 48 articles, involving 16733 cases and 23334 controls were included in the pooled analyses –.
The characteristics of studies included in the current meta-analysis are shown in Table 1. Among these studies, 13 were conducted for breast cancer, 10 for colorectal cancer, 7 for urothelial cancer, 5 for prostate cancer, 5 for lung cancer, 5 for UADT (upper aero digestive tract) cancer, 3 for ovarian cancer, 2 for gastric cancer and 1 for myeloid leukemia, multiple myeloma, and endometrial cancer, respectively. By ethnics, there were 27 studies of Caucasians, 11 studies of East Asians, 4 studies of Indians, 2 studies of Africans and 9 studies of mixed ethnics. By source of controls, 16 studies were population-based, 17 studies were hospital-based and 20 studies were not clear.
Table 2 showed the results of overall analysis and the subgroup analysis. The analyses on the full data set indicated a significant association of the SULT1A1 Arg213His polymorphism with cancer risk: heterozygous (OR = 1.09, 95% CI = 1.01–1.19, P = 0.035), homozygous (OR = 1.20, 95% CI = 1.04–1.39, P = 0.014), dominant (OR = 1.12, 95% CI = 1.03–1.22, P = 0.008) (Figure S1), recessive (OR = 1.16, 95% CI = 1.02–1.32, P = 0.027) and allelic model (OR = 1.11, 95% CI = 1.04–1.20, P = 0.003), with high heterogeneity among studies (I2 = 63.1%, 62.6%, 68.5%, 58.3% and 73.7%, respectively, all P<0.001)(Table 3).
We analyzed the association in cancer type subgroup. SULT1A1 Arg213His polymorphism can increase cancer risks in the following cancer types: breast cancer (homozygous model: OR = 1.37, 95% CI = 1.01–1.87, P = 0.045; dominant model: OR = 1.18, 95% CI = 1.00–1.40, P = 0.050 and allelic model: OR = 1.15, 95% CI = 1.00–1.32, P = 0.044); UADT cancer (heterozygous model: OR = 1.62, 95% CI = 1.11–2.35, P = 0.012; dominant model: OR = 1.63, 95% CI = 1.13–2.35, P = 0.009 and allelic model: OR = 1.52, 95% CI = 1.10–2.11, P = 0.012). Forest plots of breast cancer risk and UADT cancer risk were shown in Figure 2 and Figure 3 separately.
Analyzed by ethnicity, a moderately increased risk was observed in Caucasians (homozygous model: OR = 1.20, 95% CI = 1.01–1.43, P = 0.035 and allelic model: OR = 1.10, 95% CI = 1.01–1.19, P = 0.019) and Indians (recessive model: OR = 1.93, 95% CI = 1.22–3.07, P = 0.005). No significant association was found in other ethnicities in any model.
By control source, significant association was observed in hospital based study, but not the population based study.
To find potential source of heterogeneity, multivariable meta-regression analyses were conducted in total group and subgroups including cancer type, ethnicity, control source and publication year. In the breast cancer subgroup, ethnicity (heterozygous model, P = 0.027; recessive model, P = 0.020) and publication year (heterozygous model, P = 0.019; recessive model, P = 0.012) are significant sources of heterogeneity (Table S1). Other variables don't affect heterogeneity.
The sensitivity analysis was constructed by repeating the meta-analysis sequentially removing each study. In the recessive model, two studies ,  were found to affect the pooled OR and the heterogeneity when removed. The study conducted by Khvostova was focused on breast cancer and Sun's study was focused on colorectal cancer among Caucasians, so further sensitivity analyses were conducted in total data set and breast cancer, colorectal cancer and Caucasian subgroups after removing the two studies (Table 4 and Table S2). In total group, the heterogeneity was significantly decreased (I2 = 58.2, 42.2, 63.5, 33.1 and 66.4, respectively). In the subgroup sensitivity analyses, removing the two studies can significantly decrease the heterogeneity among studies, most I2 values less than 50%. And this polymorphism didn't show any obvious correlation with breast cancer risk (Figure 4). At last, we conducted the sensitivity analyses on the remaining studies and the result was stable.
Funnel plots and Egger's test were carried out to assess publication bias. The shapes of funnel plots indicated no obvious asymmetry (Figure 5). Egger's test found no publication bias in the heterozygous (P = 0.074); homozygous (P = 0.146); dominant (P = 0.076); recessive (P = 0.282) and allelic model (P = 0.081).
(A) heterozygous model (B) homozygous model (C) dominant model (D) recessive model The horizontal line in the funnel plot indicates the fixed-effects summary estimate, whereas the sloping lines indicate the expected 95% confidence intervals for a given SE.
SULT1A1 enzyme encoded by SULT1A1 gene plays an important role in xenobiotic metabolism. The Arg213His polymorphism, the most widely studied polymorphism within SULT1A1 gene, can reduce enzyme activity and thermostability, and consequently results in an individual's susceptibility to cancer , .
There have been a few meta-analyses focusing on this mutation and cancer risk –. However, most of these analyses were conducted before the year 2012 and a new meta-analysis is needed to give a comprehensive conclusion due to the increasing data of case-control studies.
This present meta-analysis, including 16733 cases and 23334 controls from 53 case-control studies, explored the association between the SULT1A1 Arg213His polymorphism and cancer risk. This is the largest scale meta-analysis so far. Our results suggested that the SULT1A1 Arg213His was associated with UADT cancer risk. As the upper aero digestive tract is exposed to numerous potential carcinogens such as phenolic xenobiotics, polycyclic aromatic hydrocarbons and heterocyclic aromatic amines contained in cigarette smoking, environmental pollutants and some food, this result manifests that the mutation within SULT1A1 causes the low SULT1A1 activity and is associated with high susceptibility to cancers related with environment.
In the sensitivity analyses, the study conducted by Khvostova influences the pooled estimates and the heterogeneity most in breast cancer subgroup. And after removing this study, the significant association between SULT1A1 Arg213His and breast cancer risk became null (Figure 2 and Figure 4). We further checked data from Khvostova and observed the percentage of wild homozygous genotype in Khvostova's study was obviously lower than that in other studies thus causing great heterogeneity. At last a robust result was achieved and failed to reveal significant association in breast cancer subgroup. This result is similar to Wang, Lee and Jiang –, but they found a positive association of this polymorphism with breast cancer susceptibility among Asians. While in our meta-analysis, we only recruited one paper focused on breast cancer among Asians because other papers on Asians deviate from HWE and were excluded. This is a limitation of this meta-analysis and more independent case-control studies conducted on Asians are needed to conclude a more comprehensive result.
In the ethnic subgroup analysis, we found that the genotype distributions of the SNP site are different in ethnic groups. When calculating the percentage of alleles in every ethnic, we found that His allele in Asians (9.58%) is significantly less than in Caucasians (35.2%). Different ethnicities may have different genetic backgrounds, thus causing different genotype frequencies in Asian and other ethnic groups which may influence cancer susceptibility.
Li and Kotnis have conducted meta-analyses focused on environment-related cancers, such as tobacco-related cancers and found cancer risk could be modulated by interaction between genetic variants and environmental factors , . As exposed environmental factors are different according to cancer types, for example smoking leads to lung cancer, while the intake of meat influences breast cancer and colorectal cancer ,  and our analysis took many kinds of cancer into account, we decided not to include environmental factors. Moreover, the definitions of exposed environmental factors were not consistent in the studies, which could cause great heterogeneity. Our estimates were based on crude OR values, not adjusted OR values, which may yield inaccurate calculation.
There were several sources bringing in heterogeneity, such as study design, age and sex distribution, and ethnicity. Meta-regression analysis was conducted to find source of heterogeneity. In the breast cancer subgroup, publication year could cause great heterogeneity and further attention was paid to years. We found all the recruited studies were carried out before 2005 or after 2010, and there were no studies between 2006 and 2009. The His allele was 29.6% in the studies before 2005 and 33.0% after 2010, which was significantly different (P = 0.02). This may be caused by the different study population, and needs more case-control studies to illustrate.
In conclusion, our meta-analysis suggests that the SULT1A1 Arg213His polymorphism may contribute UADT cancer risk. As the result was calculated through sampling statics and statistical difference is not the same as clinical difference, the result can be used for clinical reference, not for clinical diagnosis of cancer. Further detailed investigation with larger number of worldwide participants is needed to clarify the role of this polymorphism in cancer risk.
Forest plot on the association between SULT1A1 Arg213His polymorphism and overall cancer risk in dominant model.
The P-value of meta-regression in overall and breast cancer groups.
Heterogeneity test after omitting studies of Khvostova and Sun.
PRISMA 2009 Checklist.
Excluded studies list with reasons.
Conceived and designed the experiments: XLY MHW WPW. Performed the experiments: JJX YBZ YHZ PZ. Analyzed the data: YBZ LXF. Contributed reagents/materials/analysis tools: JJX JGW FYS. Wrote the paper: JJX YBZ VKK.
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