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Associations between CYP1A1 rs1048943 A > G and rs4646903 T > C genetic variations and colorectal cancer risk: Proof from 26 case-control studies

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Oncotarget. 2016; 7:51365-51374. https://doi.org/10.18632/oncotarget.10331

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Xueru Zhu, Zhao Wang, Jing He, Weiye Wang, Wenji Xue, Yiwei Wang, Leizhen Zheng and Mei-Ling Zhu _

Abstract

Xueru Zhu1,*, Zhao Wang2,*, Jing He2,3, Weiye Wang4, Wenji Xue1, Yiwei Wang1, Leizhen Zheng1, Mei-Ling Zhu1

1Department of Oncology, Xin Hua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Yangpu, Shanghai, China

2Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Department of Experimental Research, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China

3Department of Pediatric Surgery, Guangzhou Institute of Pediatrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China

4Shanghai Key Laboratory of Children’s Environmental Health, Xin Hua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Yangpu, Shanghai, China

*These authors contributed equally to this work

Correspondence to:

Meiling Zhu, email: [email protected]

Leizhen Zheng, email: [email protected]

Keywords: CYP1A1, polymorphism, colorectal cancer, meta-analysis

Received: March 22, 2016     Accepted: June 03, 2016     Published: June 30, 2016

ABSTRACT

Cytochrome P450 1A1 (CYP1A1) enzyme is one of the most important metabolizing enzymes responsible for the metabolism of numerous xenobiotics. Numerous individual case-control studies have investigated the associations between the CYP1A1 rs1048943 A > G and rs4646903 T > C genetic variations and colorectal cancer (CRC) risk, but the conclusions were controversial. To obtain a scientific conclusion, we performed a meta-analysis based on a total of 26 publications, including 20 studies with 8665 cases and 9953 controls on rs1048943 A > G and 19 studies with 6416 cases and 7551 controls on rs4646903 T > C, respectively. The pooled analysis indicated that rs1048943 A > G was associated with an increased risk of CRC (G vs. A: OR = 1.28, 95% CI = 1.08−1.52; GG vs. AA: OR = 1.54, 95% CI = 1.25−1.91; GA vs. AA: OR = 1.26, 95% CI = 1.00−1.60; GG/GA vs. AA: OR = 1.31, 95% CI = 1.05−1.64; GG vs. GA/AA: OR = 1.56, 95% CI = 1.26−1.91). Stratification analysis showed the association between rs1048943 A > G and CRC risk was more obvious in studies with the population-based (PB) design or high quality score. The association between rs4646903 T > C and CRC risk did not reach statistical significance in the pooled analysis as well as stratification analysis. This meta-analysis demonstrated CYP1A1 rs1048943 A > G may increase the susceptibility to CRC instead of rs4646903 T > C. This conclusion suggested CYP1A1 may contribute to the pathogenesis of CRC.


INTRODUCTION

Although the incidence rate of CRC decreased by approximately 3% per year during the past decade, CRC is still one of the most common cancers and the third leading cause of cancer-related death worldwide [1]. Despite the fact of great improvement in chemotherapy and surgical operations, the prognosis of advanced CRC is still much worse than early-stage CRC [2]. Therefore, for cancer prevention and early diagnosis, it is important to identify risk factors and biomarkers that are associated with disease susceptibility to screen high risk population.

The development of CRC is widely considered as a multi-step, multi-factorial process involving gene-gene and gene-environment interactions [3]. Previous studies have shown that lifestyle factors, such as cigarette smoking and alcohol consumption may contribute to sporadic CRC risk [4]. In vivo, these xenobiotics (e.g. nicotine and alcohol) are metabolized by xenobiotic-metabolizing enzymes including CYP1A1 superfamily, glutathione S-transferases, N-acetyltransferase, etc [5]. Furthermore, genetic variations of these enzymes may lead to the occurrence of CRC by metabolizing environmental insults [3]. In recent years, an increasing number of individual case-control studies have investigated the association of genetic variations within cytochrome P450s (CYPs) with CRC risk.

The Human Genome Project has identified 57 human cytochrome P450 enzymes, and ordered the minto 18 families and 43 subfamilies by sequence similarities [6]. Although most chemical carcinogens are inactive in vivo, they can become bio-active via CYPs. For example, benzo[a] pyrene can be metabolized and transformed to mutagenic benzo[a] pyrene diol epoxide [7, 8]. CYPs, the key of phase I enzymes, are the main enzymes in the metabolism of carcinogenic polycyclic aromatic hydrocarbons (PAHs) [9]. Among all researches of CYP involvement in procarcinogen activation, CYP1A1s polymorphisms of rs1048943 A > G and rs4646903 T > C were the most widely studied [10]. CYP1A1 rs1048943 A > G leads to amino acid change in exon 7 of CYP1A1 from Ile to Val (nucleotides A to G) at codon 462. CYP1A1 rs4646903 T > C is characterized by the T to C mutation at nucleotide 3801 in the 3’-flanking region of the gene [11].

To date, numerous case-control studies have investigated the associations between CYP1A1 rs1048943 A > G, rs4646903 T > C and CRC, but the conclusions were inconsistent. Hence, we conducted a meta-analysis to obtain a scientific conclusion.

RESULTS

Characteristics of eligible publications

A total of 26 articles reporting the associations between CYP1A1 polymorphisms and CRC risk were included in the meta-analysis. There were 20 studies (8665 cases and 9953 controls) for rs1046943 A > G and 19 studies (6416 cases and 7551 controls) for rs4646903 T > C. The study selection process was shown in Figure 1 [5, 1135].

Flow chart of studies selection.

Figure 1: Flow chart of studies selection.

The ethnicities of the 20 publications about rs1048943 A > G, included Asian (6 studies), Caucasian (13 studies) and mixed populations (1 study). The distribution of genotype among controls fulfilled the criteria of HWE in14 studies. There were 18 studies with high quality scores. For rs4646903 T > C, the ethnicities of the 19 publications included Asian (7 studies) and Caucasian (12 studies). The distribution of genotype among controls fulfilled the criteria of HWE in 17 studies. There were 17 studies with high quality scores. The main characteristics of the 26 eligible studies were listed in Table 1.

Table 1: Characteristics of the 26 articles included in the meta-analysis

Study

Country

Ethnicity

Source

Polymorphism

Sample size

HWE

HWE

Score

of control

type

(case/control)

(cases)

(control)

Hayashi,1992

Japan

Asian

PB

rs1048943

85/358

0.114

0.332

12

Sivaraman,1994

Mixed

Caucasian

PB

rs1048943

43/47

0.227

0.230

11

 

 

 

 

rs4646903

43/47

0.001

0.245

11

Frische,1999

Germany

Caucasian

PB

rs1048943

187/101

0.622

0.839

13

 

 

 

 

rs4646903

187/101

0.496

0.563

13

Ishibe,2000

America

Caucasian

PB

rs1048943

212/221

0.018

0.057

13

 

 

 

 

rs4646903

212/221

0.247

0.428

13

Sachse,2002

Britain

Caucasian

PB

rs1048943

490/592

0.035

0.002

11

 

 

 

 

rs4646903

490/592

0.040

0.596

14

Ye,2002

Britain

Caucasian

PB

rs4646903

41/82

0.613

0.599

11

Slattery,2004

America

Caucasian

PB

rs1048943

1791/2180

0.000

0.000

12

 

 

 

 

rs4646903

1805/2164

0.080

0.118

15

Hou,2005

Mixed

Mixed

HB

rs1048943

675/679

0.117

0.478

12

Landi,2005

Spain

Caucasian

HB

rs1048943

362/323

0.617

0.469

11

 

 

 

 

rs4646903

358/305

0.717

0.793

11

Chen,2005

China

Asian

PB

rs4646903

139/340

0.978

0.821

13

Little,2006

Britain

Caucasian

PB

rs1048943

251/396

0.602

0.534

14

 

 

 

 

rs4646903

232/378

0.206

0.448

14

Bente,2006

Australia+ Poland

Caucasian

HB

rs4646903

118/100

0.039

0.637

10

Youshida,2007

Japan

Asian

PB

rs1048943

66/121

0.910

0.800

11

 

 

 

 

rs4646903

66/121

0.244

0.623

11

Yeh,2007

Taiwan,China

Asian

HB

rs1048943

717/729

0.000

0.280

12

Kiss,2007

Hungary

Caucasian

HB

rs1048943

500/500

0.172

0.315

12

Pereira, 2008

Brazil

Caucasian

PB

rs1048943

114/114

0.000

0.071

12

Pande,2008

America

Caucasian

PB

rs1048943

120/137

0.294

0.000

10

 

 

 

 

rs4646903

120/137

0.046

0.272

13

Zheng,2009

China

Asian

PB

rs1048943

79/110

0.056

0.031

8

 

 

 

 

rs4646903

79/110

0.479

0.272

11

Liu,2009

China

Asian

HB

rs4646903

75/100

0.000

0.000

6

Kobayashi,2009

Japan

Asian

HB

rs1048943

117/289

0.164

0.000

7

Nisa,2010

Japan

Asian

PB

rs1048943

685/778

0.580

0.970

14

 

 

 

 

rs4646903

685/778

0.423

0.718

14

Cleary,2010

Canada

Caucasian

PB

rs1048943

1174/1293

0.000

0.006

11

 

 

 

 

rs4646903

1174/1293

0.281

0.062

14

Houlle,2011

France

Caucasian

HB

rs1048943

329/419

0.651

0.546

11

 

 

 

 

rs4646903

329/419

0.804

0.362

11

Darazy,2011

Lebanon

Asian

PB

rs4646903

70/70

0.000

0.000

5

Saeed,2013

Saudi Arabia

Asian

HB

rs4646903

100/79

0.374

0.726

10

Gil,2014

Poland

Caucasian

HB

rs1048943

478/404

0.574

0.095

11

PB, population-based; HB, hospital-based; HWE, Hardy-Weinberg equilibrium.

Meta-analysis

CYP1A1 rs1048943 A > G polymorphism

The association between CYP1A1 rs1048943 A > G and the risk of CRC was shown in Table 2 and Figure 2. To sum up, the associations under all genetic models were statistically significant (G vs. A: OR = 1.28, 95% CI = 1.08–1.52; GG vs. AA: OR = 1.54, 95% CI = 1.25–1.91; GA vs. AA: OR = 1.26,95% CI = 1.00–1.60; GG/GA vs. AA: OR = 1.31, 95% CI = 1.05–1.64; GG vs. GA/AA: OR = 1.56, 95% CI = 1.26-1.91) (Supplementary Figure 1). Further stratified analysis showed the association was especially obvious in studies with population-based (PB) designs and of high quality scores. In studies of PB designs, the association was more obvious in the homozygous model (GG vs. AA: OR = 1.61, 95% CI = 1.03–2.53). In studies of high quality score, the association was more obvious using recessive model (GG vs. GA/AA: OR = 1.45, 95% CI = 1.16–1.82). Stratification analysis by ethnicity showed the association of rs1048943 A > G and CRC were more obvious in homozygous (GG vs. AA: OR = 1.61, 95% CI = 1.04–2.47) and recessive (GG vs. GA/AA: OR = 1.59, 95% CI = 1.25-2.02) models in Asian. In Caucasian, the associations were obvious in dominant model (GA/GG vs. AA: OR=1.43, 95% CI = 1.05–1.95), heterozygous model (GA vs. AA: OR = 1.42, 95% CI = 1.04–1.96) and G allelic (G vs. A: OR = 1.33, 95% CI = 1.06–1.68). After excluding studies whose distribution of genotype in controls deviated from HWE, the association remained statistically significant (G vs. A: OR = 1.30, 95% CI = 1.05–1.61; GG vs. AA: OR = 1.51, 95% CI = 1.17–1.94; GG/GA vs. AA: OR = 1.35, 95% CI = 1.01–1.81; GG vs. GA/AA: OR = 1.52, 95% CI = 1.19–1.95). All of the results were listed in Table 2.

Table 2: Meta-analysis of the association between CYP1A1 polymorphisms and CRC risk

aP value of the Z-test for odds ratio test; bP value of the Q-test for heterogeneity test; PB, population based; HB, hospital based; HWE, Hardy-Weinberg equilibrium.

Forest plot of colorectal cancer risk associated with CYP1A1 rs1048943 A>G polymorphism (G vs. A).

Figure 2: Forest plot of colorectal cancer risk associated with CYP1A1 rs1048943 A>G polymorphism (G vs. A).

CYP1A1 rs4646903 T > C polymorphism

In the meta-analysis, the pooled analysis showed no significant association between rs4646903 T > C and CRC risk. Further stratification analyses also found no obvious association except the subgroups of deviating from HWE and low quality score which included the same two studies showed statistical significances (C vs. T: OR = 1.85, 95% CI = 1.19–2.87; CC vs. TT: OR = 2.24, 95% CI = 1.04–4.80; CT/CC vs. TT: OR = 1.88, 95% CI = 1.06–3.35) (Table 2).

Heterogeneity and sensitivity analysis

The Chi-squared-based Q-test showed substantial heterogeneities among publications for the two polymorphisms (Table 2). Meta-regression analysis for both polymorphisms yielded no significant difference between subgroups, except subgroups of HWE and study quality score for rs464903 T > C. After excluding the inferior quality studies of deviate from HWE and low score, the conclusions of both polymorphisms were not change. Furthermore, we estimated the influence of single individual data on the combined ORs by consecutively omitting each study from the meta-analysis, no obvious differences were observed for both variations (Supplementary Figure 2).

Publication bias

For rs1048943 A > G, the shapes of funnel plots were symmetric (Figure 3) and Egger’s linear regression test provided no evidence of publication bias (G vs. A: P = 0.185, t = 1.38; GG vs. AA: P = 0.325, t = 1.01; GA vs. AA: P = 0.132, t = 1.58; GG/GA vs. AA: P = 0.116, t = 1.65; GG vs. GA/AA: P = 0.587, t = 0.56). For rs4646903 T > C the funnel plots were also symmetric and Egger’s linear regression test provided no evidence of publication bias (CC vs. TT: P = 0.174, t = 1.42; CT vs. TT: P = 0.056, t = 2.05; CC vs. CT/TT: P = 0.234, t = 1.24), except two models of G allelic (C vs. T: P = 0.005, t = 3.27) and dominant model (CT/CC vs. TT: P = 0.013, t = 2.78).

Begg’s funnel plot of colorectal cancer risk associated with CYP1A1 rs1048943 A >G polymorphism (G vs. A).

Figure 3: Begg’s funnel plot of colorectal cancer risk associated with CYP1A1 rs1048943 A >G polymorphism (G vs. A).

DISCUSSION

In this meta-analyses, we comprehensively evaluated the associations between two polymorphisms (rs1048943 A > G and rs4646903 T > C) and CRC risk through 26 studies. We observed that rs1048943 A > G genetic variation was associated with increased risk of CRC. The association remained statistically significant in subgroups (Asians, Caucasians, PB, high quality score and the studies consistent with HWE). On the contrary, the association between rs4646903 T > C and CRC risk did not reach the significance level.

CYP1A1 protein is a member of CYP superfamily and widely distributes in lung, kidney, intestine, skin, larynx, placenta, lymphocyte, brain tissues [36]. Because the main role of this enzyme is to metabolize environmental carcinogens, such as PAHs, heterocyclic amines, aflatoxin B1 and estrogen [37], variations within CYP1A1 gene may induce the occurrence of CRC. Currently, a widely accepted paradigm for CYP1A1 enzyme mediated carcinogens activation is that CYP1A1 metabolizes polycyclic aromatic hydrocarbons to reactive epoxide intermediates, which could covalently bind to DNA and then induce tumors [38].

Due to the high minor allele frequency (MAF) as well as their possible involvement in an increased risk of several carcinomas [39], including lung cancer, colorectal cancer, breast cancer, leukemia, esophageal carcinoma and prostate cancer [40], CYP1A1 rs1048943 A > G and rs4646903 T > C polymorphisms are more widely studied. In addition to inducing the occurrence of cancers, the polymorphisms of CYP1A1 may also lead to other diseases, such as ulcerative colitis, colorectal adenoma, atherosclerosis, myocardial infarction and so on [4143].

Partial meta-analyses on the association of CYP1A1 polymorphisms and colorectal cancer risk showed that CYP1A1 rs1048943 A > G might be associated with increased risk of CRC [44, 45]. In the present study, we combined the studies to increase sample size and further validated this results. However, contradictory results were observed in a previous meta-analysis which concluded that there was no association between rs1048943 A > G and CRC risk [46]. This discrepancy mainly results from sample size. We analyzed 20 studies with 8665 cases and 9953 controls while they only included two studies with 238 cases and 280 controls. For rs4646903 T > C, previous studies showed no association with CRC risk which was consistent with us.

Compared to previous meta-analyses, the present analysis has some advantages. Firstly, we have the largest sample size with the statistic power of 92% to evaluate the associations. Secondly, 90% studies included in our meta-analyses were of high quality score. Thirdly, we conducted sensitivity analysis and found no obvious influence of a single study on the pooled ORs and 95% CIs for rs1048943 A > G. In addition, negative result of publication bias evaluation indicated that our conclusions were unbiased. However, between-study heterogeneity existed, we should draw the conclusion with caution, subgroups analysis of rs1048943 A > G indicated that heterogeneities may be from ethnicity, source of control or controls deviated from HWE. For rs4646903 T > C polymorphism, substantial between-study heterogeneities may originate from ethnicity, source of control and controls deviated from HWE. Besides, for unavailable original data, we failed to analyze clinical features, such as tumor stage, age and sex, etc.

In conclusion, CYP1A1 rs1048943 A > G polymorphism may increase the CRC risk. However, our study still existed in some limitations, further studies with higher quality and larger sample size are necessary.

MATERIALS AND METHODS

Search strategy

We searched publications from PubMed, Web of knowledge, Embase and Chinese database of China National Knowledge Infrastructure (CNKI) and VIP database with the following search items: “CYP1A1” or “Cytochrome P450 1A1” and “polymorphism” or “variant” or “SNP” and “colorectal cancer” or “colon cancer” or “rectal cancer”. The languages were limited to English and Chinese. We updated the search results on January 2016 and confirmed potential relevant studies through the titles and abstracts.

Selection criteria

All studies included in the meta-analysis are selected according to the following criteria: (a) case-control studies; (b) studies about the associations between CYP1A1 rs1048943 A > G or rs4646903 T > C and colorectal cancer; (c) studies that contain genotype data; (d) when studies had overlapping populations, the most recent ones with the most complete data set were included. In addition, exclusion criteria were as follows: (a) overlapped articles or studies with overlapping data; (b) review articles, conference reports and dissertations.

Data extraction

Two investigators (ZXR and ZML) extracted data independently from the eligible studies with the following items: the first author’s last name, year of publication, country, ethnicity, source of controls, polymorphism type, number of cases and controls, the frequency of each genotype in cases and controls (Supplementary Table 3), minor allele frequency (MAF) and p-value of Hardy Weinberg equilibrium (HWE). To get the accurate data, two investigators discussed together to reach a consensus.

Quality assessment

We evaluated the quality of the included studies respectively, according to the quality assessment criteria (Supplementary Table 1) [4750]. The range of quality scores are from 0 (worst) to 15 (best). Publications with quality scores < 10 were categorized as “low quality” and those with quality scores ≥ 10 were categorized as “high quality” [51]. The process of scoring was listed in Supplementary Table 2.

Statistical analysis

Stata software (version 12.0; Stata Corporation, College Station, TX) was used to perform statistical analyses. We used allelic, heterozygote, homozygote, dominant and recessive as the models. The strength of associations between the CYP1A1 rs1048943 A > G and rs4646903 T > C and the risk of colorectal cancer were evaluated by the pooled odds ratios (ORs) and 95% confidence intervals (CIs). We set the significance cutoff as a p-value of 0.05 for the pooled OR. Between-study heterogeneity was assessed using Chi-squared-based Q-test. If heterogeneity P value was lower than 0.10 ,we considered the heterogeneity to be significant and random-effects model was used [52]. Otherwise, the fixed effects model was used [53]. We also performed stratified analyses by ethnicity (Asian and Caucasian), control source (population-based and hospital-based), quality score of studies (low and high) and HWE. Sensitivity analyses were performed to measure the stability of the results by consecutively omitting each study from the meta-analysis (leave-one-out sensitivity analysis). Begg’s funnel plot [54] and Egger’s test [55] (P <0.05 was considered significant) were used to evaluate the publication bias among the literatures.

CONFLICTS OF INTEREST

The authors have declared that no competing interests exist.

FUNDING

This study was supported by funding from the Science and Technology Commission of Shanghai Municipality, China (Grant No.15ZR1427700) and Xin Hua Hospital affiliated to Shanghai Jiaotong University School of Medicine, China (Grant No.13YJ22).

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