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Research Papers:

Association between 8q24 (rs13281615 and rs6983267) polymorphism and breast cancer susceptibility: a meta-analysis involving 117,355 subjects

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Oncotarget. 2016; 7:68002-68011. https://doi.org/10.18632/oncotarget.12009

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Yafei Zhang, Xianling Zeng, Hongwei Lu, Hong Ji, Enfa Zhao, Yiming Li _

Abstract

Yafei Zhang1, Xianling Zeng2, Hongwei Lu1, Hong Ji1, Enfa Zhao3 and Yiming Li1

1 Department of General Surgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

2 Department of Obstetrics and Gynecology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

3 Department of Ultrasound, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

Correspondence to:

Yiming Li, email:

Keywords: breast cancer, 8q24, rs13281615, rs6983267, meta-analysis

Received: September 24, 2015 Accepted: August 27, 2016 Published: September 13, 2016

Abstract

Published data on the association between 8q24 polymorphism and breast cancer (BC) risk are inconclusive. Thus, we conducted a meta-analysis to evaluate the relationship between 8q24 (rs13281615 and rs6983267) polymorphism and BC risk. We searched PubMed, EMBASE, Web of Science and the Cochrane Library up to August 13, 2015 for relevant studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the strength of associations. Twenty-six studies published from 2008 to 2014, with a total of 52,683 cases and 64,672 controls, were included in this meta-analysis. The pooled results showed that there was significant association between 8q24 rs13281615 polymorphism and BC risk in any genetic model. In the subgroup analysis by ethnicity, the effects remained in Asians and Caucasians. However, no genetic models reached statistical association in Africans. There was no association in any genetic model in rs6983267. This meta-analysis suggests that 8q24 rs13281615 polymorphism is a risk factor for susceptibility to BC in Asians, Caucasians and in overall population, While, there was no association in Africans. The rs6983267 polymorphism has no association with BC risk in any genetic model. Further large scale multicenter epidemiological studies are warranted to confirm this finding.


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INTRODUCTION

Breast cancer (BC), one of the most frequently encountered malignant tumors in women, has become the main reason of tumor-associated death in our word [1], whose incidence rate is increasing year by year and accompanied by younger trend in the world [2, 3]. The etiology of BC is very complex, many factors cause it’s occurrence and development, the specific mechanism has not been clarified. Epidemiology and basic etiology studies have shown that BC’s occurrence and progression is closely related to multiple factors interaction between genetic, endocrine and external environment [4-6].

The genetic markers of BC are mainly expressed in two forms, that is, the higher external rate mutation gene and the lower external rate polymorphism gene. Compared with familial BC, most sporadic BC is associated with lower external rate polymorphism genes [7, 8]. The distribution of these genes in the population is more than 1%, and the genetic variation of these genes (Single nucleotide polymorphism, SNP) is mainly by changing the expression level and function of the protein and the modified factor inside and outside the cell, thus affecting the genetic susceptibility of BC [8]. In recent years, many BC-associated gene loci have been demonstrated by GWAS, 8q24 (rs13281615 and rs6983267) is the gene mutation site selected by this technique [7].

Previous functional studies have reported the association between 8q24 (rs13281615 and rs6983267) polymorphism and BC risk [9-29]. Because of differences in race and region, studies of this site are not entirely consistent with the conclusion that whether the site is associated with the risk of BC. To clarify the role of 8q24 (rs13281615 and rs6983267) polymorphism in BC risk, five meta-analysis [30-34] on the associations between 8q24 (rs13281615 and rs6983267) polymorphism and BC had been carried out. However, the results remain inconclusive and number of their studies included in their meta-analysis about BC is small. In the subgroup of their analyses the sample size is extremely small, and some just no subgroup. Therefore, we decided to carry out this meta-analysis on all the included case-control researches to make a more accurate assessment of the relationship. Moreover, we performed a subgroup analysis stratified by ethnicity.

RESULTS

Characteristics of included papers

The specific search process is shown in Figure 1. A total of 447 references were preliminarily identified at first based on our selection strategy. We also identified 2 papers [11, 29] through other source. 347 records left after removing repeated studies. We refer to titles or abstracts of all the included literatures, and then removed obviously irrelevant papers. In the end, the whole of the rest of the papers were checked based on the inclusion and exclusion criteria. Finally, 21 studies [9-29] on 8q24 (rs13281615 and rs6983267) polymorphism and the occurrence of BC were eventually included in our study, including 52,683 cases and 64,672 controls. Characteristics of eligible analysis are shown in Table 1. The 21 case-control papers were published between 2008 and 2014, among them, 1 study was performed in African, 7 in Asian, 12 in Caucasians and 1 in both African and Caucasians. All studies were case-controlled.

Table 1: Characteristics of the studies included in the meta-analysis

First author

Year

Country

Ethnicity

Source of controls

Number(case/control)

HWE

rs13281615

Antoniou[9]

2009

Mixed

Caucasians

Nested

7787/6662

0.100

Bai[10]

2014

China

Asian

PB

280/287

0.086

Barnholtz-Sloan[11]

2010

United States

Caucasians

PB

1223/1117

0.220

Barnholtz-Sloan[11]

2010

United States

African

PB

736/658

0.580

Campa[12]

2011

USA and Europe

Caucasians

PB

8302/11615

0.106

Chan[13]

2012

Singapore

Asian

PB

1174/1463

0.047

Elematore[14]

2014

Chile

Caucasians

PB

347/801

0.993

Fletcher[15]

2008

United Kingdom

Caucasians

PB

1470/1341

0.366

Garcia-Closas[16]

2008

Mixed

Caucasians

Nested

15084 /22105

0.672

Gorodnova[17]

2010

Russian

Caucasians

PB

140/174

0.710

Harlid[18]

2012

European

Caucasians

PB

3545/5007

0.045

Jiang[19]

2011

China

Asian

PB

493/510

1.000

Latif[20]

2010

British

Caucasians

HB

919/343

0.639

Li[29]

2011

China

Asian

HB

558/635

0.748

Long[21]

2010

China

Asian

PB

2945/2981

0.985

McInerney[22]

2009

Ireland

Caucasians

PB

917/993

0.096

Mizoo[23]

2012

Japan

Asian

PB

466/458

0.252

Shan[24]

2012

Tunisia

African

PB

639/365

0.497

Tamimi[25]

2010

Sweden

Caucasians

PB

661/711

<0.001

Teraoka[26]

2011

Denmark and USA

Caucasians

PB

606/1194

0.041

Zhang[28]

2014

China

Asian

HB

482/527

0.089

rs6983267

Fletcher[15]

2008

United Kingdom

Caucasians

PB

1480/1336

0.453

McInerney[22]

2009

Ireland

Caucasians

PB

945/957

0.349

Wokolorczyk[27]

2008

Canada

Caucasians

PB

1006/1910

0.266

Zhang[28]

2014

China

Asian

HB

478/522

0.046

HWE: Hardy-Weinberg equilibrium; PB: population based; HB: hospital-based; SNP: single nucleotide polymorphism.

Flow chart of studies selection in this meta-analysis.

Figure 1: Flow chart of studies selection in this meta-analysis.

Meta-analysis results

Table 2 and Table 3 shows the 8q24 (rs13281615 and rs6983267) polymorphisms genotype distribution and allele frequencies in in case group and control group. Main results of our study were shown in Table 4. A total of 21 studies with 52,683 cases and 64,672 controls were included. As shown in Table 4, The pooled results indicated that the correlation between 8q24 rs13281615 polymorphism and the occurrence of BC was significant in any genetic model: Allele model (OR = 1.10, 95% CI = 1.07-1.13, P < 0.00001), dominant model (OR = 1.13, 95% CI = 1.08-1.18, P < 0.00001) recessive model (OR = 1.13, 95% CI = 1.08-1.18, P < 0.00001) homozygous genetic model (OR = 1.20, 95% CI = 1.13-1.27, P < 0.00001) heterozygote comparison (OR = 1.09, 95% CI = 1.06-1.12, P < 0.00001).

The subgroup study stratified by ethnicity showed an increased BC risk in Asians (Allele model: OR = 1.08, 95% CI = 1.03-1.14, P = 0.001; dominant model: OR = 1.11, 95% CI = 1.03-1.21, P = 0.009; recessive model: OR = 1.11, 95% CI = 1.03-1.20, P = 0.008; homozygous genetic model: OR = 1.17, 95% CI = 1.07-1.29, P = 0.001; heterozygote comparison: OR = 1.08, 95% CI = 1.00-1.18, P = 0.06) and Caucasians (Allele model: OR = 1.11, 95% CI = 1.06-1.16, P < 0.00001; dominant model: OR = 1.14, 95% CI = 1.07-1.21, P < 0.0001; recessive model: OR = 1.15, 95% CI = 1.08-1.22, P < 0.00001; homozygous genetic model: OR = 1.22, 95% CI = 1.12-1.32, P < 0.00001; heterozygote comparison: OR = 1.11, 95% CI = 1.05-1.17, P = 0.0005). While, there was not any genetic model attained statistical correlation in Africans. There was no association in any genetic model in rs6983267 (Table 4).

Table 2: rs13281615 polymorphisms genotype distribution and allele frequency in cases and controls

First author

Genotype (N)

Allele frequency (N)

Case

Control

Case

Control

Total

GG

AG

AA

Total

GG

AG

AA

G

A

G

A

Antoniou

7787

1396

3872

2519

6662

1158

3317

2187

6664

8910

5633

7691

Bai

280

63

152

65

287

62

158

67

278

282

282

292

Barnholtz-Sloan

1223

230

604

389

1117

194

519

404

1064

1382

907

1327

Barnholtz-Sloan

736

130

387

219

658

123

331

204

647

825

577

739

Campa

8302

1764

4044

2494

11615

2193

5609

3813

7572

9032

9995

13235

Chan

1174

317

554

303

1463

364

693

406

1188

1160

1421

1505

Elematore

347

131

148

68

801

255

394

152

410

284

904

698

Fletcher

1470

305

730

435

1341

225

629

487

1340

1600

1079

1603

Garcia-Closas

15084

2921

7284

4879

22105

3773

10682

7650

13126

17042

18228

25982

Gorodnova

140

42

63

35

174

38

84

52

147

133

160

188

Harlid

3545

719

1723

1103

5007

884

2357

1766

3161

3929

4125

5889

Jiang

493

125

247

121

510

127

255

128

497

489

509

511

Latif

919

185

464

270

343

56

160

127

834

1004

272

414

Li

558

162

285

111

635

173

313

149

609

507

659

611

Long

2945

796

1470

679

2981

745

1491

745

3062

2828

2981

2981

McInerney

917

178

467

272

993

182

456

355

823

1011

820

1166

Mizoo

466

180

211

75

458

177

206

75

571

361

560

356

Shan

639

201

303

135

365

96

176

93

705

573

368

362

Tamimi

661

223

263

175

711

273

277

161

709

613

823

599

Teraoka

606

140

292

174

1194

213

623

358

572

640

1049

1339

Zhang

482

143

248

91

527

124

283

120

534

430

531

523

Table 3: rs6983267 polymorphisms genotype distribution and allele frequency in cases and controls

First author

Genotype (N)

Allele frequency (N)

Case

Control

Case

Control

Total

GG

AG

AA

Total

GG

AG

AA

G

A

G

A

Fletcher

1480

338

734

408

1336

312

653

371

1410

1550

1277

1395

McInerney

945

230

464

251

957

245

464

248

924

966

954

960

Wokolorczyk

1006

254

507

245

1910

513

977

420

1015

997

2003

1817

Zhang

478

151

218

109

522

183

233

106

520

436

599

445

Table 4: Meta-analysis results

Comparisons

OR

95%CI

P value

Heterogeneity

Effects model

I2

P value

Allele model

rs13281615

1.10

1.07-1.13

P < 0.00001

49%

0.006

R

African

1.08

0.96-1.22

0.18

58%

0.12

F

Asian

1.08

1.03-1.14

0.001

0%

0.77

F

Caucasians

1.11

1.06-1.16

P < 0.00001

67%

0.0004

R

rs6983267

0.95

0.89-1.01

0.10

0%

0.66

F

Dominant model

rs13281615

1.13

1.08-1.18

P < 0.00001

39%

0.03

R

African

1.13

0.94-1.36

0.18

0%

0.34

F

Asian

1.11

1.03-1.21

0.009

0%

0.92

F

Caucasians

1.14

1.07-1.21

P < 0.0001

63%

0.002

R

rs6983267

0.94

0.85-1.04

0.24

0%

0.63

F

Recessive model

rs13281615

1.13

1.08-1.18

P < 0.00001

30%

0.10

R

African

1.09

0.89-1.32

0.40

60%

0.11

F

Asian

1.11

1.03-1.20

0.008

0%

0.79

F

Caucasians

1.15

1.08-1.22

P < 0.00001

50%

0.02

R

rs6983267

0.93

0.84-1.03

0.15

0%

0.89

F

Homozygous genetic model

rs13281615

1.20

1.13-1.27

P < 0.00001

43%

0.02

R

African

1.16

0.92-1.47

0.22

60%

0.12

F

Asian

1.17

1.07-1.29

0.001

0%

0.77

F

Caucasians

1.22

1.12-1.32

P < 0.00001

62%

0.002

R

rs6983267

0.90

0.80-1.02

0.10

0%

0.69

F

Heterozygote comparison

rs13281615

1.09

1.06-1.12

P < 0.00001

22%

0.17

F

African

1.12

0.93-1.36

0.24

0%

0.68

F

Asian

1.08

1.00-1.18

0.06

0%

0.98

F

Caucasians

1.11

1.05-1.17

0.0005

55%

0.01

R

rs6983267

0.96

0.86-1.07

0.45

0%

0.74

F

F-fixed effects model; R-random effects model.

Sensitivity analyses

As shown in Table 1, all the studies conformed to he balance of Hardy-Weinberg equilibrium (HWE) in controls except 5 studies (P < 0.05), however, after performing the sensitivity analyses, the overall outcomes were no statistically significant change when removing any of the articles, indicating that our study has good stability and reliability.

Detection for heterogeneity

Heterogeneity among studies was obtained by Q statistic. Random-effect models were applied if p-value of heterogeneity tests were less than 0.1 (p ≤ 0.1), otherwise, fixed-effect models were selected (Table 4).

Publication bias

We use Begg’s funnel plot and Egger test to evaluate the published bias. As Figure 2 (rs13281615) and Figure 3 (rs6983267) indicated, the funnel plot is symmetrical, indicating that there is no significant publication bias in the total population. In our study, no significant publication bias was found in the Begg’s test and Egger’s test (P > 0.05).

Funnel plot on the association of rs13281615 variant and breast cancer in a fixed-effect model (heterozygote comparison).

Figure 2: Funnel plot on the association of rs13281615 variant and breast cancer in a fixed-effect model (heterozygote comparison). Abbreviations: SE, standard error; OR, odds ratio; A vs. G, Allele model.

Funnel plot on the association of rs6983267 variant and breast cancer in a fixed-effect model (recessive model ).

Figure 3: Funnel plot on the association of rs6983267 variant and breast cancer in a fixed-effect model (recessive model ). Abbreviations: SE, standard error; OR, odds ratio; A vs. G, Allele model.

DISCUSSION

A large amount of evidence suggests that genetics is important in determining the risk of cancer [35]. Related research is to search for the susceptibility genes associated with cancer. It is believed that SNP is the main cause of human genetic variation, which may increase individual risk to suffer cancer [14, 18, 22, 23]. With the development of medical science, hereditary susceptibility to cancer has caused people’s great interest, and the study on the genetic polymorphism of the tumor is increasing.

At present, BRCA1 and BRCA2 gene polymorphisms are generally considered to be associated with BC, but because of the low mutation rate, it can only be detected in the small part of BC patients [36]. In 2007, the whole genome association analysis identified many genetic polymorphisms that may be associated with the development of BC, which included rs6983267 and rs13281615 [37].

The 8q24 rs6983267 and rs13281615 bit is located in the non - base region of the dye - color 8q24, and Its function is not very clear. 8q24.12-24.13 location myelocytomatosis oncogene (MYC), MYC is a group of cancer genes, which are not expressed in normal cells, and expressed in some cancer cells. MYC can promote cell proliferation, immortalized, differentiation and transformation. It is an significant factor in the formation of BC, colon cancer and prostate cancer [38, 39]. Studies shown that the chromosome 8q24 region is related to the occurrence of prostate cancer and colon cancer, which can play a role in carcinogenesis through interacting with MYC gene amplification and over expression [40]. The change of some loci of a single gene may have limited impact on the ultimate effect of cancer, and it is needed to carry out large-scale studies in populations.

Recently, a growing number of epidemiological studies have been carried out to explore the relationship between 8q24 (rs13281615 and rs6983267) polymorphisms and the occurrence of BC. Nevertheless, the conclusions are still inconclusive. Therefore, we carried out the meta-analysis on the whole included case-control researches to make a more accurate assessment of the relationship.

In our study, 21 studies were eventually included, including 52,683 cases and 64,672 controls. And we assessed the relationship between 8q24 (rs13281615 and rs6983267) polymorphisms and the occurrence of BC. In the total population, the pooled results indicated that the correlation between 8q24 rs13281615 polymorphism and the occurrence of BC was significant in any genetic model (Table 4). It was partially consistent with the consequences of previous five meta-analysis [30-34], while the sample size was several times than theirs, make the results more convincing.

BC is a disease with a difference in the incidence and mortality among different ethnic groups. Each increase of 25% European descent, the risk of developing BC will increase by 1.79 times [41]. Easton [42] et al believes that the incidence of the European population is higher than that of other ethnic groups, which are consistent with the results of this study. The subgroup study stratified by ethnicity showed an increased BC risk in Asians and Caucasians (Table 4). While, there was not any genetic model attained statistical correlation in Africans. There was no association in any genetic model in rs6983267 (Table 4). It was partially consistent with the Dai(2013)’s study [30] ( with 11 papers containing 40,762 cases and 50,380 controls) and Pei(2013)’s [32] (with 12 eligible studies including 42,508 cases and 53,928 controls) findings. Another meta-analysis by Song(2012) [33] et al, including seven papers with 22,128 cases and 29,276 controls, they found no relationship between rs13281615 polymorphism and BC susceptibility in Asians. This contradiction may be caused by sample sizes and racial differences.

Our meta-analysis has some limitations in the following aspects. First, our study is a summary of the data. Due to the lack of the original data needed, we could not evaluate the cancer susceptibility stratified by age, Sex, environment, hormone level, menopause age and other risk factors. We also cannot analyze these studies to analyze the potential interaction of gene - environment and gene - gene. Secondly, we just included the published papers in our study, there may still be some published studies in line with the conditions. Moreover, our study is a summary of the data. We did not verify it from the level of basic experiments. Data from a large sample of multiple centers is still needed to confirm the relationship between 8q24 (rs13281615 and rs6983267) polymorphisms and BC risk.

In summary, our study suggests that 8q24 rs13281615 polymorphism could increase the risk of BC in Asians, Caucasians and in overall population, While, there was no association in Africans. The rs6983267 polymorphism has no relationship with the occurrence of BC in any genetic model. Data from a large sample of multiple centers is still needed to confirm our findings.

MATERIALS AND METHODS

Literature searching strategy

We searched PubMed, EMBASE, Web of science, the Cochrane Library for relevant studies published before August 13, 2015. The following keywords were used: rs6983267/rs13281615/8q24, variant*/genotype/polymorphism/SNP, breast AND (cancer or carcinom* or neoplasm* or tumor) and the combined phrases for all genetic studies on the association between the 8q24 (rs13281615 and rs6983267) polymorphism and BC risk. The reference lists of all articles were also manually screened for potential studies. Abstracts and citations were screened independently by two authors, all the agreed articles need a second screen for full-text reports. The searching was done without restriction on language.

Selection and exclusion criteria

Inclusion criteria: A study was included in this meta-analysis if it met the following criteria: i) independent case-control studies for humans; ii) the study evaluated the association between 8q24 (rs13281615 and rs6983267) polymorphism and BC risk; iii) has available genotype frequencies in cancer cases and control subjects for risk estimate. We excluded comments, editorials, systematic reviews or studies lacking sufficient data. If the publications were duplicated or shared in more than one study, the most recent publications were included. All identified studies were screened by two investigators independently. What’s more, there was no limitation for publication language.

Data extraction and synthesis

We used endnote bibliographic software to construct an electronic library of citations identified in the literature search. All the PubMed, EMBASE, Web of science and the Cochrane Library searches were performed using Endnote; duplicates were found automatically by endnote and deleted manually. All data extraction were checked and calculated twice according to the inclusion criteria listed above by two independent investigators. Data extracted from the included studies were as follows: First author, year of publication, country, ethnicity, Source of controls, Genotyping method, number of cases and controls and evidence of HWE in controls. A third reviewer would participate if some disagreements were emerged, and a final decision was made by the majority of the votes.

Statistical analysis

All statistical analyses were performed using STATA version 11.0 software (StataCorp LP, College Station, TX) and Review Manage version 5.2.0 (The Cochrane Collaboration, 2012). Hardy-Weinberg equilibrium (HWE) was assessed by χ2 test in the control group of each study [43]. The strength of associations between the 8q24 (rs13281615 and rs6983267) polymorphism and BC risk were measured by odds ratio (ORs) with 95% confidence interval (CIs). Z test was used to assess the significance of the ORs, I2 and Q statistics was used to determine the statistical heterogeneity among studies. A random-effect model was used if p value of heterogeneity tests was no more than 0.1 (p ≤ 0.1), otherwise, a fixed-effect model was selected [43, 44]. Sensitivity analyses were performed to assess the stability of the results. We used Begg’s funnel plot and Egger’s test to evaluate the publication bias [45, 46]. The strength of the association was estimated in the allele model, the dominant model, the recessive model, the homozygous genetic model, and the heterozygous genetic model, respectively. p < 0.05 was considered statistically significant. We performed subgroup according to Ethnicity.

CONFLICTS OF INTEREST

The authors have declared that no conflict of interest exists.

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