RESEARCH ARTICLE

Genetic association between cyclin D1 polymorphism and breastcancer susceptibility

XiaoRui Li & XiaoQing Huo & WeiWei Li &QingHui Yang & Ying Wang & XiaoChun Kang

Received: 19 February 2014 /Accepted: 12 August 2014# International Society of Oncology and BioMarkers (ISOBM) 2014

Abstract Cyclin D1 polymorphism has been reported to beassociated with risk of breast cancer, but the published studieshave yielded controversial results. This study was undertakento derive a precise risk estimate for the cyclin D1 polymor-phism associated with breast cancer risk. We performed asearch of EMBASE, PubMed, and Web of Science. In total,data from 18 publications were pooled and the association wasassessed by odds ratios (ORs) with 95 % confidence intervals(CIs). This analysis showed that there was no obvious associ-ation between the cyclin D1 polymorphism and breast cancerrisk in any of the analyzed genetic model. We found the samenegative association in stratified analyses by ethnicity, sourceof controls, and sample size. Our meta-analysis provides anestimate that the presence of cyclin D1 polymorphism maynot confer susceptibility to breast cancer.

Keywords Cyclin D1 . Polymorphism . Breast cancer .

Susceptibility

Introduction

Cyclin D1 belonging to the D-type cyclin family [1] and wasfirst identified in 1991 as a proto-oncogene that exercisespowerful control over the regulation of the cell cycle [2, 3].Cell cycle transition fromG1 to S phase is mainlymediated bycyclin-dependent kinases (CDKs) [4]. CDKs are accumulatedand activated by cyclin D1 in response to mitogenic growthfactors in early to mid G1 phase [5]. Genetic alternations ofcyclin D1 protein that governs phosphorylation of the retino-blastoma protein (RB) and control exit from the G1 phase of

the cell cycle occur frequently in human cancers and inacti-vation of this pathway may lead to cancer development [6].Cyclin D1 has been indicated to be over-expressed in nearly50 % of mammary tumors and one of the most commonlyover-expressed oncogenes in breast cancer [7].

Germline genetic variability is common in cyclin D1, forexample, single nucleotide polymorphisms (SNPs). Thesecommon SNPs may alter the function and activity of cyclinD1 gene, consequently causing differences in individual sus-ceptibility to cancer progression. In exon 4 of cyclin D1, therelies a silent G to A substitution at nt870 (rs603965) related tothe increase of cyclin D1 expression [8]. The discovery of thispolymorphism has stimulated inquiry into the role of thiscyclin D1 variant in carcinogenesis. Mounting evidence haswell documented a correlation between the cyclin D1 poly-morphism and the risk of colorectal cancer [9], esophagealadenocarcinoma [10], childhood acute lymphoblastic leuke-mia [11], lung cancer [12], and head and neck cancer [13]. Theinvasive breast cancer among women is also a focus forinvestigators in recent years.

To date, a series of studies concerning the association of thecyclin D1 polymorphism and breast cancer risk have beenreported [14–17]. These studies, however, provide inconclu-sive results, partially because of the study design with arelatively small sample size and different ethnicities. To vali-date the association between the cyclin D1 polymorphism andbreast cancer risk, we performed a meta-analysis that assem-bles a large sample size consisting of 18 case–control studies.

Materials and methods

Search strategy

The studies reporting the association between the cyclin D1polymorphism and breast cancer risk were identified from

X. Li (*) :X. Huo :W. Li :Q. Yang :Y. Wang :X. KangDepartment of Oncology, The First Affiliated Hospital of XinxiangMedical University, Xinxiang, Chinae-mail: drlixaorui@126.com

Tumor Biol.DOI 10.1007/s13277-014-2489-5

EMBASE, PubMed, and Web of Science without languagelimitation. Search strategies used for the databases were asfollows: (cyclin D1) and (Pro241Pro or rs603965 or rs9344)and (polymorphism or polymorphisms) and (cancer or breastcancer). Where there were multiple articles with the samesubjects, the most complete or recent article was used. Wealso reviewed the reference lists of the selected articles toidentify additional relevant studies that were missed in theelectronic search.

Inclusion criteria

Two investigators independently screened all titles and ab-stracts of the identified studies. Any associated study inhumans, regardless of sample size, was included if satisfyingthe following criteria: (a) a case–control study; (b) evaluationof the cyclin D1 polymorphism and breast cancer risk; and (c)has available genotype frequencies in cancer cases and controlsubjects for risk estimate.

Data extraction

Two investigators performed data extraction independentlyaccording to the inclusion criteria listed above. The followingdata were recorded for each study: the first author’s name,publication year, ethnicity, study country, genotyping method,

total numbers of cases and controls, and numbers of GG, GA,and AA genotypes in cases and controls. Whenever multipleethnic groups were included in the same study, data wereextracted separately and classified into Caucasians or Asians.

Statistical analysis

Data in the control group of each study were used to assessHardy-Weinberg equilibrium (HWE) by χ2 test. The strengthof association between the cyclin D1 polymorphism and riskof breast cancer was measured by odds ratios (ORs) with 95%confidence intervals (CIs). The risks (ORs) of cancer associ-ated with this polymorphismwas estimated in AAvs. GG, AA+ GAvs. GG, AAvs. GA + GG, allele Avs. allele G, and GAvs. GG, respectively.

Heterogeneity assumption was examined by a χ2-based Qtest. A P value of >0.10 for the Q test was considered homo-geneous among studies. The pooled OR estimate of eachstudy was calculated by the fixed-effects model based on theMantel-Haenszel method [18] when there was no evidence ofobvious heterogeneity (P>0.10). The random-effects modelbased on the DerSimonian and Laird method [19] was usedwhen the Q test indicated significant heterogeneity (P<0.10).Heterogeneity was also quantified with the I2 metric (I2<25 %: no heterogeneity; I2=25–50 %: moderate heterogene-ity; I2=50–75 %: large heterogeneity, I2>75 %: extreme

Table 1 Characteristics of studies included in the meta-analysis for an association between the G870A polymorphism and risk of breast cancer

First author Year Ethnicity Country Genotyping method Source HWE

Grieu 2003 Caucasian Australia PCR-SSCP Hospital-based 0.556

Krippl 2003 Caucasian Austria PCR Population-based 0.152

Forsi 2004 Caucasian Finland PCR-RFLP Population-based 0.862

Ceschi 2005 Asian Singapore TaqMan Population-based 0.230

Shu 2005 Asian China PCR-RFLP Population-based 0.005

Onay 1 2008 Caucasian Canada TaqMan Population-based 0.412

Onay 2 2008 Caucasian Canada TaqMan Population-based 0.999

Yu 2008 Asian China RT-PCR Hospital-based 0.001

Naidu 2008 Asian Malaysia PCR-RFLP Hospital-based 0.787

Driver 2008 Caucasian UK TaqMan Population-based 0.656

Millar 2009 Caucasian USA NR Population-based 0.153

Yaylim-Eraltan 2009 Caucasian Turkey PCR Hospital-based 0.816

Justenhoven 2009 Caucasian Germany MALDI-TOF Population-based 0.468

Haiman 2009 Caucasian USA Direct sequencing Population-based 0.159

Canbay 2010 Caucasian Turkey PCR-RFLP Population-based 0.659

Jelonek 2010 Caucasian Poland PCR-RFLP Hospital-based 0.029

Jeon 2010 Asian Korea MALDI-TOF Hospital-based 0.096

Absenger 2013 Caucasian Austria TaqMan Population-based 0.302

Bedewy 2013 Caucasian Egypt PCR-RFLP Population-based 0.741

PCR polymerase chain reaction, PCR-RFLP PCR-restriction fragment length polymorphism, PCR-SSCP PCR-single strand conformation polymor-phism, MALDI-TOF matrix-assisted laser desorption/ionization time-of-flight, NR not reported, TaqMan TaqManSNP, HWE Hardy-Weinbergequilibrium

Tumor Biol.

heterogeneity) [20]. Subgroup analyses were performed byethnicity (Caucasian and Asian), control source (HB and PB)and sample size (numbers of cases, <500; 500–1,000; and>1,000).

One-way sensitivity analysis was performed by repeatingmeta-analysis of deleting each single study to assess thestability of the results. An estimate of potential publicationbias was determined by Begg’s funnel plot and an asymmetricplot suggested a possible publication bias. The funnel plot wasfurther examined by Egger’s test [21], with a significant Pvalue of 0.10.

All of the statistical data used in our meta-analysis wereanalyzed by STATA version 12.0 (StataCorp, College Station,TX). AllP values were two-sidedwith a significant level of 0.10.

Results

Characteristics of studies

We yielded a total of 116 studies from EMBASE, PubMed,andWeb of Science. After excluding 71 irrelevant studies, and23 articles with insufficient data, 22 studies remained to befurther examined. We reviewed full texts of the remainingstudies and removed another four studies: two of them didnot allow data extraction [22, 23], one was updated by asubsequently published eligible study [24], and one was areview article [25], leaving 18 articles [14–17, 26–39] involv-ing 12,975 cancer cases and 15,180 control subjects for dataextraction and pooled analysis.

The 18 articles consisting of 19 case–control studies (onepublication contained more than one individual study with thesame ethnicity) were published between 2003 and 2013.Among them, five studies were in Asians and 14 in Caucasians.The characteristics of these 19 studies are presented in Table 1.

Meta-analysis

The pooled ORs and 95 % CIs for the cyclin D1 polymor-phism and breast cancer risk are showed in Table 2. All 18publications for this polymorphism presented available geno-type data and contained adequate information for subgroupanalyses by ethnicity, control source, and sample size. As noevidence of between-study heterogeneity was indicated in allgenetic models, a fixed-effects model was used. The com-bined results based on all studies showed that there was nostatistically significant link between the cyclin D1 polymor-phism and risk of breast cancer either in the AAvs. GG (OR=1.05, 95%CI=0.99–1.11,P=0.975, I2=0.0%) genetic modelor in the AA + GA vs. GG (OR=1.02, 95 % CI=0.98–1.06,P=1.000, I2=0.0 %) genetic model. None of the other threemodels suggested any significant evidence for breast cancer T

able2

Meta-analysisof

theassociations

betweentheG870A

polymorphism

andbreastcancer

risk

AAvs.G

GAA+GAvs.G

GAAvs.G

A+GG

AlleleAvs.alleleG

GAvs.G

G

OR(95%

CI)

Ph

I2(%

)OR(95%

CI)

Ph

I2(%

)OR(95%

CI)

Ph

I2(%

)OR(95%

CI)

Ph

I2(%

)OR(95%

CI)

Ph

I2(%

)

Ethnicity

Caucasian

1.04

(0.97,1.12)

0.875

0.0

1.02

(0.98,1.06)

0.993

0.0

1.04

(0.97,1.11)

0.730

0.0

1.02

(0.99,1.06)

0.886

0.0

1.02

(0.97,1.07)

0.956

0.0

Asian

1.05

(0.95,1.16)

0.945

0.0

1.02

(0.95,1.10)

0.965

0.0

1.03

(0.94,1.13)

0.525

0.0

1.03

(0.97,1.09)

0.930

0.0

1.03

(0.94,1.13)

0.795

0.0

Source

ofcontrol

Hospital

1.07

(0.95,1.22)

0.978

0.0

1.03

(0.95,1.13)

0.979

0.0

1.05

(0.94,1.18)

0.651

0.0

1.04

(0.97,1.11)

0.978

0.0

1.05

(0.94,1.16)

0.756

0.0

Populatio

n1.04

(0.97,1.11)

0.839

0.0

1.02

(0.98,1.06)

0.991

0.0

1.03

(0.97,1.10)

0.672

0.0

1.02

(0.99,1.05)

0.846

0.0

1.02

(0.97,1.07)

0.970

0.0

Sam

plesize

<500

1.07

(0.93,1.25)

0.953

0.0

1.02

(0.93,1.12)

0.978

0.0

1.11

(0.97,1.27)

0.819

0.0

1.04

(0.97,1.13)

0.973

0.0

1.01

(0.90,1.14)

0.784

0.0

500–1000

1.04

(0.96,1.13)

0.523

0.0

1.02

(0.97,1.07)

0.835

0.0

1.02

(0.94,1.10)

0.375

5.5

1.02

(0.98,1.06)

0.491

0.0

1.02

(0.96,1.08)

0.807

0.0

>1,000

1.05

(0.95,1.16)

0.700

0.0

1.02

(0.96,1.09)

0.930

0.0

1.03

(0.94,1.13)

0.590

0.0

1.02

(0.97,1.08)

0.703

0.0

1.03

(0.95,1.12)

0.900

0.0

Total

1.05

(0.99,1.11)

0.975

0.0

1.02

(0.98,1.06)

1.000

0.0

1.03

(0.98,1.09)

0.806

0.0

1.02

(0.99,1.05)

0.976

0.0

1.02

(0.98,1.07)

0.986

0.0

PhPvalueof

heterogeneity

test,C

Iconfidence

interval,O

Rodds

ratio

Tumor Biol.

risk. Lack of significance persisted in the stratified analyses byethnicity, source of controls, and sample size (Figs. 1 and 2).

Sensitivity analyses

Sensitivity analyses were performed by deleting each singlestudy to evaluate the influence of the individual dataset to thepooled OR. The overall results did not show quantitativechanges when excluding any study, suggesting the stabilityand reliability of this meta-analysis.

Publication bias

Both Begg’s test and Egger’s test were employed to assess thepublication bias among the studies. Neither Begg’s test norEgger’s test showed statistical evidence for publication bias inour meta-analysis (PBegg=0.780, PEgger=0.458 for AAvs. GA+ GG) (Fig. 3).

Discussion

Cyclin D1 alterations are a relatively common event in cancer,especially in breast cancer. Over-expression of this gene

should be responsible for 50–80 % of all DCIS cases[40–42]. The cyclin D1 polymorphism is an extensively stud-ied SNP in cyclin D1 gene, for the A allele generates a noveltranscript known as “transcript b” by modulating messengerRNA (mRNA) alternative splicing [43, 44]. Transcript b couldbe a nuclear oncogene and is expressed in tumor-derived cells[45]. Evidence from both experimental and epidemiologicstudies supports the hypothesis that the cyclin D1 polymor-phism is associated with breast cancer [16, 17]. In contrast tothe positive conclusions, negative associations are also dem-onstrated [26, 27]. In an attempt to resolve this discrepancyand to test whether the cyclin D1 polymorphism could modifythe risk of breast cancer, we conducted this large meta-analysis.

In the present study, including 12,975 cancer cases and15,180 control subjects from 19 case–control studies, weexamined the association of the well-characterized polymor-phism and breast cancer. The combined results showed thatthere is no obvious association between the cyclin D1 poly-morphism and the risk of breast cancer in general populations.From stratified analyses, we did not find an effective modifi-cation of breast cancer risk by ethnicity, source of control, andsample size.

Several meta-analyses have shifted their attention to thistopic. The first study came in 2008, with the discovery of an

Fig. 1 Forest plot of overall riskof breast cancer associated withthe G870A polymorphism (AAvs. GG) by the fixed effects foreach of the 18 published studies.For each study, the estimates ofOR and its 95 % CI were plottedwith a box and a horizontal line.The symbol filled diamondindicates pooled OR andits 95 % CI

Tumor Biol.

increased cancer risk associated with the cyclin D1 polymor-phism [46]. Following this, four subsequent meta-analyseswere conducted and showed the same results that are consis-tent with the initial meta-analysis [47–50]. Conversely, our

study is far larger compared with any previous study, impli-cating an inverse finding. One reasonable explanation is thatthis common SNP itself is unlikely to have a significantbiological effect, and a small sampled study may mislead the

Fig. 2 Forest plot of overall riskof breast cancer associated withthe G870A polymorphism (AA +GAvs. GG) by the fixed effectsfor each of the 18 publishedstudies. For each study, theestimates of OR and its 95 % CIwere plotted with a box and ahorizontal line. The symbol filleddiamond indicates pooled OR andits 95 % CI

Begg's funnel plot with pseudo 95% confidence limits

Low

er

CI (O

R)

s.e. of: Lower CI (OR)

0 2 4 6

-10

0

10

20

Fig. 3 Funnel plot analysis todetect publication bias. Eachpoint represents an individualstudy for the indicated association

Tumor Biol.

understanding of the predisposition role played in the risk ofbreast cancer.

It is hard to interpret the results when significant heteroge-neity and publication bias were indicated. These two factors,however, were not observed in our meta-analysis. Despite theobvious strengths, several limitations have to be considered ininterpreting the results. Most of the included studies wereretrospective and differed substantially in study designs. Forexample, either population-based controls or hospital-basedcontrols were used. The different criteria for control selectionmay have introduced bias. Further, although no statisticallysignificant heterogeneity was indicated in stratification analy-ses in our combined analysis, other stratification factors mayinfluence the between-study heterogeneity. Hence, we suggestfurther genetic association studies with more risk factorsanalyzed.

In summary, this meta-analysis evaluated the effect of thecyclin D1 polymorphism on breast cancer risk and supports anonsignificant association between them. Additional evidenceon the cyclin D1 and breast cancer association is necessary tofurther clarify the findings in this analysis.

References

1. Ormandy CJ et al. Cyclin D1, EMS1 and 11q13 amplification inbreast cancer. Breast Cancer Res Treat. 2003;78(3):323–35.

2. Motokura T et al. A novel cyclin encoded by a bcl1-linked candidateoncogene. Nature. 1991;350(6318):512–5.

3. Knudsen KE et al. Cyclin D1: polymorphism, aberrant splicing andcancer risk. Oncogene. 2006;25(11):1620–8.

4. Reed SI. The role of p34 kinases in the G1 to S-phase transition.Annu Rev Cell Biol. 1992;8:529–61.

5. Diehl JA. Cycling to cancer with cyclin D1. Cancer Biol Ther.2002;1(3):226–31.

6. Sherr CJ. Cancer cell cycles. Science. 1996;274(5293):1672–7.7. Sutherland RL, Musgrove EA. Cyclin D1 and mammary carcinoma:

new insights from transgenic mouse models. Breast Cancer Res.2002;4(1):14–7.

8. Ewen ME et al. Functional interactions of the retinoblastoma proteinwith mammalian D-type cyclins. Cell. 1993;73(3):487–97.

9. Bala S, Peltomaki P. Cyclin D1 as a genetic modifier in hereditarynonpolyposis colorectal cancer. Cancer Res. 2001;61(16):6042–5.

10. Casson AG et al. Cyclin D1 polymorphism (G870A) and risk foresophageal adenocarcinoma. Cancer. 2005;104(4):730–9.

11. Hou X et al. Cyclin D1 gene polymorphism and susceptibility tochildhood acute lymphoblastic leukemia in a Chinese population. IntJ Hematol. 2005;82(3):206–9.

12. Hung RJ et al. Sequence variants in cell cycle control pathway, X-rayexposure, and lung cancer risk: a multicenter case-control study inCentral Europe. Cancer Res. 2006;66(16):8280–6.

13. Zheng Y et al. Cyclin D1 polymorphism and risk for squamous cellcarcinoma of the head and neck: a case-control study.Carcinogenesis. 2001;22(8):1195–9.

14. Grieu F et al. Lack of association between CCND1 G870A polymor-phism and the risk of breast and colorectal cancers. Anticancer Res.2003;23(5b):4257–9.

15. Ceschi M et al. The effect of cyclin D1 (CCND1) G870A-polymorphism on breast cancer risk is modified by oxidative stressamong Chinese women in Singapore. Carcinogenesis. 2005;26(8):1457–64.

16. Shu XO et al. Association of cyclin D1 genotype with breast cancerrisk and survival. Cancer Epidemiol Biomarkers Prev. 2005;14(1):91–7.

17. Onay UV et al. Combined effect of CCND1 and COMT polymor-phisms and increased breast cancer risk. BMC Cancer. 2008;8:6.

18. Mantel N, Haenszel W. Statistical aspects of the analysis of data fromretrospective studies of disease. J Natl Cancer Inst. 1959;22(4):719–48.

19. DerSimonian R, Laird N.Meta-analysis in clinical trials. Control ClinTrials. 1986;7(3):177–88.

20. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.

21. Egger M et al. Bias in meta-analysis detected by a simple, graphicaltest. BMJ. 1997;315(7109):629–34.

22. Abramson VG et al. Cyclin D1b in human breast carcinoma andcoexpression with cyclin D1a is associated with poor outcome.Anticancer Res. 2010;30(4):1279–85.

23. Labonte MJ et al. The Cyclin D1 (CCND1) A870G polymorphismpredicts clinical outcome to lapatinib and capecitabine in HER2-positive metastatic breast cancer. Ann Oncol. 2012;23(6):1455–64.

24. Onay VU et al. SNP-SNP interactions in breast cancer susceptibility.BMC Cancer. 2006;6:114.

25. Al DA, Qureshi S, Al Saleh KA, Al Qahtani FH, Aleem A, AlSaif A,et al. Studies on the methods of diagnosis and biomarkersused inearly detection of breast cancer in the Kingdom of Saudi Arabia: anoverview. World J Med Sci. 2013;8(1):36–47.

26. Krippl P et al. The 870G>A polymorphism of the cyclin D1 gene isnot associated with breast cancer. Breast Cancer Res Treat.2003;82(3):165–8.

27. Forsti A et al. Single nucleotide polymorphisms in breast cancer.Oncol Rep. 2004;11(4):917–22.

28. Yu CP et al. Tumor susceptibility and prognosis of breast cancerassociated with the G870A polymorphism of CCND1. Breast CancerRes Treat. 2008;107(1):95–102.

29. Naidu R, Yip CH, Taib NA. Polymorphisms of HER2 Ile655Val andcyclin D1 (CCND1) G870A are not associated with breast cancer riskbut polymorphic allele of HER2 is associated with nodal metastases.Neoplasma. 2008;55(2):87–95.

30. Driver KE et al. Association of single-nucleotide polymorphisms inthe cell cycle genes with breast cancer in the British population.Carcinogenesis. 2008;29(2):333–41.

31. Millar EK et al. Cyclin D1b protein expression in breast cancer isindependent of cyclin D1a and associated with poor disease outcome.Oncogene. 2009;28(15):1812–20.

32. Yaylim-Eraltan I et al. Breast cancer and cyclin D1 gene polymor-phism in Turkish women. In Vivo. 2009;23(5):767–72.

33. Justenhoven C et al. Polymorphic loci of E2F2, CCND1 and CCND3are associated with HER2 status of breast tumors. Int J Cancer.2009;124(9):2077–81.

34. Haiman CA et al. Screening and association testing of commoncoding variation in steroid hormone receptor co-activator and co-repressor genes in relation to breast cancer risk: the multiethniccohort. BMC Cancer. 2009;9:43.

35. Canbay E et al. CCND1 and CDKN1B polymorphisms and risk ofbreast cancer. Anticancer Res. 2010;30(7):3093–8.

36. Jelonek K et al. Association between single-nucleotide polymor-phisms of selected genes involved in the response to DNA damageand risk of colon, head and neck, and breast cancers in a Polishpopulation. J Appl Genet. 2010;51(3):343–52.

37. Jeon S et al. Combined genetic effect of CDK7 and ESR1 polymor-phisms on breast cancer. Breast Cancer Res Treat. 2010;121(3):737–42.

Tumor Biol.

38. Absenger, G., et al. (2013). A common and functional gene variant inthe vascular endothelial growth factor a predicts clinical outcome inearly-stage breast cancer. Mol Carcinog.

39. Bedewy AM et al. Association of cyclin D1 A870G polymorphismwith two malignancies: acute lymphoblastic leukemia and breastcancer. J BUON. 2013;18(1):227–38.

40. Roy PG, Thompson AM. Cyclin D1 and breast cancer. Breast.2006;15(6):718–27.

41. Simpson JF et al. Amplification of CCND1 and expression of itsprotein product, cyclin D1, in ductal carcinoma in situ of the breast.Am J Pathol. 1997;151(1):161–8.

42. Gillett CE et al. Cyclin D1 and associated proteins in mammaryductal carcinoma in situ and atypical ductal hyperplasia. J Pathol.1998;184(4):396–400.

43. Betticher DC et al. Alternate splicing produces a novel cyclin D1transcript. Oncogene. 1995;11(5):1005–11.

44. Wu J et al. Identification of the cyclin D1b mRNAvariant in mouse.Mol Biol Rep. 2009;36(5):953–7.

45. Lu F, Gladden AB, Diehl JA. An alternatively spliced cyclin D1isoform, cyclin D1b, is a nuclear oncogene. Cancer Res.2003;63(21):7056–61.

46. Pabalan N et al. Cyclin D1 Pro241Pro (CCND1-G870A) polymorphismis associated with increased cancer risk in human populations: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2008;17(10):2773–81.

47. Lu C et al. CCND1 G870A polymorphism contributes to breastcancer susceptibility: a meta-analysis. Breast Cancer Res Treat.2009;116(3):571–5.

48. Sergentanis TN, Economopoulos KP. Cyclin D1 G870A polymor-phism and breast cancer risk: a meta-analysis comprising 9,911 casesand 11,171 controls. Mol Biol Rep. 2011;38(8):4955–63.

49. Cui J, Shen L, Wang Y. Specific CCND1 G870A alleles associatedwith breast cancer susceptibility: a meta-analysis of 5,528 cases and5,353 controls. Asian Pac J Cancer Prev. 2012;13(10):5023–5.

50. Yang J et al. Cyclin D1 G870A polymorphism and breast cancer risk:a meta-analysis involving 23,998 subjects. Oncol Res. 2011;19(12):519–25.

Tumor Biol.