Skip to main content
  • Research article
  • Open access
  • Published:

Evaluation of functional genetic variants at 6q25.1 and risk of breast cancer in a Chinese population

Abstract

Introduction

Single-nucleotide polymorphisms (SNPs) at 6q25.1 that are associated with breast cancer susceptibility have been identified in several genome-wide association studies (GWASs). However, the exact causal variants in this region have not been clarified.

Methods

In the present study, we genotyped six potentially functional single-nucleotide polymorphisms (SNPs) within the CCDC170 and ESR1 gene regions at 6q25.1 and accessed their associations with risk of breast cancer in a study of 1,064 cases and 1,073 cancer-free controls in Chinese women. The biological function of the risk variant was further evaluated by performing laboratory experiments.

Results

Breast cancer risk was significantly associated with three SNPs located at 6q25.1—rs9383935 in CCDC170 and rs2228480 and rs3798758 in ESR1—with variant allele attributed odds ratios (ORs) of 1.38 (95% confidence interval (CI): 1.20 to 1.57, P = 2.21 × 10-6), 0.84 (95% CI: 0.72 to 0.98, P = 0.025) and 1.19 (95% CI: 1.04 to 1.37, P = 0.013), respectively. The functional variant rs9383935 is in high linkage disequilibrium (LD) with GWAS-reported top-hit SNP (rs2046210), but only rs9383935 showed a strong independent effect in conditional regression analysis. The rs9383935 risk allele A showed decreased activity of reporter gene in both the MCF-7 and BT-474 breast cancer cell lines, which might be due to an altered binding capacity of miR-27a to the 3' untranslated region (3' UTR) sequence of CCDC170. Real-time quantitative reverse transcription PCR confirmed the correlation between rs9383935 genotypes and CCDC170 expression levels.

Conclusions

The results of this study suggest that the functional variant rs9383935, located at the 3' UTR of CCDC170, may be one candidate of the causal variants at 6q25.1 that modulate the risk of breast cancer.

Introduction

Breast cancer is the most common female malignancy worldwide, accounting for 23% of all the new cancer cases in 2008 [1]. The incidence of breast cancer is relatively low in China compared with Western countries [2]. However, the incidence has increased rapidly in the past two decades, likely due to the change in lifestyle among Chinese women [2],[3].

Genetic variation has been proved to be a critical factor in discriminating cancer-susceptible individuals [4]. In recent genome-wide association studies (GWASs), researchers have identified numerous single-nucleotide polymorphisms (SNPs) associated with breast cancer risk in diverse populations [5]. Among these SNPs, rs2046210, located between coiled-coil domain containing 170 (CCDC170, also called C6orf97) and estrogen receptor 1 (ESR1) at 6q25.1, was first reported to be associated with the risk of breast cancer in Chinese populations [6]. Subsequently, one intronic variant, rs3757318 in CCDC170[7], and another intronic rs9383951 in ESR1[8], were also found to be associated with breast cancer risk. To date, investigators in numerous studies have confirmed these associations with breast cancer in this region, especially for rs2046210 [9]-[12].

ESR1 is a strong candidate susceptibility gene related to breast cancer in the 6q25.1 region (encoding estrogen receptor α), and studies have shown its implication in breast carcinogenesis [13],[14]. Nevertheless, the putative functions of this region are still undefined. Most of the SNPs at 6q25.1 mentioned above have mapped to introns or intergenic regions. In a previous study, a 41-kb block of the 6p25.1 region was systematically analyzed, and significant associations with breast cancer risk were observed for rs1038304, rs6929137, rs2046210 and rs10484919 [15]. However, these variants ae all located upstream of the ESR1 gene region. Hence, to evaluate the causal variants at 6q25.1 in the development of breast cancer, we screened the potentially functional variants at 6q25.1 within two genes (ESR1 and CCDC170) and assessed their associations with breast cancer risk in a case-control study including 1,064 breast cancer cases and 1,073 controls in Chinese women in Jiangsu province in eastern China. We further evaluated potential biological functions of the SNPs that we found to be associated with breast cancer risk.

Material and methods

Study subjects

This study included 1,064 breast cancer cases and 1,073 cancer-free controls, whose characteristics were described previously [16]. Briefly, breast cancer patients were recruited from the First Affiliated Hospital of Nanjing Medical University, the Cancer Hospital of Jiangsu Province and the Gulou Hospital, Nanjing, China, between January 2004 and April 2010. Cases were diagnosed on the basis of standard histological and clinical criteria. The estrogen receptor (ER) and progesterone receptor (PR) status of all breast cancer patients was determined on the basis of immunohistochemistry (IHC) results in pathology reports. The controls were randomly selected from among more than 30,000 participants in a community-based screening program conducted in Jiangsu province, China. The cases and controls were frequency-matched for age (5-year interval). All participants were genetically unrelated. After informed consent was obtained, each individual was interviewed face-to-face to collect information about demographic data and menstrual and reproductive history, and approximately 5 ml of venous blood was collected. This study was approved by the institutional review board of Nanjing Medical University.

Single-nucleotide polymorphism selection and genotyping

In this study, we applied two approaches to select potential functional SNPs at 6q25.1. First, we focused on those in linkage disequilibrium (LD) with the GWAS-identified SNP rs2046210 at this region and replicated the results in another independent sample. As shown in Additional file 1: Figure S1, a total of 30 SNPs are in LD with rs2046210 (r2 > 0.8), which were further functionally evaluated by SNPinfo [17] and expression quantitative trait loci (eQTL) analyses [18]. As a result, rs3983935 in CCDC170 was selected because it is in strong LD with rs2046210 (r2 = 0.86) and was predicted to (1) affect a potential binding site of microRNA-27a (miR-27a) located in the 3' untranslated region (3' UTR) of CCDC170 and (2) regulate expression of CCDC170 in the eQTL analysis.

Using another approach taking into consideration the existence of multiple independent breast cancer susceptibility loci at the 6q25.1 region and the importance of ESR1 in breast cancer development, we also focused on potential functional SNPs of ESR1 (chr6:152160379-152466099). Potentially functional SNPs located in the coding (synonymous SNPs, missense SNPs and nonsense SNPs) and regulatory regions (promoter, 5' UTR and 3' UTR) were selected. The SNPs were further filtered according to the LD analysis (r2 < 0.8) and minor allele frequency (MAF) ≥ 0.05 in Chinese Han population. Six SNPs of ESR1 met the criteria (Additional file 1: Figure S1), but rs1801132 was excluded because of the failure of probe design. We also included one SNP of CCDC170 (rs9383935) and five SNPs of ESR1 (rs488133, rs3798577, rs3798758, rs3798757 and rs2228480). In addition, the well-known SNP at 6q25.1, rs2046210, was selected.

Genomic DNA was isolated from leukocyte pellets of venous blood by proteinase K digestion and followed by phenol-chloroform extraction. All of the DNA samples were checked for quality and quantity with a NanoDrop 2000 spectrophotometer (NanoDrop, Wilmington, DE, USA) and by DNA electrophoresis before genotyping. SNPs were genotyped by using Infinium BeadChip (Illumina, San Diego, CA, USA). The call rate ranged from 97.7% to 97.9% for six SNPs tested in all subjects.

CCDC170 3' untranslated region luciferase plasmids construct and site-directed mutagenesis

The CCDC170 3' UTR containing the rs9383935 G allele was amplified by PCR from human genomic DNA carrying the GG homozygous genotype template with the following primers: sense 5'-AGACGCGTTAAGTCAGGGGCTTTACTAGC-3' and antisense 5'-GCAAGCTTCTGCTGAGTAGTTGGGATTACA-3'. The PCR products were separated in agarose gel, extracted, purified and cloned into the pMIR-REPORT™ miRNA expression reporter vector system (Applied Biosystems, Foster City, CA, USA) with MluI and HindIII digestion and then were ligated by T4 DNA ligase to the recombinant constructs (Additional file 2: Figure S2). The plasmid with the rs9383935 G allele was used as the template for the mutation G → A. The site-directed mutagenesis for the plasmid with the A allele construct was generated using a Mut Express Fast Mutagenesis kit (Vazyme Biotech, Nanjing, China). All PCR amplifications and constructs were sequenced to confirm the accuracy of cloning.

Transient transfection and luciferase assays

MCF-7 and BT-474 cell lines were obtained from Nanjing KeyGen Biotech (Nanjing, China), where they were characterized by mycoplasma detection, DNA fingerprinting, isozyme detection and cell vitality detection. The cell lines were maintained in growth medium supplemented with 10% heat-inactivated fetal bovine serum and 100 U/ml penicillin and 100 μg/ml streptomycin in a 37°C incubator supplemented with 5% CO2 (MCF-7 with Dulbecco's modified Eagle's medium and BT474 with RPMI 1640 medium). Cell lines were seeded into 24-well culture plates and incubated for 24 hours before transfection. Transfections were performed using Lipofectamine 2000 reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's protocol. The luciferase plasmids (empty vector for control and vectors with different rs9383935 alleles) were cotransfected, respectively, into different cells with synthesized mature miR-27a-3p mimic (5'-UUCACAGUGGCUAAGUUCCGC-3') or miRNA negative control. The pRL-SV40 plasmid (Promega, Madison, WI, USA) was also cotransfected as an internal control. After a 24-hour incubation, Firefly and Renilla luciferase activities were determined with the Dual-Luciferase Reporter Assay System (Promega) on a luminometer (BioTek, Winooski, VT, USA). Three independent experiments with six replicates were performed in triplicates.

Transfection of has-miR-27a-3p in MCF-7 breast cancer cell line

The has-miR-27a mimic and the negative control RNA duplex were transfected into MCF-7 cells seeded in six-well plates using Lipofectamine 2000 reagent. Cells were harvested 16 hours after transfection, and RNAs were isolated. Two independent transfection experiments were conducted in triplicate. Real-time PCR analysis of mRNA levels was performed as well.

Real-time quantitative reverse transcription PCR of CCDC170 and ESR1

Total RNAs from peripheral blood samples of 122 healthy individuals or breast cancer cell lines were extracted using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. RNAs were reverse-transcribed into cDNA using PrimeScript™ RT Master Mix (TaKaRa Bio, Tokyo, Japan). Real-time quantitative reverse transcription PCR (qRT-PCR) was carried out with a TaqMan Gene Expression Assay (Applied Biosystems) contained probes for CCDC170 (Hs00228128_m1) and ESR1 (Hs00174860_m1). Each assay was analyzed in triplicate, and ACTB (Hs99999903_m1) was used as an endogenous control. The threshold cycle (Ct) was determined for each assay. The relative expression levels were calculated using the 2−ΔCt method.

Statistical analysis

Differences in demographic characteristics, selected variables and frequencies of alleles and genotypes between the cases and the controls were analyzed by using Student's t-test (for continuous variables) and χ2 test (for categorical variables). The Hardy-Weinberg equilibrium (HWE) for the genotype distribution of each SNP was evaluated using the goodness-of-fit χ2 test by comparing the observed genotype frequencies with the expected ones among the controls. Logistic regression analyses were employed to evaluate the associations between SNPs and the risk of breast cancer by estimating the odds ratios (ORs) and their 95% confidence intervals (CIs) with adjustment for potential confounders such as age, age at menarche and menopausal status. The heterogeneity of associations between subgroups was assessed using the χ2-based Q-test. Differences in measurements of luciferase assays and miR-27a-3p transfection experiments between subgroups were examined using the t-test. Differences in the expression levels of CCDC170 and ESR1 among GG, GA and AA genotypes of rs9383935 were assessed by nonparametric trend test. All of the statistical analyses were two-sided with P < 0.05 taken as the significance level, and they were performed with SAS 9.1.3 software (SAS Institute, Cary, NC, USA).

Results

The characteristics of the 1,064 breast cancer cases and the 1,073 cancer-free controls have been presented elsewhere [16]. In brief, age variable was comparable between cases and controls (P > 0.05). The breast cancer cases showed an earlier age at menarche, a later age at first live birth and a lower proportion of natural postmenopausal status compared with the controls (all P < 0.05). Among the 869 patients with immunohistochemistry records for tumor tissues, 490 cases (56.4%) were ER-positive and 506 cases (58.2%) were PR-positive.

The genotype distributions of the seven SNPs between cases and controls and their associations with breast cancer risk are summarized in Table 1. The observed genotype frequencies of seven SNPs followed Hardy-Weinberg equilibrium among the controls (P > 0.05 for all seven SNPs). Logistic regression analysis revealed that the minor rs9383935 A allele of CCDC170 was significantly associated with an increased risk of breast cancer in an additive model (per-allele OR = 1.38, 95% CI: 1.20 to 1.57, P = 2.21 × 10-6). A similar association was observed for the rs2046210 A allele (per-allele OR = 1.32, 95% CI: 1.16 to 1.50, P = 2.04 × 10-5). In addition, the rs3798758 A allele of ESR1 was associated with an increased risk of breast cancer (per-allele OR = 1.19, 95% CI: 1.04 to 1.37, P = 0.013), whereas the rs2228480 A allele of ESR1 was associated with a decreased risk (per-allele OR = 0.84, 95% CI: 0.72 to 0.98, P = 0.025). However, no significant associations were observed for rs488133, rs3798577 or rs3798757. After correction for multiple testing (n = 7), rs9383935 and rs2046210 of CCDC170 were still significantly associated with breast cancer risk (P < 0.007).

Table 1 Summary of associations between seven single-nucleotide polymorphisms at 6q25.1 and breast cancer risk a

We further evaluated the associations of rs9383935, rs2046210, rs3798758 and rs2228480 with risk of breast cancer by subgroups of age, age at menarche and first live birth, menopausal status (premenopausal and natural menopausal) and subtype of breast cancer (ER and PR status). As shown in Table 2, the associations for rs9383935 and rs2046210 were significant in all the subgroups (all P < 0.05). Specifically, the association with rs3798758 was significant among women of younger age, older age at menarche and premenopausal status (P = 0.005, 0.022 and 0.037, respectively). For rs2228480, a significant association was also observed in women of an older age at both menarche and birth of first child (P = 0.005 and P = 0.048, respectively). In subtypes of breast cancer, rs3798758 was significantly associated with risk of ER-positive breast cancers (per-allele OR = 1.21, 95% CI: 1.02 to 1.48, P = 0.030). Meanwhile, the rs2228480 A allele showed a protective effect regardless of ER and/or PR status. However, no heterogeneity was observed in any strata of the subgroups.

Table 2 Stratified analysis of the associations between rs9383935, rs2046210, rs2228480 and rs3798758 with breast cancer risk

To substantiate these findings, we performed logistic regression analyses conditioned on the four significant SNPs at 6q25.1 (Table 3). We first focused on the two SNPs, rs9383935 and rs2046210, which were in LD (r2 = 0.86) and passed multiple testing correction. After adjusting for rs2046210, the data for rs9383935 remained significant (P = 0.025). In the reverse condition, the results derived for rs2046210 showed a much weaker association (P = 0.810). Next, we included all four SNPs in the same model and found that the effects of rs2228480 and rs3798758 were apparently decreased after conditioned on the three other SNPs (P = 0.069 and P = 0.082, respectively), as was the result for rs2046210 (P = 0.901); however, the effect of rs9383935 remained significant (P = 0.019). Taken together, the results of the conditional regression analysis indicated a strong independent effect of rs9383935 on breast cancer risk in our study population.

Table 3 Conditional regression analysis of rs9383935, rs2046210, rs2228480 and rs3798758

As predicted with RNAhybrid, miR-27a-3p has a lower minimum free energy (MFE) with the G allele (|MFE| = 21.5 kcal/mol) of rs9383935 in CCDC170 than that with the A allele (|MFE| = 25.1 kcal/mol) (Additional file 3: Figure S3). Thus, we proposed that the A allele may decrease the expression of CCDC170, possibly by reducing miRNA repression. Therefore, we constructed the plasmids containing the rs9383935 G or A allele to determine whether this variant could affect gene expression. When we cotransfected miR-27a-3p mimic into MCF-7 cell line, we found that the activity of the reporter gene with the rs9383935 A allele was significantly decreased compared with that of the G allele (0.72 versus 0.28; P = 0.012). Similar effects were observed in the BT-474 cell line (0.87 versus 0.53, P = 0.018) (Figure 1). Subsequently, we transfected miR-27a-3p into MCF-7 breast cancer cells and validated its regulation of the endogenous CCDC170. The qRT-PCR assay showed that miR-27a-2p significantly decreased CCDC170 mRNA level compared with the negative controls (P = 0.016, Figure 2A); however, we did not find significant changes in ESR1 expression after miR-27a-3p transcription (P = 0.361) (Figure 2B).

Figure 1
figure 1

Luciferase reporter assays of rs9383935 G/A in MCF-7 and BT-474 cell lines. The G allele constructs had significantly higher luciferase activity than the plasmids bearing the A allele in both the MCF-7 (*P = 0.012) and BT-474 (**P = 0.018) cell lines. Shown are the mean ± SD of relative luciferase expression for plasmids with different alleles after normalized by control groups in parallel experiments.

Figure 2
figure 2

Transfection of miR-27a-3p in MCF-7 breast cancer cell line. (A) miR-27a-3p downregulated CCDC170 mRNA expression after 16-hour transfection compared with negative control (NC) (P = 0.016). (B) ESR1 mRNA expression was not significantly different between the two groups (P = 0.361).

To further analyze the influence of rs9383935 on gene expression, we examined CCDC170 and ESR1 expression in 122 healthy individuals using qRT-PCR. We found that the subjects with the risk AA genotype had the highest level of CCDC170 expression, followed by subjects with the GA and GG genotypes (P = 0.012) (Figure 3A). However, we did not detect a difference in ESR1 expression between different rs9383935 genotypes (P = 0.238) (Figure 3B).

Figure 3
figure 3

Correlation of rs9383935 genotypes with CCDC170 and ESR1 relative expression. (A) P = 0.012. (B) P = 0.238.

Discussion

The 6q25.1 region was first identified as a breast cancer susceptibility locus in a GWAS of Chinese women [6], which was well-replicated in subsequent follow-up studies [12]. Rs2046210 is an intergenic variant located 29 kb upstream of ESR1 5' UTR and 6 kb downstream of CCDC170 3' UTR. eQTL analysis indicated that rs2046210 was significantly associated with CCDC170 expression [19]. However, it has been suggested that there is no strong evidence to support a role of SNP rs2046210 as a functional variant regulating the expression of CCDC170 according to the results of bioinformatics analysis from SNPinfo and RegulomeDB [20]. Nevertheless, these findings suggest that other genetic variants highly correlated with rs2046210 at 6q25.1 may be functional and may modulate individual susceptibility to breast cancer.

Recently, Cai et al. conducted luciferase assays with four fragments from the 36-kb region harboring rs2046210, and they found that rs6913578, in strong LD with rs2046210 (r2 > 0.8 in CHB and European ancestry (CEU)), might be a functional variant acting as a regulator of enhancement [21], suggesting that genetic variants at 6q25.1 may function through modulating a transcriptional mechanism. In contrast, in the present study, we analyzed functional SNPs in strong LD (r2 > 0.8) with rs2046210, especially for those SNPs in the miRNA binding sites. Interestingly, we found that rs9383935 highly correlated with rs2046210 was significantly associated breast cancer susceptibility, which result from the allele's differential binding affinity of miR-27a in the 3' UTR of CCDC170 as evaluated by luciferase assays and miRNA transfection in breast cancer cell lines. Notably, this functional variant in CCDC170 showed a strong independent effect, even when well-known rs2046210 was adjusted for in the logistic regression analysis. Moreover, qRT-PCR results confirmed that the eQTL annotation linked rs9383935 to CCDC170 expression. CCDC170 is an uncharacterized open reading frame (ORF) located upstream of ESR1. Several genetic variants within this gene have been implicated in GWASs as being associated with the risk of breast cancer and bone mineral density [7],[22]-[24]. For example, Dunbiers et al. observed that three ORFs including CCDC170 expression were highly correlated with ESR1 in aromatase inhibitor-treated breast tumor and breast cancer cell lines [25]. miR-27a is known to function as an onco-miRNA in several cancer cell lines [26]-[28] and to play an important part in cell differentiation and proliferation [28],[29]. Furthermore, overexpression of miR-27a could promote epithelial-mesenchymal transition in cancer metastasis and could be a promising prognostic factor in breast cancer [30].

Taken together, these findings suggest that the variant rs9383935 may modulate individual susceptibility to breast cancer, possibly through regulating miR-27a inhibition of CCDC170 expression. On the basis of the above results, rs9383935 could be considered a potential causal variant at 6q25.1. Additional studies are needed to validate our findings and extend the role of CCDC170 in the etiology of breast cancers.

Researchers in numerous studies have evaluated the associations between variants in ESR1 and breast cancer risk [31],[32]. As mediated by estrogen, ERα can directly bind to estrogen response elements or indirectly interacts with chromatin through tethering to other transcription factors, such as coactivators or corepressors [13]. Clinical and epidemiological studies have shown that ERα affects cancer initiation, progression and response to treatment, especially in breast cancer [14]. In a previous study, we conducted a meta-analysis in diverse populations and provided evidence for associations between two SNPs (rs2234693, rs1801132) of ESR1and breast cancer susceptibility [31]. In a follow-up study, we performed a case°Control study with 878 cases and 900 controls on rs2234693 and rs1801132 validated the association of rs2234693 with breast cancer risk in Chinese women (OR = 0.85, 95% CI: 0.74 to 0.98, P = 0.024), but not for rs1801132 [15].

As an extension of our previous studies, in the present study we evaluated potentially functional SNPs of ESR1 in a larger sample size comprising 1,064 cases and 1,073 controls. We found significant associations of rs3798758 and rs2228480 with breast cancer risk Chinese women. The SNP rs2228480, located in exon 8 of ESR1, is a synonymous variant. The exon 8 involves in the assembling of the C-terminal region of ERα [33]. This region modulates interaction between ERα and other transcription factors, likely to change the affinity of ERα with DNA [33]. Although synonymous variants do not change amino acid sequences, accumulated evidence indicates that these variants can modify mRNA splicing, stability, structure and translation process [34]. For example, Nackley et al. showed that diverse mRNA secondary structures with different stability were correlated to protein expression levels [35]. Another SNP, rs3798758, may also influence miRNA binding, including miR-383, a negative regulator of proliferation [36]. Nevertheless, in the present study, both of these two SNPs showed weak effects in our multivariate logistic regression analysis, which failed to show their independent associations with breast cancer risk. However, some variants in intron regions which might be involved in alternative splicing or enhancer manipulation were not included in the present study. Additional investigations focused on these regions are warranted to expand the understanding of 6q25.1 in breast cancer susceptibility.

Conclusions

Overall, in the present study, we evaluated six potentially functional SNPs within the 6q25.1 region and confirmed that rs9383935, rs3798758 and rs2228480 were associated with breast cancer in Chinese women, and we also replicated rs2046210 in accordance with previous reports. Specifically, the CCDC170 rs9383935 showed the most prominent effect of any other variants of ESR1 or rs2046210, which provides new evidence for the role of the 6q25.1 region in breast cancer susceptibility. Further functional investigations of CCDC170 and 6q25.1 are warranted to fully reveal the mechanisms underlying the observed association with risk of breast cancer.

Authors' contributions

HS, XG and ZH conceived of the study and managed the overall project. YW, YH, ZQ, YJ and JC were responsible for sample-processing and performed the experiments. YW and GJ interpreted the initial statistical analyses and drafted the manuscript. JD and YW performed data management and checked the statistical analyses. HS, ZH, XG, GJ and HM contributed to the editing of the manuscripts. All authors read and approved the final manuscript.

Additional files

Abbreviations

CCDC170:

Coiled-coil domain containing 170

CI:

Confidence interval

eQTL:

Expression quantitative trait loci

ER:

Estrogen receptor

ESR1:

Estrogen receptor 1

GWAS:

Genome-wide association study

HWE:

Hardy–Weinberg equilibrium

IHC:

Immunohistochemistry

LD:

Linkage disequilibrium

MAF:

Minor allele frequency

MFE:

Minimum free energy

OR:

Odds ratio

PR:

Progesterone receptor

SNP:

Single-nucleotide polymorphism

UTR:

Untranslated region

References

  1. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM: Estimates of worldwide burden of cancer in, 2008: GLOBOCAN 2008. Int J Cancer. 2010, 127: 2893-2917. 10.1002/ijc.25516.

    Article  CAS  PubMed  Google Scholar 

  2. Linos E, Spanos D, Rosner BA, Linos K, Hesketh T, Qu JD, Gao YT, Zheng W, Colditz GA: Effects of reproductive and demographic changes on breast cancer incidence in China: a modeling analysis. J Natl Cancer Inst. 2008, 100: 1352-1360. 10.1093/jnci/djn305.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Ziegler RG, Anderson WF, Gail MH: Increasing breast cancer incidence in China: the numbers add up. J Natl Cancer Inst. 2008, 100: 1339-1341. 10.1093/jnci/djn330.

    Article  PubMed  Google Scholar 

  4. Hirschhorn JN, Daly MJ: Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 2005, 6: 95-108. 10.1038/nrg1521.

    Article  CAS  PubMed  Google Scholar 

  5. Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health: A Catalog of Published Genome-Wide Association Studies. (accessed 22 August 2014)., [http://www.genome.gov/26525384]

  6. Zheng W, Long J, Gao YT, Li C, Zheng Y, Xiang YB, Wen W, Levy S, Deming SL, Haines JL, Gu K, Fair AM, Cai Q, Lu W, Shu XO: Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nat Genet. 2009, 41: 324-328. 10.1038/ng.318.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Turnbull C, Ahmed S, Morrison J, Pernet D, Renwick A, Maranian M, Seal S, Ghoussaini M, Hines S, Healey CS, Hughes D, Warren-Perry M, Tapper W, Eccles D, Evans DG, Hooning M, Schutte M, van den Ouweland A, Houlston R, Ross G, Langford C, Pharoah PD, Stratton MR, Dunning AM, Rahman N, Easton DF: Genome-wide association study identifies five new breast cancer susceptibility loci. Nat Genet. 2010, 42: 504-507. 10.1038/ng.586.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Long J, Cai Q, Sung H, Shi J, Zhang B, Choi JY, Wen W, Delahanty RJ, Lu W, Gao YT, Shen H, Park SK, Chen K, Shen CY, Ren Z, Haiman CA, Matsuo K, Kim MK, Khoo US, Iwasaki M, Zheng Y, Xiang YB, Gu K, Rothman N, Wang W, Hu Z, Liu Y, Yoo KY, Noh DY, Han BG, et al: Genome-wide association study in east Asians identifies novel susceptibility loci for breast cancer. PLoS Genet. 2012, 8: e1002532-10.1371/journal.pgen.1002532.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hein R, Maranian M, Hopper JL, Kapuscinski MK, Southey MC, Park DJ, Schmidt MK, Broeks A, Hogervorst FB, Bueno-de-Mesquit HB, Muir KR, Lophatananon A, Rattanamongkongul S, Puttawibul P, Fasching PA, Hein A, Ekici AB, Beckmann MW, Fletcher O, Johnson N, dos Santos Silva I, Peto J, Sawyer E, Tomlinson I, Kerin M, Miller N, Marmee F, Schneeweiss A, Sohn C, Burwinkel B, et al: Comparison of 6q25 breast cancer hits from Asian and European Genome Wide Association Studies in the Breast Cancer Association Consortium (BCAC). PLoS One. 2012, 7: e42380-10.1371/journal.pone.0042380.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Zheng W, Zhang B, Cai Q, Sung H, Michailidou K, Shi J, Choi JY, Long J, Dennis J, Humphreys MK, Wang Q, Lu W, Gao YT, Li C, Cai H, Park SK, Yoo KY, Noh DY, Han W, Dunning AM, Benitez J, Vincent D, Bacot F, Tessier D, Kim SW, Lee MH, Lee JW, Lee JY, Xiang YB, Zheng Y, et al: Common genetic determinants of breast-cancer risk in East Asian women: a collaborative study of 23 637 breast cancer cases and 25 579 controls. Hum Mol Genet. 2013, 22: 2539-2550. 10.1093/hmg/ddt089.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Stacey SN, Sulem P, Zanon C, Gudjonsson SA, Thorleifsson G, Helgason A, Jonasdottir A, Besenbacher S, Kostic JP, Fackenthal JD, Huo D, Adebamowo C, Ogundiran T, Olson JE, Fredericksen ZS, Wang X, Look MP, Sieuwerts AM, Martens JW, Pajares I, Garcia-Prats MD, Ramon-Cajal JM, de Juan A, Panadero A, Ortega E, Aben KK, Vermeulen SH, Asadzadeh F, van Engelenburg KC, Margolin S, et al: Ancestry-shift refinement mapping of the C6orf97-ESR1 breast cancer susceptibility locus. PLoS Genet. 2010, 6: e1001029-10.1371/journal.pgen.1001029.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Dai J, Hu Z, Jiang Y, Shen H, Dong J, Ma H: Breast cancer risk assessment with five independent genetic variants and two risk factors in Chinese women. Breast Cancer Res. 2012, 14: R17-10.1186/bcr3101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Thomas C, Gustafsson JA: The different roles of ER subtypes in cancer biology and therapy. Nat Rev Cancer. 2011, 11: 597-608. 10.1038/nrc3093.

    Article  CAS  PubMed  Google Scholar 

  14. Holst F, Stahl PR, Ruiz C, Hellwinkel O, Jehan Z, Wendland M, Lebeau A, Terracciano L, Al-Kuraya K, Jänicke F, Sauter G, Simon R: Estrogen receptor ? (ESR1) gene amplification is frequent in breast cancer. Nat Genet. 2007, 39: 655-660. 10.1038/ng2006.

    Article  CAS  PubMed  Google Scholar 

  15. Han J, Jiang T, Bai H, Gu H, Dong J, Ma H, Hu Z, Shen H: Genetic variants of 6q25 and breast cancer susceptibility: a two-stage fine mapping study in a Chinese population. Breast Cancer Res Treat. 2011, 129: 901-907. 10.1007/s10549-011-1527-x.

    Article  PubMed  Google Scholar 

  16. Qin Z, Xue J, He Y, Ma H, Jin G, Chen J, Hu Z, Liu X, Shen H: Potentially functional polymorphisms in ATG10 are associated with risk of breast cancer in a Chinese population. Gene. 2013, 527: 491-495. 10.1016/j.gene.2013.06.067.

    Article  CAS  PubMed  Google Scholar 

  17. Xu Z, Taylor JA: SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res. 2009, 37: W600-W605. 10.1093/nar/gkp290.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Expression quantitative trait locus (eQTL) browser at the Pritchard lab. [] (accessed 22 August 2014)., [http://eqtl.uchicago.edu/cgi-bin/gbrowse/eqtl/]

  19. Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, Castagne R, Maouche S, Germain M, Lackner K, Rossmann H, Eleftheriadis M, Sinning CR, Schnabel RB, Lubos E, Mennerich D, Rust W, Perret C, Proust C, Nicaud V, Loscalzo J, Hübner N, Tregouet D, Münzel T, Ziegler A, Tiret L, Blankenberg S, Cambien F: Genetics and beyond-the transcriptome of human monocytes and disease susceptibility. PLoS One. 2010, 5: e10693-10.1371/journal.pone.0010693.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, Karczewski KJ, Park J, Hitz BC, Weng S, Cherry JM, Snyder M: Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012, 22: 1790-1797. 10.1101/gr.137323.112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cai Q, Wen W, Qu S, Li G, Egan KM, Chen K, Deming SL, Shen H, Shen CY, Gammon MD, Blot WJ, Matsuo K, Haiman CA, Khoo US, Iwasaki M, Santella RM, Zhang L, Fair AM, Hu Z, Wu PE, Signorello LB, Titus-Ernstoff L, Tajima K, Henderson BE, Chan KY, Kasuga Y, Newcomb PA, Zheng H, Cui Y, Wang F, et al: Replication and functional genomic analyses of the breast cancer susceptibility locus at 6q25.1 generalize its importance in women of Chinese, Japanese, and European ancestry. Cancer Res. 2011, 71: 1344-1355. 10.1158/0008-5472.CAN-10-2733.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fletcher O, Johnson N, Orr N, Hosking FJ, Gibson LJ, Walker K, Zelenika D, Gut I, Heath S, Palles C, Coupland B, Broderick P, Schoemaker M, Jones M, Williamson J, Chilcott-Burns S, Tomczyk K, Simpson G, Jacobs KB, Chanock SJ, Hunter DJ, Tomlinson IP, Swerdlow A, Ashworth A, Ross G, dos Santos Silva I, Lathrop M, Houlston RS, Peto J: Novel breast cancer susceptibility locus at 9q31.2: results of a genome-wide association study. J Natl Cancer Inst. 2011, 103: 425-435. 10.1093/jnci/djq563.

    Article  CAS  PubMed  Google Scholar 

  23. Styrkarsdottir U, Halldorsson BV, Gretarsdottir S, Gudbjartsson DF, Walters GB, Ingvarsson T, Jonsdottir T, Saemundsdottir J, Center JR, Nguyen TV, Bagger Y, Gulcher JR, Eisman JA, Christiansen C, Sigurdsson G, Kong A, Thorsteinsdottir U, Stefansson K: Multiple genetic loci for bone mineral density and fractures. N Engl J Med. 2008, 358: 2355-2365. 10.1056/NEJMoa0801197.

    Article  CAS  PubMed  Google Scholar 

  24. Estrada K, Styrkarsdottir U, Evangelou E, Hsu YH, Duncan EL, Ntzani EE, Oei L, Albagha OM, Amin N, Kemp JP, Koller DL, Li G, Liu CT, Minster RL, Moayyeri A, Vandenput L, Willner D, Xiao SM, Yerges-Armstrong LM, Zheng HF, Alonso N, Eriksson J, Kammerer CM, Kaptoge SK, Leo PJ, Thorleifsson G, Wilson SG, Wilson JF, Aalto V, Alen M, et al: Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat Genet. 2012, 44: 491-501. 10.1038/ng.2249.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Dunbier AK, Anderson H, Ghazoui Z, Lopez-Knowles E, Pancholi S, Ribas R, Drury S, Sidhu K, Leary A, Martin LA, Dowsett M: ESR1 is co-expressed with closely adjacent uncharacterised genes spanning a breast cancer susceptibility locus at 6q25.1. PLoS Genet. 2011, 7: e1001382-10.1371/journal.pgen.1001382.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Zhu H, Wu H, Liu X, Evans BR, Medina DJ, Liu CG, Yang JM: Role of microRNA miR-27a and miR-451 in the regulation of MDR1/P-glycoprotein expression in human cancer cells. Biochem Pharmacol. 2008, 76: 582-588. 10.1016/j.bcp.2008.06.007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liu T, Tang H, Lang Y, Liu M, Li X: MicroRNA-27a functions as an oncogene in gastric adenocarcinoma by targeting prohibitin. Cancer Lett. 2009, 273: 233-242. 10.1016/j.canlet.2008.08.003.

    Article  CAS  PubMed  Google Scholar 

  28. Mertens-Talcott SU, Chintharlapalli S, Li X, Safe S: The oncogenic microRNA-27a targets genes that regulate specificity protein transcription factors and the G2-M checkpoint in MDA-MB-231 breast cancer cells. Cancer Res. 2007, 67: 11001-11011. 10.1158/0008-5472.CAN-07-2416.

    Article  CAS  PubMed  Google Scholar 

  29. Portal MM: MicroRNA-27a regulates basal transcription by targeting the p44 subunit of general transcription factor IIH. Proc Natl Acad Sci U S A. 2011, 108: 8686-8691. 10.1073/pnas.1014018108.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Tang W, Zhu J, Su S, Wu W, Liu Q, Su F, Yu F: MiR-27 as a prognostic marker for breast cancer progression and patient survival. PLoS One. 2012, 7: e51702-10.1371/journal.pone.0051702.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Li N, Dong J, Hu Z, Shen H, Dai M: Potentially functional polymorphisms in ESR1 and breast cancer risk: a meta-analysis. Breast Cancer Res Treat. 2010, 121: 177-184. 10.1007/s10549-009-0532-9.

    Article  CAS  PubMed  Google Scholar 

  32. Dunning AM, Healey CS, Baynes C, Maia AT, Scollen S, Vega A, Rodríguez R, Barbosa-Morais NL, Ponder BAJ, Low YL, Bingham S, Haiman CA, Le Marchand L, Broeks A, Schmidt MK, Hopper J, Southey M, Beckmann MW, Fasching PA, Peto J, Johnson N, Bojesen SE, Nordestgaard B, Milne RL, Benitez J, Hamann U, Ko Y, Schmutzler RK, Burwinkel B, Schürmann P, et al: Association of ESR1 gene tagging SNPs with breast cancer risk. Hum Mol Genet. 2009, 18: 1131-1139. 10.1093/hmg/ddn429.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Klinge CM: Estrogen receptor interaction with co-activators and co-repressors. Steroids. 2000, 65: 227-251. 10.1016/S0039-128X(99)00107-5.

    Article  CAS  PubMed  Google Scholar 

  34. Sauna ZE, Kimchi-Sarfaty C: Understanding the contribution of synonymous mutations to human disease. Nat Rev Genet. 2011, 12: 683-691. 10.1038/nrg3051.

    Article  CAS  PubMed  Google Scholar 

  35. Nackley AG, Shabalina SA, Tchivileva IE, Satterfield K, Korchynskyi O, Makarov SS, Maixner W, Diatchenko L: Human catechol-O-methyltransferase haplotypes modulate protein expression by altering mRNA secondary structure. Science. 2006, 314: 1930-1933. 10.1126/science.1131262.

    Article  CAS  PubMed  Google Scholar 

  36. Lian J, Tian H, Liu L, Zhang XS, Li WQ, Deng YM, Yao GD, Yin MM, Sun F: Downregulation of microRNA-383 is associated with male infertility and promotes testicular embryonal carcinoma cell proliferation by targeting IRF1. Cell Death Dis. 2010, 1: e94-10.1038/cddis.2010.70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to all the participants and researchers for their contributions and commitment to this study. Funding support for this project was provided by the National Natural Science Foundation of China (81071715 and 81102179), the Key Project of the National Natural Science Foundation of China (81230067), a key grant from the Natural Science Foundation of Jiangsu Higher Education Institutions (09KJA330001), the Program for Changjiang Scholars and Innovative Research Team in University (IRT0631), the Young Talents Support Program of the Organization Department of the CPC Central Committee and the Priority Academic Program of the Development of Jiangsu Higher Education Institutions (Public Health and Preventive Medicine). The authors thank Dr Qingyi Wei of the Duke Cancer Institute for language editing.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Zhibin Hu, Xiaoxiang Guan or Hongbing Shen.

Additional information

Competing interests

The authors declare that they have no competing interests.

Electronic supplementary material

13058_2014_422_MOESM1_ESM.jpeg

Additional file 1: Figure S1.: Overview of the 6q25.1 region (chr6:151767683-152466099) from the UCSC Genome Browser (NCBI36/hg18). The upper panel shows the 698.4-kb region in 6q25.1 contain four genes: RMND1, C6orf211, CCDC170 and ESR1. The lower panel shows linkage disequilibrium (LD) plots of 31 SNPs in LD with rs2046210 and 6 selected functional SNPs marked with an asterisk. LD values between SNPs as indicated in the diamonds were measured by r2 in Chinese descent (CHB). For example, the r2 value between rs2046210 and rs9383935 was 0.86 in CHB. (JPEG 665 KB)

Additional file 2: Figure S2.: The construction of CCDC170 3' UTR luciferase reporter plasmid. (JPEG 219 KB)

13058_2014_422_MOESM3_ESM.jpeg

Additional file 3: Figure S3.: The predicted binding affinity of miR-27a-3p and CCDC170 3' UTR. The figures and the values of minimum free energy (MFE) were generated in RNAhybrid (http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/). Different alleles of rs9383935 are marked with squares. (JPEG 102 KB)

Authors’ original submitted files for images

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Y., He, Y., Qin, Z. et al. Evaluation of functional genetic variants at 6q25.1 and risk of breast cancer in a Chinese population. Breast Cancer Res 16, 422 (2014). https://0-doi-org.brum.beds.ac.uk/10.1186/s13058-014-0422-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s13058-014-0422-x

Keywords