All subjects included in this study were Han Chinese women. The mean ages of the patients and controls were 48.48 ± 10.18 and 44.59 ± 11.26 years, respectively. An independent-sample t-test indicated a significant difference in age distribution between the two groups (P < 0.05, data not shown), so all statistical analyses were subsequently adjusted by age.

All SNPs conformed to Hardy-Weinberg equilibrium (HWE) among both cases and controls (P > 0.05) with minor allele frequency (MAF) ≥ 0.22 (Table 1). The SNPs rs11638442, rs2073475, and rs16968478 were in high or complete linkage disequilibrium as well as rs2959003 and rs2279357 (supplementary material). D′ values are shown in Figure 1. The SNP rs2959008 had a low LD compared to the others.

Six main haplotypes of CYP11A1 were considered in the analysis for all subjects. The results of individual haplotype analysis and breast cancer are shown in Table 2. The haplotype TTTCAG was most common in both case and control groups. The distribution frequency of haplotype CCCCGA was significantly different between the two groups and protective against the development of breast cancer (OR, 0.64; 95% CI, 0.48–0.86; P = 0.0033).

The genotype distributions of rs2959008 and rs2279357 were significantly different between cases and controls in the chosen genetic model (Table 3). For rs2959008, the variant genotype C/T-C/C was significantly associated with a decreased risk of breast cancer (OR, 0.75; 95% CI, 0.58–0.96; P = 0.023) compared with the wild-type TT. Individuals carrying the C allele showed protection from breast cancer (OR, 0.80; 95% CI, 0.67–0.96; P = 0.018). In contrast to rs2959008, the homozygous TT variant and allele T of rs2279357 were associated with elevated susceptibility to breast cancer (OR, 1.44; 95% CI, 1.05–1.98; P = 0.022 and OR, 1.23; 95% CI, 1.04–1.47; P = 0.018, respectively). A correlation between the rs2959003 polymorphism and breast cancer was also observed under the log-additive model. Three other SNPs (rs11638442, rs2073475, and rs16968478) did not show significant differences between the groups in the present study (supplementary material).

A further association analysis was conducted to identify the interactions of two susceptibility-associated SNPs, rs2959008 and rs2279357, and their impact on the risk of breast cancer. The results indicated that the united genotype TT-TT of rs2959008 and rs2279357 showed increased breast cancer risk (OR, 1.65; 95% CI, 1.18–2.31; P = 0.003) (Table 4). There was also a marginal association between genotype CT/CC-TT and reduced breast cancer risk (OR, 0.12; 95% CI, 0.02–0.94; P = 0.044).

Breast cancer risk is partially determined by endogenous hormone levels [25]. Given the important role of P450scc in steroid sex hormone biosynthesis, this case-control study was performed among Han Chinese women in Guangdong province. All six SNPs (rs2959008, rs2959003, rs2279357, rs11638442, rs2073475 and rs16968478) are located in noncoding regions of CYP11A1, with the first four in introns and the latter two upstream of the gene. The results showed that rs2959008 and rs2279357 of the CYP11A1 gene were strongly associated with breast cancer risk, as well as the interaction of the two SNPs.

Numerous studies have examined CYP11A1 gene polymorphisms. The best studied region is the pentanucleotide [TTTTA]_n repeat (D15S520) located 528 bp upstream of the translational initiation site, which showed six common polymorphisms with four, six, seven, eight, nine, or ten [TTTTA] repeats. In the Chinese population, the main variants are the four-, six-, and eight-repeat alleles, which are correlated with risks of breast cancer [16,17] and polycystic ovarian syndrome [21]. The [TTTTA]₄ and [TTTTA]₆ alleles were also shown to be associated with prostate cancer in other ethnic groups [22,23]. However, the [(TAAAA)_n] polymorphism was different from common biallelic variations in the present study.

Setiawan et al. systematically evaluated genetic variations spanning 67 kb of CYP11A and suggested that common variations in CYP11A may be related to breast cancer susceptibility in a western Multiethnic Cohort Study, but no particular SNP or haplotype was identified as the most likely causal variant [18]. Mammographic density has also been shown to be a breast cancer risk factor, and is strongly associated with hormone exposure profile [26]. In Swedish women, our five tag SNPs (rs2959008, rs2959003, rs2279357, rs11638442, and rs16968478) were significantly related to mammographic density in single SNP analysis, but the relationship disappeared after correction for multiple testing [27]. Another three tag SNPs (rs4555110, rs3825944, and rs7173655) were significantly associated with increased (1.3–1.4-fold) endometrial cancer risk in women in Boston, USA [24]. Along with another 11 loci, polymorphisms of CYP11A1 were also confirmed to be associated with hypertension and blood pressure (BP) in the Japanese population, with the presence of more of these alleles indicating higher risk [28]. These results were mainly based on Western populations. Haplotype analysis indicated that the promoter haplotype of CYP11A1 was associated with increased risk of breast cancer among Chinese women in Shanghai, but three of our SNPs (rs2959008, rs2959003, and rs16968478) were not included [19]. Here, we focused on the Han Chinese population in Guangdong province and identified breast cancer-related SNPs. Six SNPs that have seldom been reported in the Han Chinese population were selected to verify the association. The results suggested that the haplotype CCCCGA had a protective effect against breast cancer. Two single SNPs, rs2959008 and rs2279357, were significantly associated with breast cancer risk and interaction analysis also demonstrated that the united genotype TT-TT of these two SNPs showed much higher risk of breast cancer.

The subjects participated in our study were recruited between April 2009 and October 2011 from Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China. All participants were permanent residents of Guangdong from the Han Chinese population. Clinical information for each subject was collected from medical records.

Peripheral blood samples were collected from the participants and stored at −70 °C until DNA extraction. Genomic DNA was extracted from peripheral blood samples using an E.Z.N.A.™ blood DNA kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s protocol.

For each SNP, a pair of amplification primers and an extension primer was designed using Assay Design 3.1 software (Sequenom, San Diego, CA, USA). Genotypes were generated using the SEQUENOM MassARRAY matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry platform (Sequenom, San Diego, CA, USA) according to the manufacturer’s instructions. This is one of the most powerful tools for detecting insertions, deletions, substitutions, and other polymorphisms in amplified DNA, and allows rapid, efficient, and high-throughput detection without any interactions. The overall call rates ranged from 99.63% to 100%.

Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium (LD) for the six SNPs were calculated using Haploview 4.2 (Daly Lab, Cambridge, MA, USA). The genotype and allele distributions as well as the interactions of SNPs between case and control subjects were compared. Multiple inheritance models (codominant, dominant, recessive, overdominant, and log-additive) were chosen to evaluate the associations between each SNP and breast cancer risk. The odds ratio (OR) and 95% confidence interval (95% CI) were evaluated by binary logistic regression analyses. There was a significant difference in age distribution between case and control groups as described previously, so the age was adjusted by setting as a covariate in association analyses for each SNP. Statistical analyses were implemented using SPSS 13.0 software (SPSS, Chicago, IL, USA) and the Web-based tool SNPstats [29]. All comparisons were two-sided and P < 0.05 was regarded as statistically significant.