| Breast cancer is the most common cancer and the leading cause of cancer related death among women worldwide, accounting for 23%. Although the incidence rate of breast cancer in China is about one-third of that in the United States, it has been significantly increasing dramatically in recent years in both urban and rural areas, especially in big cities such as Shanghai, Beijing and et al. Breast cancer has already been one of main causes contributing to disease related deaths and a serious one to be resolved in public health. However, the exact mechanisms of breast cancer are still unclear. It is well accepted that the etiology of breast cancer appears to entail a complex combination of genetic and environmental.Although life/environment related factors are implicated in breast carcinogenesis, it is a complex polygenic disorder in which genetic makeup also play an important role. In the past decades, high-penetrance genes (e.g., BRCA1, BRCA2, PTEN and TP53) have been identified to be associated with familiar breast cancer. However, these genes account for less than 5% of overall breast cancer patients and most of the risk is likely to be attributable to more low-penetrance variants, whose effects may range from small to moderate (OR=1.1-1.5). Genome-wide Association Study (GWAS), emerging with the completion of Human Genome Project and promotion of HapMap as well as advances in genotyping technology, is one of the powerful tools for genetic susceptibility study in complex diseases, including breast cancer. Recently, several genome-wide association studies (GWAS) have identified novel breast cancer risk single nucleotide polymorphisms (SNPs). However, most of the studies were conducted among Caucasians, and whether these genetic variants are applicable marker SNPs in Asian women is unclear.In the current study, a two-stage case-control study of 1792 breast cancer cases and 1867 cancer-free controls was conducted among Chinese women. We tested firstly whether 15 SNPs identified by previous GWAS were also breast cancer marker SNPs in Chinese. Then, we grouped the marker SNPs, and modeled them with clinical risk factors, to see the usage of these factors in breast cancer risk assessment. Five SNPs located at 2q35, 3p24, 6q22, 6q25 and 10q26 were consistently associated with breast cancer risk in our two-stage case control analyses. Overall, the five SNPs all contributed to breast cancer susceptibility in dominant genetic model (2q35, rs13387042: adjusted OR=1.26, P=0.006; 3q24.1, rs2307032: adjusted OR=1.24, P=0.005; 6q22.33, rs2180341: adjusted OR=1.22, P=0.006; 6q25.1, rs2046210: adjusted OR=1.51, P=2.40×10-8; 10q26.13, rs2981582: adjusted OR=1.31, P=1.96×10-4). Two methods, one by risk factors counting and another by OR weighted risk scoring, were used to evaluate the cumulative effects of the 5 significant SNPs and two clinical risk factors (age at menarche and age at first live birth). Risk score analyses (AUC: 0.641, 95%CI: 0.622-0.659) presented better discrimination than that by risk factors counting (AUC: 0.624, 95%CI: 0.608-0.642) (P<0.0001). Absolute risk was then calculated by the modified Gail. model and an AUC of 0.653 (95% CI=0.635-0.671) was obtained for the combination of 5 marker SNPs, age at menarche and age at first live birth. This study shows that some GWAS identified variants from Caucasians can be used in our Chinese population and combined considerations of these genetic variants can improve the risk predictive ability of breast cancer. However, more breast cancer associated risk variants should be incorporated to optimize the risk assessment. |
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