Breast cancer risk assessment with five independent genetic variants and two risk factors in chinese women
Cette étude évalue l'association entre 15 polymorphismes à simple nucléotide, déjà identifiés dans des études sur des populations caucasiennes, et le risque de cancer du sein chez des populations chinoises, en prenant en compte les critères d'âge à la ménopause et lors de la première grossesse
INTRODUCTION:Recently, several genome-wide association studies (GWAS) have identified novel single nucleotide polymorphisms (SNPs) associated with breast cancer risk. However, most of the studies were conducted among Caucasians and only one from Chinese.METHODS:In the current study, we first tested whether 15 SNPs identified by previous GWAS were also breast cancer marker SNPs in this Chinese population. 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. Two methods (risk factors counting and 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).RESULTS:Five SNPs located at 2q35, 3p24, 6q22, 6q25 and 10q26 were consistently associated with breast cancer risk in both testing set (878 cases and 900 controls) and validation set (914 cases and 967 controls) samples. Overall, all of the five SNPs 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=2.40x10-8; 10q26.13, rs2981582: adjusted OR=1.31, P=1.96x10-4). Risk score analyses (AUC: 0.649, 95%CI: 0.631-0.667; sensitivity=62.60%, specificity=57.05%) presented better discrimination than that by risk factors counting (AUC: 0.637, 95%CI: 0.619-0.655; sensitivity=62.16%, specificity=60.03%) (P<0.0001). Absolute risk was then calculated by the modified Gail model and an AUC of 0.658 (95% CI=0.640-0.676) (sensitivity=61.98%, specificity=60.26%) was obtained for the combination of 5 marker SNPs, age at menarche and age at first live birth.CONCLUSIONS:This study shows that 5 GWAS identified variants were also consistently validated in this Chinese population and combining these genetic variants with other risk factors can improve the risk predictive ability of breast cancer. However, more breast cancer associated risk variants should be incorporated to optimize the risk assessment.