Han Mi-Ryung, Deming-Halverson Sandra, Cai Qiuyin, Wen Wanqing, Shrubsole Martha J, Shu Xiao-Ou, Zheng Wei, Long Jirong
Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, 8th Floor, Nashville, TN, 37203-1738, USA.
Breast Cancer. 2015 Sep;22(5):544-51. doi: 10.1007/s12282-014-0518-2. Epub 2014 Feb 9.
Genome-wide association studies have discovered multiple genetic loci associated with breast cancer risk. Investigating these loci would be helpful to evaluate previous findings and identify causal variants for breast cancer. We evaluated index SNPs in 17 of these loci in a study of 1,511 cases and 1,454 controls of European descent.
We investigated the overall association with breast cancer and among subtypes defined as ER+ (estrogen receptor positive), ER- (estrogen receptor negative) and triple-negative breast cancer (TNBC). Combined effects of SNPs on breast cancer risk were assessed via a genetic risk score. We evaluated the contribution of both genetic variants and traditional risk factors to a breast cancer risk assessment model.
Five of the 17 SNPs were significantly associated (P ≤ 0.05) with overall breast cancer in the same direction as previously reported: rs13387042 (2q35/TNP1), rs4973768 (3p24/SLC4A7), rs2046210 (6q25/ESR1), rs1219648 (10q26/FGFR2), and rs4784227 (16q12/TOX3). When stratified by breast cancer subtype, all five SNPs were associated (P < 0.05) with ER+ cancer, three with ER- cancer (rs13387042, rs1219648, and rs4784227), and one with TNBC (rs1219648). A GRS, based on those five significant SNPs, showed strong association with overall breast cancer with ORs (95 % CI) of 1.48 (1.22-1.79), 1.85 (1.52-2.25) and 2.26 (1.82-2.80), respectively, for each quartile, (P = 2.0 × 10(-15)). Traditional risk factors, including previous benign breast disease, breast cancer family history and parity, were significantly associated with breast cancer risk in the present study. These factors, together with the GRS, were used to build a breast cancer risk assessment model with a c statistic of 0.6321 from receiver operating characteristic analysis. The contribution of the GRS to the model was greater than prior benign breast disease, family history and parity with the c statistic change of 0.0374, 0.0324, 0.0103, 0.0012, respectively.
Our study demonstrates that five SNPs were associated with overall breast cancer, with stronger association for ER+ than ER- cancer as previously reported, and suggests that a risk assessment model incorporating the GRS from five loci is useful in identifying women at high risk of breast cancer.
全基因组关联研究已发现多个与乳腺癌风险相关的基因位点。对这些位点进行研究将有助于评估既往研究结果,并确定乳腺癌的因果变异。我们在一项针对1511例病例和1454例欧洲血统对照的研究中,对其中17个位点的索引单核苷酸多态性(SNP)进行了评估。
我们研究了这些SNP与乳腺癌的总体关联,以及在雌激素受体阳性(ER+)、雌激素受体阴性(ER-)和三阴性乳腺癌(TNBC)等亚型中的关联。通过遗传风险评分评估SNP对乳腺癌风险的综合影响。我们评估了基因变异和传统风险因素对乳腺癌风险评估模型的贡献。
17个SNP中的5个与总体乳腺癌显著相关(P≤0.05),方向与先前报道一致:rs13387042(2q35/TNP1)、rs4973768(3p24/SLC4A7)、rs2046210(6q25/ESR1)、rs1219648(10q26/FGFR2)和rs4784227(16q12/TOX3)。按乳腺癌亚型分层时,所有5个SNP均与ER+癌相关(P<0.05),3个与ER-癌相关(rs13387042、rs1219648和rs4784227),1个与TNBC相关(rs1219648)。基于这5个显著SNP的遗传风险评分显示与总体乳腺癌有很强的关联,每四分位数的比值比(95%可信区间)分别为1.48(1.22 - 1.79)、1.85(1.52 - 2.25)和2.26(1.82 - 2.80),(P = 2.0×10-15)。在本研究中,包括既往乳腺良性疾病、乳腺癌家族史和生育情况在内的传统风险因素与乳腺癌风险显著相关。这些因素与遗传风险评分一起用于构建乳腺癌风险评估模型,通过受试者工作特征分析,该模型的c统计量为0.6321。遗传风险评分对模型的贡献大于既往乳腺良性疾病、家族史和生育情况,c统计量的变化分别为0.0374、0.0324、0.0103、0.0012。
我们的研究表明,5个SNP与总体乳腺癌相关,与先前报道一致,ER+癌的关联强于ER-癌,并提示包含来自5个位点的遗传风险评分的风险评估模型有助于识别乳腺癌高危女性。