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相关阅读 单核苷酸多态性（SNP）是指同一物种不同个体基因组DNA序列同一位置（等位序列）单个核苷酸存在差别的现象，是研究基因遗传变异的重要依据。人基因组平均约每1000个核苷酸即可能出现1个SNP变化，其中某些SNP可能与疾病有关。至少有94种常见的SNP与乳腺癌相关，既往研究尚未直接评估一系列SNP对接受预防疗法女性进行风险预测的精准化程度。 2016年12月28日，美国临床肿瘤学会官方期刊《临床肿瘤学杂志》在线发表伦敦玛丽王后大学、伦敦癌症研究院、皇家马斯登医院、伦敦癌症中心、曼彻斯特大学、英国克里斯蒂医院（欧洲最大的癌症中心）的研究报告，在两项他莫昔芬预防乳腺癌的随机研究中，分析了88种SNP对高危女性乳腺癌风险的影响。 该研究采用巢式（嵌套、重叠）病例对照，对国际乳腺癌干预研究（IBIS-I）或皇家马斯登研究中的女性，进行了基于88种SNP（SNP88）的风险评分。按年龄、临床研究、随访时间、治疗分组，将总计359位发生癌症的女性与636位对照者进行匹配，采用OncoArray进行基因分型，采用条件逻辑回归和匹配一致性指数（mC）衡量了单用SNP88以及联合蒂勒-库济克（TC）模型对于预测乳腺癌风险因素的能力。 结果发现，SNP88可以预测乳腺癌总风险（四分位范围比值比[IQ-OR]：1.37，95%置信区间：1.14～1.66，mC：0.55），但是主要对雌激素受体阳性病变（与非雌激素受体阴性病变相比，IQ-OR：1.44，95%置信区间：1.16～1.79，异质性P=0.10）。然而，SNP88观察到的风险仅为预期的46%（95%置信区间：19%～74%）。治疗组之间未见显著交互效应（安慰剂、他莫昔芬的IQ-OR分别为：1.46、1.25，95%置信区间分别为：1.13～1.87、0.96～1.64，异质性P=0.5）。SNP88的预测能力与TC模型（IQ-OR：1.45，95%置信区间：1.21～1.73，mC：0.55）相似，但是独立于TC模型（斯皮尔曼优势序位相关系数：0.012，P=0.7），两者强强联合时预测能力可见实质提高（IQ-OR：1.64，95%置信区间：1.36～1.97，mC：0.60）。 因此，对于乳腺癌风险居高并考虑预防疗法的女性，多基因风险评分可以提高TC或类似模型预测风险的精准程度，对于此类女性的精准风险评定可能需要再校对。 J Clin Oncol. 2016 Dec 28. [Epub ahead of print] Impact of a Panel of 88 Single Nucleotide Polymorphisms on the Risk of Breast Cancer in High-Risk Women: Results From Two Randomized Tamoxifen Prevention Trials. Cuzick J, Brentnall AR, Segal C, Byers H, Reuter C, Detre S, Lopez-Knowles E, Sestak I, Howell A, Powles TJ, Newman WG, Dowsett M. Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London; The Institute of Cancer Research; Royal Marsden Hospital; Cancer Centre London, London; University of Manchester and Central Manchester Foundation Trust; The Christie NHS Foundation Trust, Manchester, United Kingdom. Purpose: At least 94 common single nucleotide polymorphisms (SNPs) are associated with breast cancer. The extent to which an SNP panel can refine risk in women who receive preventive therapy has not been directly assessed previously. Materials and Methods: A risk score on the basis of 88 SNPs (SNP88) was investigated in a nested case-control study of women enrolled in the International Breast Intervention Study (IBIS-I) or the Royal Marsden study. A total of 359 women who developed cancer were matched to 636 controls by age, trial, follow-up time, and treatment arm. Genotyping was done using the OncoArray. Conditional logistic regression and matched concordance indices (mC) were used to measure the performance of SNP88 alone and with other breast cancer risk factors assessed using the Tyrer-Cuzick (TC) model. Results: SNP88 was predictive of breast cancer risk overall (interquartile range odds ratio [IQ-OR], 1.37; 95% CI, 1.14 to 1.66; mC, 0.55), but mainly for estrogen receptor-positive disease (IQ-OR, 1.44; 95% CI, 1.16 to 1.79; P for heterogeneity = .10) versus estrogen receptor-negative disease. However, the observed risk of SNP88 was only 46% (95% CI, 19% to 74%) of expected. No significant interaction was observed with treatment arm (placebo IQ-OR, 1.46; 95% CI, 1.13 to 1.87; tamoxifen IQ-OR, 1.25; 95% CI, 0.96 to 1.64; P for heterogeneity = .5). The predictive power was similar to the TC model (IQ-OR, 1.45; 95% CI, 1.21 to 1.73; mC, 0.55), but SNP88 was independent of TC (Spearman rank-order correlation, 0.012; P = .7), and when combined multiplicatively, a substantial improvement was seen (IQ-OR, 1.64; 95% CI, 1.36 to 1.97; mC, 0.60). Conclusion: A polygenic risk score may be used to refine risk from the TC or similar models in women who are at an elevated risk of breast cancer and considering preventive therapy. Recalibration may be necessary for accurate risk assessment. PMID: 28029312 DOI: 10.1200/JCO.2016.69.8944 |
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