Genes, environment and breast cancer risk: The 15 year follow-up of the Prof-SC

描述（由申请人提供）：BRCA 1和BRCA 2的发现使乳腺癌的预防和筛查策略更有针对性。目前正在发现的具有中等风险突变的基因，以及具有常见低风险相关变异的多个基因座，意味着将发现更多具有重大遗传风险的女性。尽管基因组医学取得了这些进展，但对于高危女性来说，仍然存在一些悬而未决的问题，其中大多数人在任何目前确定的易感基因中都没有携带突变：1）我患乳腺癌的绝对风险是多少？2)有没有可以改变的因素可以降低我的风险？对于先前患有乳腺癌的女性，3）我能做些什么来降低患新癌症的风险吗？这些问题的答案是改善临床护理的基础，而且早就应该这样做了。我们缺乏这些重要问题的答案，因为许多研究未能捕捉到家族史的复杂性，并且缺乏长期随访数据来衡量风险。非专科诊所常用的乳腺癌风险预测模型通常仅基于一级家族史来捕获风险。没有乳腺癌预测模型是基于，也没有验证，大的前瞻性队列的高风险妇女。研究BRCA 1和BRCA 2突变携带者风险的潜在修饰因子的研究采用了回顾性设计，并包括对疾病幸存者过度采样的流行癌症。为了解决这些差距，我们建议对30，563名女性进行积极随访，其中2，597名是BRCA 1和BRCA 2突变携带者。这些妇女来自1995年以来在美国招募和跟踪的9,739个家庭，加拿大和澳大利亚。我们收集了这些妇女同样广泛的基线流行病学、多代系谱和遗传数据。我们的前瞻性家庭研究中，乳腺癌易感性增加的女性在潜在的家族风险特征（FRP）方面差异很大，可以使用多代系谱和遗传数据进行估计。我们将使用两个单独的队列（基线时18，530名未受影响的女性和12，033名受影响的女性）估计年龄特异性乳腺癌的绝对和相对风险，作为其估计FRP，可改变的风险因素以及BRCA 1和BRCA 2突变状态的函数。到随访结束时，我们估计1，427名未受影响的妇女和1，359名基线受影响的妇女将被诊断为新的乳腺癌。这些新病例中有15-17%将是BRCA 1或BRCA 2突变携带者。我们将利用我们的发现，通过整合来自多代家族史、测量的基因变异和风险因素的信息来增强预测模型。临床实践一直保守的建议高风险的妇女，特别是突变携带者，关于潜在的生活方式的改变，以减少风险，根据这一建议的研究，平均风险的妇女。相反，我们建议为所有风险范围内的女性建立更准确的预测模型，用于制定更有效的预防策略。

DESCRIPTION (provided by applicant): The discovery of BRCA1 and BRCA2 has resulted in more appropriate targeting of preventive and screening strategies for breast cancer. The on-going discovery of genes with moderate-risk mutations, and of multiple loci with common low-risk associated variants, means that more women at substantial genetic risk will be identified. Despite these advances in genomic medicine, there remain major unanswered questions for high risk women, the majority of whom do not carry mutations in any currently identified susceptibility genes: 1) What is my absolute risk of breast cancer?; 2) Are there modifiable factors that might lower my risk?; and, for women with prior breast cancer, 3) Can I do anything to lower my risk of a new cancer? Answers to these questions are fundamental to improving clinical care, and are long overdue. We lack answers to these important questions because many studies fail to capture the complexity of family history and lack long-term follow-up data to measure risk. Breast cancer risk prediction models commonly used at non-specialist clinics often capture risk based on only first-degree family history. No breast cancer prediction models have been based on, nor validated with, large prospective cohorts of high risk women. Studies that have examined potential modifiers of risk for BRCA1 and BRCA2 mutation carriers have used a retrospective design and included prevalent cancers over-sampled for disease survivors. To address these gaps, we propose to conduct active follow-up of 30,563 women of whom 2,597 are BRCA1 and BRCA2 mutation carriers. These women come from 9,739 families recruited and followed since 1995 in the U.S., Canada, and Australia. We collected the same extensive baseline epidemiologic, multigenerational pedigree, and genetic data for these women. Our prospective family study is enriched with women at increased susceptibility for breast cancer who vary widely in underlying Familial Risk Profile (FRP), which can be estimated using multigenerational pedigree and genetic data. We will estimate age-specific absolute, and relative, risks of breast cancer using two separate cohorts (18,530 women unaffected and 12,033 women affected at baseline), as a function of their estimated FRP, modifiable risk factors, and by BRCA1 and BRCA2 mutation status. By the end of follow-up, we estimate 1,427 of the women unaffected and 1,359 women affected at baseline will be diagnosed with a new breast cancer. 15-17% of these new cases will be in BRCA1 or BRCA2 mutation carriers. We will use our findings to enhance prediction models by incorporating information from multigenerational family history, measured gene variants, and risk factors. Clinical practice has been conservative in advising high risk women, particularly mutation carriers, about potential lifestyle modifications to reduce risk, basing this advice on studies of average-risk women. Instead, we propose to build more accurate prediction models for women across the spectrum of risk that can be used to tailor more effective prevention strategies.