Barrdahl Myrto, Canzian Federico, Lindström Sara, Shui Irene, Black Amanda, Hoover Robert N, Ziegler Regina G, Buring Julie E, Chanock Stephen J, Diver W Ryan, Gapstur Susan M, Gaudet Mia M, Giles Graham G, Haiman Christopher, Henderson Brian E, Hankinson Susan, Hunter David J, Joshi Amit D, Kraft Peter, Lee I-Min, Le Marchand Loic, Milne Roger L, Southey Melissa C, Willett Walter, Gunter Marc, Panico Salvatore, Sund Malin, Weiderpass Elisabete, Sánchez María-José, Overvad Kim, Dossus Laure, Peeters Petra H, Khaw Kay-Tee, Trichopoulos Dimitrios, Kaaks Rudolf, Campa Daniele
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Int J Cancer. 2015 Dec 15;137(12):2837-45. doi: 10.1002/ijc.29446. Epub 2015 Aug 14.
The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele =0.70; 95% CI: 0.58-0.85; ptrend = 2.84 × 10(-4) ; HRheterozygotes = 0.71; 95% CI: 0.55-0.92; HRhomozygotes = 0.48; 95% CI: 0.31-0.76; p2DF = 1.45 × 10(-3) ). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend = 6.6 × 10(-4) ; HRheterozygotes = 0.96 95% CI: 0.90-1.03; HRhomozygotes = 1.21; 95% CI: 1.09-1.35; p2DF =1.25 × 10(-4) ). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.
乳腺癌患者的生存情况在很大程度上受肿瘤特征影响，如TNM分期、肿瘤分级和激素受体状态。然而，越来越多的证据表明，遗传基因变异可能会影响疾病预后和对治疗的反应。有几条证据表明，影响乳腺癌风险的等位基因可能也与乳腺癌生存相关。我们在来自美国国立癌症研究所乳腺癌和前列腺癌队列联盟（BPC3）的10255例乳腺癌患者中，研究了35个乳腺癌易感位点与疾病总生存（OS）之间的关联，其中1379例死亡，包括754例死于乳腺癌。我们还对近35000例患者和5000例死亡病例进行了荟萃分析，将BPC3和乳腺癌协会联盟（BCAC）的结果合并，并对具有显著关联的单核苷酸多态性（SNP）进行了计算机模拟分析。在BPC3中，LSP1-rs3817198的C等位基因与OS改善显著相关（每等位基因风险比=0.70；95%置信区间：0.58-0.85；趋势p=2.84×10⁻⁴；杂合子风险比=0.71；95%置信区间：0.55-0.92；纯合子风险比=0.48；95%置信区间：0.31-0.76；p₂DF=1.45×10⁻³）。在计算机模拟分析中，预测LSP1-rs3817198的C等位基因可增加肿瘤抑制因子细胞周期蛋白依赖性激酶抑制剂1C（CDKN1C）的表达。在荟萃分析中，TNRC9-rs3803662与死亡风险增加显著相关（荟萃分析风险比=1.09；95%置信区间：1.04-1.15；趋势p=6.6×10⁻⁴；杂合子风险比=0.96，95%置信区间：0.90-1.03；纯合子风险比=1.21；95%置信区间：1.09-1.35；p₂DF=1.25×10⁻⁴）。总之，我们表明，到目前为止所确定的乳腺癌风险单核苷酸多态性（SNP）与乳腺癌预后相关的SNP之间几乎没有重叠，LSP1-rs3817198和TNRC9-rs3803662可能为例外。
