Division of Oncology, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFMED UK), Slovakia.
Division of Oncology, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFMED UK), Slovakia; Clinic of Gynaecology and Obstetrics, Martin University Hospital, Slovakia.
J Biotechnol. 2019 Jun 20;299:1-7. doi: 10.1016/j.jbiotec.2019.04.014. Epub 2019 Apr 16.
Breast cancer (BC) development is caused by the interaction of environmental and genetic factors. At least 90 susceptible genetic variants with different population penetration and incidence have been associated with BC. This paper therefore analysed the individual discrimination power of 8 low penetrant common genetic variants and calculated the predictive accuracy of the genetic risk model. The study enrolled 171 women with developed breast cancer (57.06 ± 11.60 years) and 146 control subjects (50.24 ± 10.69 years). The genotyping was performed by high resolution melting method (HRM) and confirmed by Sanger sequencing, and the Random Forest algorithm provided the ROC curve with AUC values. Significant association with BC was confirmed in 2 SNPs: rs2981582 FGFR2 and rs889312 MAP3K1, and the odds ratios of homozygotes with two risk alleles in both SNP's were higher than in heterozygotes with one mutant allele, as follows: FGFR2 TT: 1.953 (95%CI 1.014-3.834, p = 0.049), CT 1.771 (95%CI 1.088-2.899, p = 0.026) and MAP3K1 CC 2.894 (95%CI 1.028-9.566, p = 0.048), AC 1.760 (95%CI 1.108-2.813, p = 0.019). FGFR2 had the best discrimination ability, followed by MAP3K1 and CASP8. Discriminative accuracy of the genetic risk model distinguishing the breast cancer patients and controls explained by AUC was 0.728, with 70.6% sensitivity and 65.1% specificity. Our study results therefore confirmed polygenic breast cancer inheritance with important involvement of FGFR2, MAP3K1, LSP1 and CASP8 gene variants.
乳腺癌（BC）的发生是由环境和遗传因素相互作用引起的。至少有 90 种易感遗传变异与 BC 有关，其在不同人群中的渗透率和发病率不同。本文因此分析了 8 种低穿透性常见遗传变异的个体判别能力，并计算了遗传风险模型的预测准确性。该研究纳入了 171 名患有乳腺癌的女性（57.06±11.60 岁）和 146 名对照受试者（50.24±10.69 岁）。基因分型采用高分辨率熔解法（HRM）进行，并通过 Sanger 测序进行确认，随机森林算法提供了具有 AUC 值的 ROC 曲线。rs2981582 FGFR2 和 rs889312 MAP3K1 这 2 个 SNP 与 BC 显著相关，且这两个 SNP 的纯合子携带两个风险等位基因的比值比杂合子携带一个突变等位基因的比值更高，如下所示：FGFR2 TT：1.953（95%CI 1.014-3.834，p=0.049），CT 1.771（95%CI 1.088-2.899，p=0.026）和 MAP3K1 CC 2.894（95%CI 1.028-9.566，p=0.048），AC 1.760（95%CI 1.108-2.813，p=0.019）。FGFR2 具有最佳的判别能力，其次是 MAP3K1 和 CASP8。AUC 解释的遗传风险模型区分乳腺癌患者和对照的判别准确率为 0.728，灵敏度为 70.6%，特异性为 65.1%。因此，我们的研究结果证实了多基因乳腺癌遗传，FGFR2、MAP3K1、LSP1 和 CASP8 基因变异具有重要作用。
