Ghoussaini Maya, French Juliet D, Michailidou Kyriaki, Nord Silje, Beesley Jonathan, Canisus Sander, Hillman Kristine M, Kaufmann Susanne, Sivakumaran Haran, Moradi Marjaneh Mahdi, Lee Jason S, Dennis Joe, Bolla Manjeet K, Wang Qin, Dicks Ed, Milne Roger L, Hopper John L, Southey Melissa C, Schmidt Marjanka K, Broeks Annegien, Muir Kenneth, Lophatananon Artitaya, Fasching Peter A, Beckmann Matthias W, Fletcher Olivia, Johnson Nichola, Sawyer Elinor J, Tomlinson Ian, Burwinkel Barbara, Marme Frederik, Guénel Pascal, Truong Thérèse, Bojesen Stig E, Flyger Henrik, Benitez Javier, González-Neira Anna, Alonso M Rosario, Pita Guillermo, Neuhausen Susan L, Anton-Culver Hoda, Brenner Hermann, Arndt Volker, Meindl Alfons, Schmutzler Rita K, Brauch Hiltrud, Hamann Ute, Tessier Daniel C, Vincent Daniel, Nevanlinna Heli, Khan Sofia, Matsuo Keitaro, Ito Hidemi, Dörk Thilo, Bogdanova Natalia V, Lindblom Annika, Margolin Sara, Mannermaa Arto, Kosma Veli-Matti, Wu Anna H, Van Den Berg David, Lambrechts Diether, Floris Giuseppe, Chang-Claude Jenny, Rudolph Anja, Radice Paolo, Barile Monica, Couch Fergus J, Hallberg Emily, Giles Graham G, Haiman Christopher A, Le Marchand Loic, Goldberg Mark S, Teo Soo H, Yip Cheng Har, Borresen-Dale Anne-Lise, Zheng Wei, Cai Qiuyin, Winqvist Robert, Pylkäs Katri, Andrulis Irene L, Devilee Peter, Tollenaar Rob A E M, García-Closas Montserrat, Figueroa Jonine, Hall Per, Czene Kamila, Brand Judith S, Darabi Hatef, Eriksson Mikael, Hooning Maartje J, Koppert Linetta B, Li Jingmei, Shu Xiao-Ou, Zheng Ying, Cox Angela, Cross Simon S, Shah Mitul, Rhenius Valerie, Choi Ji-Yeob, Kang Daehee, Hartman Mikael, Chia Kee Seng, Kabisch Maria, Torres Diana, Luccarini Craig, Conroy Don M, Jakubowska Anna, Lubinski Jan, Sangrajrang Suleeporn, Brennan Paul, Olswold Curtis, Slager Susan, Shen Chen-Yang, Hou Ming-Feng, Swerdlow Anthony, Schoemaker Minouk J, Simard Jacques, Pharoah Paul D P, Kristensen Vessela, Chenevix-Trench Georgia, Easton Douglas F, Dunning Alison M, Edwards Stacey L
Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK.
Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia.
Am J Hum Genet. 2016 Oct 6;99(4):903-911. doi: 10.1016/j.ajhg.2016.07.017. Epub 2016 Sep 15.
Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER) breast cancer (per-g allele OR ER = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER) breast cancer (lead SNP rs6864776: per-a allele OR ER = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10), and a single signal 3 SNP (rs200229088: per-t allele OR ER = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis.
全基因组关联研究（GWAS）已揭示5p12处多个基因变异与乳腺癌风险增加相关。在此，我们利用乳腺癌协会联盟（BCAC）中50项病例对照研究的104,660名受试者的数据，报告了该位点的精细定位。通过对1兆碱基区域（位置44,394,495 - 45,364,167；NCBI构建版本37）内3,365个基因分型和推算的单核苷酸多态性（SNP）的数据进行分析，我们发现了至少三个独立信号的证据：最强信号由单个SNP rs10941679组成，与雌激素受体阳性（ER）乳腺癌风险相关（每g等位基因OR ER = 1.15；95%置信区间1.13 - 1.18；p = 8.35 × 10）。在对rs10941679进行校正后，我们检测到信号2，由38个与雌激素受体阴性（ER）乳腺癌相关性更强的SNP组成（领先SNP rs6864776：每a等位基因OR ER = 1.10；95%置信区间1.05 - 1.14；p条件 = 1.44 × 10），以及单个信号3 SNP（rs200229088：每t等位基因OR ER = 1.12；95%置信区间1.09 - 1.15；p条件 = 1.12 × 10）。在正常乳腺组织和乳腺肿瘤中的表达数量性状位点分析表明，rs10941679的g（风险）等位基因与FGF10和MRPS30的表达增加相关。功能分析表明，SNP rs10941679定位于一个增强子元件，该元件在乳腺癌细胞系中与FGF10和MRPS30启动子区域发生物理相互作用。FGF10是一种癌基因，可与FGFR2结合，在约10%的人类乳腺癌中过表达，而MRPS30在细胞凋亡中起关键作用。这些数据表明，5p12处最强的关联信号是通过FGF10和MRPS30的协同激活介导的，这两个基因是乳腺癌发病机制的候选基因。
