英國(guó)《自然》雜志5月27日在線發(fā)表的術(shù)報(bào)告稱,，英美等國(guó)科學(xué)家的一項(xiàng)聯(lián)合研究發(fā)現(xiàn)，婦女體內(nèi)的4個(gè)基因發(fā)生變異,，就會(huì)增加患乳腺癌的風(fēng)險(xiǎn),。
科學(xué)家們通過(guò)對(duì)2.2萬(wàn)名患乳腺癌的婦女和2.2萬(wàn)名健康婦女進(jìn)行基因分析,，經(jīng)過(guò)多次篩選和鑒別，最終他們確信找到了4個(gè)能夠致人患乳腺癌的基因：FGFR2,、TNRC9,、MAP3K1和LSP1。
研究說(shuō),，如果婦女體內(nèi)的FGFR2和TNRC9基因中,，任何一個(gè)發(fā)生變異，她患乳腺癌的幾率將高出20%,；如果兩個(gè)基因均發(fā)生變異，她的患病幾率將高出40%至60%,；體內(nèi)MAP3K1或LSP1基因發(fā)生變異的婦女患病幾率則比常人高10%,。科學(xué)家們認(rèn)為,，此次發(fā)現(xiàn)的重要意義在于,，它不僅為基因療法治療乳腺癌打開(kāi)了一扇大門(mén)，也有助于醫(yī)學(xué)界利用基因分析法治療其他癌癥,。“我們希望,，這項(xiàng)研究可以幫助我們更好地了解乳腺癌背后隱藏的機(jī)理和生物學(xué)特征，從而使我們找到預(yù)防和治療乳腺癌的更好方法,。”
原始出處:
Nature advance online publication 27 May 2007 | doi:10.1038/nature05887; Received 9 February 2007; Accepted 30 April 2007; Published online 27 May 2007
Genome-wide association study identifies novel breast cancer susceptibility loci
Correspondence to: Douglas F. Easton1 Correspondence and requests for materials should be addressed to D.F.E. (Email: [email protected]).
Douglas F. Easton1, Karen A. Pooley2, Alison M. Dunning2, Paul D. P. Pharoah2, Deborah Thompson1, Dennis G. Ballinger3, Jeffery P. Struewing4, Jonathan Morrison2, Helen Field2, Robert Luben5, Nicholas Wareham5, Shahana Ahmed2, Catherine S. Healey2, Richard Bowman6The SEARCH collaborators and , Kerstin B. Meyer7, Christopher A. Haiman8, Laurence K. Kolonel9, Brian E. Henderson8, Loic Le Marchand9, Paul Brennan10, Suleeporn Sangrajrang11, Valerie Gaborieau10, Fabrice Odefrey10, Chen-Yang Shen12, Pei-Ei Wu12, Hui-Chun Wang12, Diana Eccles13, D. Gareth Evans14, Julian Peto15, Olivia Fletcher16, Nichola Johnson16, Sheila Seal17, Michael R. Stratton17,18, Nazneen Rahman17, Georgia Chenevix-Trench19, Stig E. Bojesen20, Børge G. Nordestgaard20, Christen K. Axelsson21, Montserrat Garcia-Closas22, Louise Brinton22, Stephen Chanock23, Jolanta Lissowska24, Beata Peplonska25, Heli Nevanlinna26, Rainer Fagerholm26, Hannaleena Eerola26,27, Daehee Kang28, Keun-Young Yoo28,29, Dong-Young Noh28, Sei-Hyun Ahn30, David J. Hunter31,32, Susan E. Hankinson32, David G. Cox31, Per Hall33, Sara Wedren33, Jianjun Liu34, Yen-Ling Low34, Natalia Bogdanova35,36, Peter Schürmann36, Thilo Dörk36, Rob A. E. M. Tollenaar37, Catharina E. Jacobi38, Peter Devilee39, Jan G. M. Klijn40, Alice J. Sigurdson41, Michele M. Doody41, Bruce H. Alexander42, Jinghui Zhang4, Angela Cox43, Ian W. Brock43, Gordon MacPherson43, Malcolm W. R. Reed44, Fergus J. Couch45, Ellen L. Goode45, Janet E. Olson45, Hanne Meijers-Heijboer46,47, Ans van den Ouweland47, André Uitterlinden48, Fernando Rivadeneira48, Roger L. Milne49, Gloria Ribas49, Anna Gonzalez-Neira49, Javier Benitez49, John L. Hopper50, Margaret McCredie51, Melissa Southey50, Graham G. Giles52, Chris Schroen53, Christina Justenhoven54, Hiltrud Brauch54, Ute Hamann55, Yon-Dschun Ko56, Amanda B. Spurdle19, Jonathan Beesley19, Xiaoqing Chen19kConFab and AOCS Management Group and , Arto Mannermaa118,119, Veli-Matti Kosma118,119, Vesa Kataja118,120, Jaana Hartikainen118,119, Nicholas E. Day65, David R. Cox63 & Bruce A. J. Ponder62,67
Abstract
Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2 > 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P < 10-7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P < 0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.
