Literature DB >> 23292081

No association between ovarian cancer susceptibility variants and breast cancer risk among Chinese women.

Xiangyu Ma1, Qiuyin Cai, Ryan J Delahanty, Xiao-Ou Shu, Ben Zhang, Wei Lu, Yu-Tang Gao, Wei Zheng, Jirong Long, Alicia Beeghly-Fadiel.   

Abstract

BACKGROUND: As breast and ovarian cancers may have similar etiologies, this study aimed to evaluate the hypothesis that breast cancer shares common genetic susceptibility variants with ovarian cancer.
METHODS: Ten genetic variants in nine loci were previously identified to be associated with ovarian cancer risk among Caucasian women; an additional 353 variants in high-linkage disequilibrium (r(2) ≥ 0.6) among Han Chinese were identified. Data were available from the Affymetrix Genome-Wide Array (6.0) or MACH imputation for 25 and 78 common genetic variants [minor allele frequency (MAF) ≥0.05], respectively. Associations with breast cancer risk were evaluated by additive logistic regression models among 2,918 breast cancer cases and 2,324 controls.
RESULTS: No associations with breast cancer risk were evident for 103 ovarian cancer susceptibility variants in five loci. Four loci were not evaluated, as they included only rare variants (MAF < 0.05).
CONCLUSIONS: Ovarian cancer susceptibility variants identified in Caucasian women were not associated with breast cancer risk among 5,242 Chinese women. IMPACT: These findings suggest that breast and ovarian cancer may not share common susceptibility variants among Chinese women.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23292081      PMCID: PMC3596432          DOI: 10.1158/1055-9965.EPI-12-1365

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  7 in total

1.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits.

Authors:  Lucia A Hindorff; Praveen Sethupathy; Heather A Junkins; Erin M Ramos; Jayashri P Mehta; Francis S Collins; Teri A Manolio
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-27       Impact factor: 11.205

2.  SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap.

Authors:  Andrew D Johnson; Robert E Handsaker; Sara L Pulit; Marcia M Nizzari; Christopher J O'Donnell; Paul I W de Bakker
Journal:  Bioinformatics       Date:  2008-10-30       Impact factor: 6.937

Review 3.  Hereditary breast and ovarian cancer: review and future perspectives.

Authors:  Michael P Lux; Peter A Fasching; Matthias W Beckmann
Journal:  J Mol Med (Berl)       Date:  2005-11-11       Impact factor: 4.599

4.  Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1.

Authors:  Wei Zheng; Jirong Long; Yu-Tang Gao; Chun Li; Ying Zheng; Yong-Bin Xiang; Wanqing Wen; Shawn Levy; Sandra L Deming; Jonathan L Haines; Kai Gu; Alecia Malin Fair; Qiuyin Cai; Wei Lu; Xiao-Ou Shu
Journal:  Nat Genet       Date:  2009-02-15       Impact factor: 38.330

5.  Identification of new genetic risk variants for type 2 diabetes.

Authors:  Xiao Ou Shu; Jirong Long; Qiuyin Cai; Lu Qi; Yong-Bing Xiang; Yoon Shin Cho; E Shyong Tai; Xiangyang Li; Xu Lin; Wong-Ho Chow; Min Jin Go; Mark Seielstad; Wei Bao; Huaixing Li; Marilyn C Cornelis; Kai Yu; Wanqing Wen; Jiajun Shi; Bok-Ghee Han; Xue Ling Sim; Liegang Liu; Qibin Qi; Hyung-Lae Kim; Daniel P K Ng; Jong-Young Lee; Young Jin Kim; Chun Li; Yu-Tang Gao; Wei Zheng; Frank B Hu
Journal:  PLoS Genet       Date:  2010-09-16       Impact factor: 5.917

6.  Breast cancer susceptibility alleles and ovarian cancer risk in 2 study populations.

Authors:  Margaret A Gates; Shelley S Tworoger; Kathryn L Terry; Immaculata De Vivo; David J Hunter; Susan E Hankinson; Daniel W Cramer
Journal:  Int J Cancer       Date:  2009-02-01       Impact factor: 7.396

7.  Association between invasive ovarian cancer susceptibility and 11 best candidate SNPs from breast cancer genome-wide association study.

Authors:  Honglin Song; Susan J Ramus; Susanne Krüger Kjaer; Richard A DiCioccio; Georgia Chenevix-Trench; Celeste Leigh Pearce; Estrid Hogdall; Alice S Whittemore; Valerie McGuire; Claus Hogdall; Jan Blaakaer; Anna H Wu; David J Van Den Berg; Daniel O Stram; Usha Menon; Aleksandra Gentry-Maharaj; Ian J Jacobs; Penny M Webb; Jonathan Beesley; Xiaoqing Chen; Mary Anne Rossing; Jennifer A Doherty; Jenny Chang-Claude; Shan Wang-Gohrke; Marc T Goodman; Galina Lurie; Pamela J Thompson; Michael E Carney; Roberta B Ness; Kirsten Moysich; Ellen L Goode; Robert A Vierkant; Julie M Cunningham; Stephanie Anderson; Joellen M Schildkraut; Andrew Berchuck; Edwin S Iversen; Patricia G Moorman; Montserrat Garcia-Closas; Stephen Chanock; Jolanta Lissowska; Louise Brinton; Hoda Anton-Culver; Argyrios Ziogas; Wendy R Brewster; Bruce A J Ponder; Douglas F Easton; Simon A Gayther; Paul D P Pharoah
Journal:  Hum Mol Genet       Date:  2009-03-20       Impact factor: 6.150

  7 in total
  1 in total

1.  Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice.

Authors:  Kenji Yano; Eiji Yamamoto; Koichiro Aya; Hideyuki Takeuchi; Pei-Ching Lo; Li Hu; Masanori Yamasaki; Shinya Yoshida; Hidemi Kitano; Ko Hirano; Makoto Matsuoka
Journal:  Nat Genet       Date:  2016-06-20       Impact factor: 38.330

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.