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Associations between Gene Expression Variations and Ovarian Cancer Risk Alleles Identified from Genome Wide Association Studies
Author(s) -
Hua Zhao,
Jie Shen,
Dan Wang,
Steven R. Gregory,
Leonardo Medico,
Qiang Hu,
Li Yan,
Kunle Odunsi,
Shashikant Lele,
Song Liu
Publication year - 2012
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0047962
Subject(s) - genome wide association study , biology , genetics , genetic association , allele , ovarian cancer , gene , single nucleotide polymorphism , cancer , bioinformatics , genotype
Functional genetic variations play important roles in shaping phenotypic differences among individuals through affecting gene expression, and thus, very likely to influence disease susceptibility, such as cancer susceptibility. One critical question in this era of post-genome wide association studies (GWAS) is how to assess the functional significance of the genetic variations identified from GWAS. In the current study, with lymphoblastoid cell lines (LCLs) from 74 non-related women with familial ovarian cancer and 47 unrelated controls matched on gender and race, we explored the associations between seven ovarian cancer risk variants identified from GWAS ( rs3814113 on 9p22.2, rs2072590 on 2q31, rs2665390 on 3q25, rs10088218 , rs1516982 , rs10098821 on 8q24.21, and rs2363956 on 19p13) and whole genome mRNA expression profiles. We observed 95 significant trans-associations at a permutation level of 0.001. Compared to the other risk variants, rs10088218 , rs1516982 , and rs10098821 on 8q24.21 had the greatest number of significant associations (25, 16, and 38, respectively). Two possible cis-associations were observed between rs10098821 and c-Myc , and rs2072590 and HS.565379 (Permutated P = 0.0198 and 0.0399, respectively). Pathway enrichment analysis showed that several key biological pathways, such as cell cycle (P = 2.59×10 −06 ), etc, were significantly overrepresented. Further characterization of significant associations between mRNAs and risk alleles might facilitate understanding the functions of GWAS discovered risk alleles in the genetic etiology of ovarian cancer.

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