title: Associations between gene expression variations and ovarian cancer risk alleles identified from genome wide association studies.
abstract: 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.
authors.affiliation: Department of Cancer Prevention and Controls, Roswell Park Cancer Institute, Buffalo, New York, United States of America. hzhao2@mdanderson.org
authors.forename: Hua
authors.initials: H
authors.lastname: Zhao
authors.forename: Jie
authors.initials: J
authors.lastname: Shen
authors.forename: Dan
authors.initials: D
authors.lastname: Wang
authors.forename: Yuqing
authors.initials: Y
authors.lastname: Guo
authors.forename: Steven
authors.initials: S
authors.lastname: Gregory
authors.forename: Leonardo
authors.initials: L
authors.lastname: Medico
authors.forename: Qiang
authors.initials: Q
authors.lastname: Hu
authors.forename: Li
authors.initials: L
authors.lastname: Yan
authors.forename: Kunle
authors.initials: K
authors.lastname: Odunsi
authors.forename: Shashikant
authors.initials: S
authors.lastname: Lele
authors.forename: Song
authors.initials: S
authors.lastname: Liu
mesh_terms: D048868:Adaptor Proteins, Signal Transducing / Q000235:genetics; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000483:Alleles; D005260:Female; D005786:Gene Expression Regulation; D015972:Gene Expression Regulation, Neoplastic; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D055106:Genome-Wide Association Study; D006801:Humans; D008214:Lymphocytes / Q000166:cytology; D008875:Middle Aged; D000070957:MutL Protein Homolog 1; D009687:Nuclear Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000378:metabolism; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012333:RNA, Messenger / Q000378:metabolism; D012306:Risk
chemical_list: D048868:Adaptor Proteins, Signal Transducing; C501486:MLH1 protein, human; D009687:Nuclear Proteins; D012333:RNA, Messenger; D000070957:MutL Protein Homolog 1