Evaluation of microRNA expression profiles and their associations with risk alleles in lymphoblastoid cell lines of familial ovarian cancer

• Published in: Carcinogenesis (New York) 2012-03, Vol.33 (3), p.604-612
• Main Authors: JIE SHEN, DAN WANG, HUA ZHAO, GREGORY, Steven R, MEDICO, Leonard, QIANG HU, LI YAN, ODUNSI, Kunle, LELE, Shashikant B, AMBROSONE, Christine B, SONG LIU
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Cancer Biomarkers and Molecular Epidemiology; Carcinogenesis; Carcinogenesis, carcinogens and anticarcinogens; Cell Line, Tumor; Female; Female genital diseases; Gene Expression Profiling; Genetic Predisposition to Disease; Genetic Variation; Genome-Wide Association Study; Gynecology. Andrology. Obstetrics; Humans; Medical sciences; MicroRNAs - biosynthesis; MicroRNAs - genetics; Oligonucleotide Array Sequence Analysis; Ovarian Neoplasms - genetics; Ovarian Neoplasms - metabolism; Phenotype; Polymorphism, Single Nucleotide; Risk Factors; Tumors
• ISSN: 0143-3334; 1460-2180
• DOI: 10.1093/carcin/bgs008

Interindividual variations of microRNA expression are likely to influence the expression of microRNA target genes and, therefore, contribute to phenotypic differences in humans, including cancer susceptibility. Whether microRNA expression variation has any role in ovarian cancer development is still unknown. Here, we evaluated microRNA expression profiles in lymphoblastoid cell lines from 74 women with familial ovarian cancer and 47 unrelated controls matched on gender and race. We found that the cases and unrelated controls can be clustered using 95 differentially expressed microRNAs with 91% accuracy. To assess the potential implications of microRNAs in ovarian cancer, we investigated the associations between microRNA expression and seven ovarian cancer risk variants discovered from genome-wide association studies (GWAS), namely, rs3814113 on 9p22.2, rs2072590 on 2q31, rs2665390 on 3q25, rs10088218, rs1516982, rs10098821 on 8q24.21 and rs2363956 on 19p13. We observed 130 significant associations at a permutation level of 0.01. Compared with other risk variants, rs3814113 and rs2072590 had the greatest number of significant associations (68 and 37, respectively). Interestingly, 14 microRNAs that were associated with ovarian cancer risk alleles belong to five microRNA clusters. The most notable cluster is the tumorigenic miR-17-92 cluster with five microRNAs, all of which are significantly associated with rs3814113. Using pathway analysis, several key biological pathways were significantly overrepresented, such as cellular response to stress (P = 2.87 × 10(-06)), etc. Further characterization of significant associations between microRNAs and risk alleles could facilitate the understanding of the functions of these GWAS discovered risk alleles in the genetic etiology of ovarian cancer.