Evaluation of Common Inherited Variants in Mitochondrial-Related and MicroRNA-Related Genes as Novel Risk Factors for Ovarian Cancer
Epithelial ovarian cancer (EOC) is a leading cause of morbidity and mortality among women in the United States, and the etiology is incompletely understood. Common, low penetrant genetic variants such as single nucleotide polymorphisms (SNPs) likely contribute to a significant proportion of EOC. We...
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Format: | Others |
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Scholar Commons
2010
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Online Access: | http://scholarcommons.usf.edu/etd/3488 http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=4683&context=etd |
Summary: | Epithelial ovarian cancer (EOC) is a leading cause of morbidity and mortality among women in the United States, and the etiology is incompletely understood. Common, low penetrant genetic variants such as single nucleotide polymorphisms (SNPs) likely contribute to a significant proportion of EOC. We examined whether SNPs in two understudied yet biologically important types of genes, mitochondrial-related and miRNA-related genes, may contribute to EOC susceptibility using data from a large, homogeneous study population of 1,815 EOC cases and 1,900 controls (frequency-matched on age-group and race/ethnicity) genotyped through stage 1 of an ongoing genome-wide association study. Inter-individual variation in genes involved in mitochondrial biogenesis was strongly associated with EOC risk (empirical P=0.050), especially for genes NRF1, PPARGC1A, MTERF, ESRRA, and CAMK2D. SNPs in several genes involved in the biogenesis of miRNAs (LIN28, LIN28B, AGO2, DICER, and DROSHA) also demonstrated associations with EOC risk; a joint meta-analysis and in vitro investigations reinforced evidence for a protective role of LIN28B rs12194974 (combined OR= 0.90, 95% CI: 0.82-0.98), a G>A SNP predicted to reside in a transcription factor binding site in the highly conserved LIN28B promoter. Our findings provide valuable insight into the pathogenesis of EOC, and support the consideration of variants in these genes as candidates when building risk prediction models. Most importantly, this work has provided a strong foundation for further lines of research that may aid in reducing the burden of this disease. |
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