N.2: Project 2 Ovarian cancer is a lethal gynecologic malignancy and its development is poorly understood. We have performed four independent genome wide association studies (GWAS) in ovarian cancer and have identified highly significant, replicated single nucleotide polymorphisms (SNPs) associated with ovarian cancer risk. In Project 1, these GWAS will be combined to identify additional susceptibility loci and genetic variants associated with risk. Here we will evaluate the functional significance of candidate genes and SNPs at these loci.
The specific aims are as follows: 1. To evaluate the role of candidate genes at susceptibility loci in ovarian cancer. We will use bioinformatics tools to extract publicly available data describing a role for candidate genes in cancer. Next, we will assess differences in transcript/protein expression between ovarian cancer cell lines and primary tumours, and normal ovarian epithelia. Then we will determine whether candidate genes have acquired somatic genetic changes in primary ovarian cancers. 2. To determine the functional significance of candidate SNPs in the susceptibility regions. Bioinformatics tools will be employed to determine whether a SNP's DNA location can predict functional impact. We will also correlate SNP genotype and copy number variants (CNVs) with differential germline expression and methylation status. 3. To evaluate the role of candidate SNPs located distant from known Open Reading Frames. We expect several SNP associations to fall in """"""""gene deserts"""""""". Bioinformatics tools will be used to predict microRNAs or distant regulatory regions, and to identify conserved elements. We will look for functional evidence of regulatory elements correlated with SNP location using chromatin immunoprecipitation and sequencing analysis (ChlP-Seq). 4. To perform detailed functional characterization of candidate genes and SNPs. We will evaluate the biological significance of candidate genes using three-dimensional culture models of ovarian cancers and normal ovaries. We will modulate their expression using cDNA or shRNA expression mediated by lentlviral transduction. Bioinformatics predictions of SNP function will be tested using specific functional assays that will depend on the nature of the candidate gene and SNP. This will include mobility shift DNA binding, reporter and DNAse I hypersensitivity assays. The knowledge gained from this large collaborative study will significantly contribute to our understanding of the functional rationale underlying genetic susceptibility and survival in women diagnosed with ovarian cancer.
Determining the functional mechanism for genetic variants that cause ovarian cancer will improve our understanding of the underlying biology of the disease. This will also enhance the ability to identify women at greatest risk, and potentially lead to the development of more effective, individualized therapies. The studies may also inform the research community about the cellular origins of epithelial ovarian cancers, which remains an unresolved clinical and research question.
|(2016) Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer. Nat Commun 7:11375|
|Zhao, Zhiguo; Wen, Wanqing; Michailidou, Kyriaki et al. (2016) Association of genetic susceptibility variants for type 2 diabetes with breast cancer risk in women of European ancestry. Cancer Causes Control 27:679-93|
|Cheng, Timothy H T; Thompson, Deborah J; O'Mara, Tracy A et al. (2016) Five endometrial cancer risk loci identified through genome-wide association analysis. Nat Genet 48:667-74|
|(2016) Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types. Cancer Discov 6:1052-67|
|Saunders, Edward J; Dadaev, Tokhir; Leongamornlert, Daniel A et al. (2016) Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array. Br J Cancer 114:945-52|
|Shi, Jiajun; Zhang, Yanfeng; Zheng, Wei et al. (2016) Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer. Int J Cancer 139:1303-17|
|Lei, Jieping; Rudolph, Anja; Moysich, Kirsten B et al. (2016) Genetic variation in the immunosuppression pathway genes and breast cancer susceptibility: a pooled analysis of 42,510 cases and 40,577 controls from the Breast Cancer Association Consortium. Hum Genet 135:137-54|
|Gusev, Alexander; Shi, Huwenbo; Kichaev, Gleb et al. (2016) Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation. Nat Commun 7:10979|
|Winham, Stacey J; Pirie, Ailith; Chen, Yian Ann et al. (2016) Investigation of Exomic Variants Associated with Overall Survival in Ovarian Cancer. Cancer Epidemiol Biomarkers Prev 25:446-54|
|Muranen, Taru A; Greco, Dario; Blomqvist, Carl et al. (2016) Genetic modifiers of CHEK2*1100delC-associated breast cancer risk. Genet Med :|
Showing the most recent 10 out of 114 publications