Ovarian cancer is the most deadly gynecologic cancer. We are challenged on almost every front by this complex malignancy: few modifiable risk factor have been identified for primary prevention, current screening is neither sensitive nor specific enough to use at the population level, and current cytotoxic therapy regimens (single or combined) extend survival but ultimately are ineffective as most ovarian cancer patients still die of chemo- resistant recurrent disease. A new understanding of key factors that contribute to cancer development and chemo-resistance is needed to inform the biological basis for novel interventions and therapies. An intriguing possibility is that mitochondria and mitochondrial DNA (mtDNA) play a role, as yet undefined, in ovarian cancer development and progression. Our overall goal is to understand how mtDNA can be used to predict women at elevated risk for ovarian cancer who may benefit from more intensive medical workups resulting in earlier diagnosis and to predict women who are most likely to benefit from specific therapies. Our working hypothesis is that women with ovarian cancer will have different polymorphic variants of mtDNA and/or a different distribution of mtDNA copy number in blood and cancerous tissue than similar women without ovarian cancer. We also hypothesize that one or more of these mtDNA features will be predictive of risk and survival. In testing our hypotheses, we will use extensive resources of the Ovarian Cancer in Alberta and British Columbia (OVAL-BC) Study, a population-based case-control study with ~1235 cases and 2070 controls recruited from 2002-2011. Existing data/specimens include extensive interview information and DNA from blood/buccal samples. We will augment this resource with detailed information on treatment and tumor histology as well as cancerous tissue samples. We have access to a leading next-generation sequencing platform for systematic and detailed characterization of mtDNA variation using index tags that act as molecular barcodes for simultaneous sequencing of up to 96 samples at a time, allowing us to completely sequence mtDNA from blood or saliva in very case and control and mtDNA from cancerous tissue in the cases. Our exceptional OVAL-BC Study resource, access to medical records and tissue, expert pathology review, and technological strength makes us uniquely poised to assess the effect of mitochondrial genetic variation on ovarian cancer risk and survival. Thus, by characterizing mtDNA and risk/survival in an existing and well- characterized population, we may, in the short-term, identify new biomarkers that could be further assessed in efforts to prevent death from ovarian cancer. Ultimately, such knowledge can be used to elicit more effective ovarian cancer prevention and treatment.
Ovarian cancer is the most deadly gynecologic cancer. Our goal is to understand how mtDNA can be used to predict: 1) women who are at elevated risk for ovarian cancer who may benefit from more intensive medical workups resulting in earlier diagnosis;and, 2) women who are most likely to benefit from specific therapies. By characterizing mtDNA and risk and survival in an existing and well-characterized population, we may, in the short-term, identify new biomarkers that could be immediately relevant in efforts to prevent death from ovarian cancer. Ultimately, such knowledge can be used to elicit more effective ovarian cancer prevention and treatment.
|Reid, Brett M; Permuth, Jennifer B; Chen, Y Ann et al. (2017) Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci. Cancer Epidemiol Biomarkers Prev 26:116-125|
|Permuth, Jennifer B; Reid, Brett; Earp, Madalene et al. (2016) Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility: results from a large-scale collaboration. Oncotarget 7:72381-72394|
|Mackenzie, Robertson; Talhouk, Aline; Eshragh, Sima et al. (2015) Morphologic and Molecular Characteristics of Mixed Epithelial Ovarian Cancers. Am J Surg Pathol 39:1548-57|