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Grant Details

Grant Number: 1R01CA160669-01A1 Interpret this number
Primary Investigator: Cook, Linda
Organization: University Of New Mexico Health Scis Ctr
Project Title: Mitochondrial DNA and Ovarian Cancer Risk and Survival
Fiscal Year: 2012


Abstract

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: 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.



Publications

p53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study.
Authors: Köbel M. , Kang E.Y. , Weir A. , Rambau P.F. , Lee C.H. , Nelson G.S. , Ghatage P. , Meagher N.S. , Riggan M.J. , Alsop J. , et al. .
Source: The journal of pathology. Clinical research, 2023-03-22; , .
EPub date: 2023-03-22.
PMID: 36948887
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Profiling the immune landscape in mucinous ovarian carcinoma.
Authors: Meagher N.S. , Hamilton P. , Milne K. , Thornton S. , Harris B. , Weir A. , Alsop J. , Bisinoto C. , Brenton J.D. , Brooks-Wilson A. , et al. .
Source: Gynecologic oncology, 2023 Jan; 168, p. 23-31.
EPub date: 2022-11-08.
PMID: 36368129
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Increased FOXJ1 protein expression is associated with improved overall survival in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis Consortium Study.
Authors: Weir A. , Kang E.Y. , Meagher N.S. , Nelson G.S. , Ghatage P. , Lee C.H. , Riggan M.J. , Gentry-Maharaj A. , Ryan A. , Singh N. , et al. .
Source: British journal of cancer, 2023 Jan; 128(1), p. 137-147.
EPub date: 2022-11-02.
PMID: 36323878
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Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci.
Authors: DeVries A.A. , Dennis J. , Tyrer J.P. , Peng P.C. , Coetzee S.G. , Reyes A.L. , Plummer J.T. , Davis B.D. , Chen S.S. , Dezem F.S. , et al. .
Source: Journal of the National Cancer Institute, 2022-11-14; 114(11), p. 1533-1544.
PMID: 36210504
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Refined cut-off for TP53 immunohistochemistry improves prediction of TP53 mutation status in ovarian mucinous tumors: implications for outcome analyses.
Authors: Kang E.Y. , Cheasley D. , LePage C. , Wakefield M.J. , da Cunha Torres M. , Rowley S. , Salazar C. , Xing Z. , Allan P. , Bowtell D.D.L. , et al. .
Source: Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2021 Jan; 34(1), p. 194-206.
EPub date: 2020-07-28.
PMID: 32724153
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Identification of novel epithelial ovarian cancer loci in women of African ancestry.
Authors: Manichaikul A. , Peres L.C. , Wang X.Q. , Barnard M.E. , Chyn D. , Sheng X. , Du Z. , Tyrer J. , Dennis J. , Schwartz A.G. , et al. .
Source: International journal of cancer, 2020-06-01; 146(11), p. 2987-2998.
EPub date: 2019-10-08.
PMID: 31469419
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Ovarian Carcinoma Histotype: Strengths and Limitations of Integrating Morphology With Immunohistochemical Predictions.
Authors: Köbel M. , Luo L. , Grevers X. , Lee S. , Brooks-Wilson A. , Gilks C.B. , Le N.D. , Cook L.S. .
Source: International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists, 2019 Jul; 38(4), p. 353-362.
PMID: 29901523
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Evaluation of vitamin D biosynthesis and pathway target genes reveals UGT2A1/2 and EGFR polymorphisms associated with epithelial ovarian cancer in African American Women.
Authors: Grant D.J. , Manichaikul A. , Alberg A.J. , Bandera E.V. , Barnholtz-Sloan J. , Bondy M. , Cote M.L. , Funkhouser E. , Moorman P.G. , Peres L.C. , et al. .
Source: Cancer medicine, 2019 May; 8(5), p. 2503-2513.
EPub date: 2019-04-18.
PMID: 31001917
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Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women.
Authors: Lawrenson K. , Song F. , Hazelett D.J. , Kar S.P. , Tyrer J. , Phelan C.M. , Corona R.I. , Rodríguez-Malavé N.I. , Seo J.H. , Adler E. , et al. .
Source: Gynecologic oncology, 2019 May; 153(2), p. 343-355.
EPub date: 2019-03-19.
PMID: 30898391
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A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.
Authors: Kim S. , Wang M. , Tyrer J.P. , Jensen A. , Wiensch A. , Liu G. , Lee A.W. , Ness R.B. , Salvatore M. , Tworoger S.S. , et al. .
Source: International journal of cancer, 2019-05-01; 144(9), p. 2192-2205.
EPub date: 2019-01-20.
PMID: 30499236
Related Citations

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk.
Authors: Yang Y. , Wu L. , Shu X. , Lu Y. , Shu X.O. , Cai Q. , Beeghly-Fadiel A. , Li B. , Ye F. , Berchuck A. , et al. .
Source: Cancer research, 2019-02-01; 79(3), p. 505-517.
EPub date: 2018-12-17.
PMID: 30559148
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Shared heritability and functional enrichment across six solid cancers.
Authors: Jiang X. , Finucane H.K. , Schumacher F.R. , Schmit S.L. , Tyrer J.P. , Han Y. , Michailidou K. , Lesseur C. , Kuchenbaecker K.B. , Dennis J. , et al. .
Source: Nature communications, 2019-01-25; 10(1), p. 431.
EPub date: 2019-01-25.
PMID: 30683880
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Association of p16 expression with prognosis varies across ovarian carcinoma histotypes: an Ovarian Tumor Tissue Analysis consortium study.
Authors: Rambau P.F. , Vierkant R.A. , Intermaggio M.P. , Kelemen L.E. , Goodman M.T. , Herpel E. , Pharoah P.D. , Kommoss S. , Jimenez-Linan M. , Karlan B.Y. , et al. .
Source: The journal of pathology. Clinical research, 2018 Oct; 4(4), p. 250-261.
EPub date: 2018-09-21.
PMID: 30062862
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A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
Authors: Lu Y. , Beeghly-Fadiel A. , Wu L. , Guo X. , Li B. , Schildkraut J.M. , Im H.K. , Chen Y.A. , Permuth J.B. , Reid B.M. , et al. .
Source: Cancer research, 2018-09-15; 78(18), p. 5419-5430.
EPub date: 2018-07-27.
PMID: 30054336
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Racial/ethnic differences in the epidemiology of ovarian cancer: a pooled analysis of 12 case-control studies.
Authors: Peres L.C. , Risch H. , Terry K.L. , Webb P.M. , Goodman M.T. , Wu A.H. , Alberg A.J. , Bandera E.V. , Barnholtz-Sloan J. , Bondy M.L. , et al. .
Source: International journal of epidemiology, 2018-04-01; 47(2), p. 460-472.
PMID: 29211900
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Dose-Response Association of CD8+ Tumor-Infiltrating Lymphocytes and Survival Time in High-Grade Serous Ovarian Cancer.
Authors: Ovarian Tumor Tissue Analysis (OTTA) Consortium , Goode E.L. , Block M.S. , Kalli K.R. , Vierkant R.A. , Chen W. , Fogarty Z.C. , Gentry-Maharaj A. , Tołoczko A. , Hein A. , et al. .
Source: JAMA oncology, 2017-12-01; 3(12), p. e173290.
PMID: 29049607
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Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci.
Authors: Reid B.M. , Permuth J.B. , Chen Y.A. , Teer J.K. , Monteiro A.N. , Chen Z. , Tyrer J. , Berchuck A. , Chenevix-Trench G. , Doherty J.A. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2017 Jan; 26(1), p. 116-125.
EPub date: 2016-12-29.
PMID: 28035019
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Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility: results from a large-scale collaboration.
Authors: Permuth J.B. , Reid B. , Earp M. , Chen Y.A. , Monteiro A.N. , Chen Z. , AOCS Study Group , Chenevix-Trench G. , Fasching P.A. , Beckmann M.W. , et al. .
Source: Oncotarget, 2016-11-08; 7(45), p. 72381-72394.
PMID: 27911851
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Morphologic and Molecular Characteristics of Mixed Epithelial Ovarian Cancers.
Authors: Mackenzie R. , Talhouk A. , Eshragh S. , Lau S. , Cheung D. , Chow C. , Le N. , Cook L.S. , Wilkinson N. , McDermott J. , et al. .
Source: The American journal of surgical pathology, 2015 Nov; 39(11), p. 1548-57.
PMID: 26099008
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