Grant Details
Grant Number: |
1R01CA188943-01A1 Interpret this number |
Primary Investigator: |
Hildebrandt, Michelle |
Organization: |
University Of Tx Md Anderson Can Ctr |
Project Title: |
Discovery of Novel Rare Variants as Ovarian Cancer Susceptibility Factors |
Fiscal Year: |
2015 |
Abstract
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DESCRIPTION (provided by applicant): Ovarian cancer is a rare cancer, with less than 25,000 new cases diagnosed each year in the United States. It is also among the most lethal cancers owing to the lack of effective screening measures and the "symptom- less" nature of the disease, resulting in frequent diagnoses of high-grade, invasive disease. To have a meaningful impact in survival for this disease, in parallel with advances in treatment options, improvements in risk assessment also need to be made that can assist in prevention and screening. Towards this, there have been significant efforts in identifying common, germline genetic variants as susceptibility loci. This includes genome-wide association studies that have now identified 11 loci associated with ovarian cancer risk, with six additional loci to be published in the coming months. However, these variants combined only explain less than 5% of the heritable risk of ovarian cancer. Even when with the contribution of BRCA1 and BRCA2 mutations to ovarian cancer risk, there is still ~60% of heritable risk that remains unaccounted for. We hypothesize that rare variants in multiple genes individually confer an intermediate risk of ovarian cancer and
that these variants can be highly informative in accurately predict ovarian cancer risk, while providing clues about the etiology of the disease. To test this hypothesis, we are proposing to perform whole exome sequencing followed by targeted sequencing in a total of 8,000 ovarian cancer cases and 8,000 matched controls of European descent to identify the spectrum of rare genetic variation that contributes to ovarian cancer susceptibility. With the known differences in prognosis for European American (EA) and African American (AA) women diagnosed with ovarian cancer, we will also sequence the top candidate genes identified in the EA population in the largest, ongoing study of AA women with ovarian cancer. A better understanding of the similarities and differences in the genetic architecture of ovarian cancer between EA and AA women will be a step forward in understanding this health disparity. Finally, sequencing of ovarian tumors from individuals with rare germline susceptibility variants will provide the opportunity to link somatic and germline variation in mediating ovarian cancer risk. Together, these analyses have the potential to enhance ovarian cancer risk assessment that can identify those at highest risk who would be candidates for refinement of existing or the development of new screening modalities and prevention measures.
Publications
Molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms.
Authors: Davidson N.R.
, Barnard M.E.
, Hippen A.A.
, Campbell A.
, Johnson C.E.
, Way G.P.
, Dalley B.K.
, Berchuck A.
, Salas L.A.
, Peres L.C.
, et al.
.
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2024-05-23 00:00:00.0; , .
EPub date: 2024-05-23 00:00:00.0.
PMID: 38780898
Related Citations
A whole-exome case-control association study to characterize the contribution of rare coding variation to pancreatic cancer risk.
Authors: Yu Y.
, Chang K.
, Chen J.S.
, Bohlender R.J.
, Fowler J.
, Zhang D.
, Huang M.
, Chang P.
, Li Y.
, Wong J.
, et al.
.
Source: Hgg Advances, 2022-01-13 00:00:00.0; 3(1), p. 100078.
EPub date: 2021-12-10 00:00:00.0.
PMID: 35047863
Related Citations
Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer.
Authors: Song H.
, Dicks E.M.
, Tyrer J.
, Intermaggio M.
, Chenevix-Trench G.
, Bowtell D.D.
, Traficante N.
, Group A.
, Brenton J.
, Goranova T.
, et al.
.
Source: Journal Of Medical Genetics, 2021 May; 58(5), p. 305-313.
EPub date: 2020-06-16 00:00:00.0.
PMID: 32546565
Related Citations
XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.
Authors: Yu Y.
, Hu H.
, Bohlender R.J.
, Hu F.
, Chen J.S.
, Holt C.
, Fowler J.
, Guthery S.L.
, Scheet P.
, Hildebrandt M.A.T.
, et al.
.
Source: Nucleic Acids Research, 2018-04-06 00:00:00.0; 46(6), p. e32.
PMID: 29294048
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