A fundamental goal of human genetics is to decipher the relationship between genotype and phenotype. Cancer is defined as a disease comprising a heritable genetic component that confers cancer predisposition and an acquired (somatic) component where disease is driven by an accumulation of genetic mutations leading to ever increasing deregulation of normal cellular functions. Population based genome wide association studies (GWAS) and whole genome sequencing (WGS) analyses have identified thousands of germline risk variants for ovarian cancer and somatic non-coding mutations involved in ovarian cancer development. Identifying genomic regions where there are interactions between germline and somatic variants may enable us to identify the critical drivers of disease. We have established an end-to-end pipeline that can efficiently evaluate the functional significance of thousands of genetic variants in disease at once. We have also established ex-vivo models of fallopian tube secretary epithelial cells (precursors of ovarian cancer) and in vitro 3D models of chemoresistant ovarian cancer. In this proposal, we plan to address provocative question #3 ?Do genetic interactions between germline variations and somatic mutations contribute to differences in tumor evolution or response to therapy?? with the following specific aims: (1) Use computational approaches, to identify genomic regions where germline and somatic genetic variants converge to indicate shared target genes and regulatory networks driving ovarian cancer development; (2) Use chromosome conformation capture assays to validate interactions between regulatory targets and their target genes; (3) Use CRISPR/Cas9 screens to establish the functional significance of germline-somatic interacting regions in ovarian cancer development.

Public Health Relevance

FOR LAY AUDIENCE Ovarian cancer is responsible for more than 150,000 deaths per year and so it remains a high priority to develop effective prevention approaches and to identify new disease specific therapies to reduce disease mortality. The research we propose here has two components: (1) To characterize the component of genetic and epigenomic interactions in ovarian cancer development; (2) to establish the functional relevance of genetic findings for clinical translation. This is a highly integrated multi-disciplinary research program ? but these approaches to novel discovery and functional understanding are desperately needed to advance our basic knowledge of this disease to develop clinical interventions that save lives.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA244569-01A1
Application #
10052250
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Nelson, Stefanie A
Project Start
2020-06-01
Project End
2025-05-31
Budget Start
2020-06-01
Budget End
2021-05-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Cedars-Sinai Medical Center
Department
Type
DUNS #
075307785
City
Los Angeles
State
CA
Country
United States
Zip Code
90048