Access Type

Open Access Dissertation

Date of Award

January 2018

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Molecular Biology and Genetics

First Advisor

Michael A. Tainsky

Abstract

While 25% of ovarian cancer (OVCA) cases are due to inherited factors, most of the genetic risk remains unexplained. This study addressed this gap by identifying previously undescribed OVCA risk loci through the whole exome sequencing (WES) of 48 BRCA1/BRCA2 wild type women diagnosed with OVCA, selected for high risk of genetic inheritance. Five clearly pathogenic variants were identified in this sample, four of which are in two genes featured on current multi-gene panels; (RAD51D, ATM). In addition, a high impact variant in FANCM (R1931*) was identified. FANCM has been recently implicated in familial breast cancer risk but is not yet featured on testing panels. Numerous rare and predicted to be damaging variants of unknown significance were detected in genes on current commercial testing panels. Also, the BRCA2 variant p.K3326*, considered benign but resulting in a 93 amino acid truncation, was overrepresented in our sample (OR= 4.95, p=0.01) and coexisted in the germline of these women with other deleterious variants, suggesting a possible role as a modifier of genetic penetrance.

A candidate gene analysis detected loss of function (LOF) variants in genes involved in OVCA relevant pathways; DNA repair and cell cycle control, including FANCM, CHK1, TP53I3, REC8, HMMR, RAD1, and MCM4. Wet lab functional assessment implicated FANCM, CHK1, RAD1 and TP53I3 as having the BRCA-like phenotype typically observed in tumor suppressor genes commonly mutated the germline of women with inherited risk of breast and/or ovarian cancer. Importantly, plotting various panel genes based on cell viability and sensitivity to DNA damage after siRNA knock down correctly differentiated between moderate and high penetrant genes. This technique identified candidate genes CHK1 and RAD1 as high and TP53I3 as moderate in penetrance.

The results of this project indicate that WES on study samples filtered for family history and negative for known causal variants is the most appropriate study design for identifying rare and novel high-risk variants. This study implicates novel risk loci as well as highlights the necessity of wet lab functional assessment. Importantly, this study also suggests that wet lab assays may be employed to differentiate moderate from high risk genetic loci.

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