Simon A Gayther

PIBBS MENTOR

Professor

Preventive Medicine

Research Topics

  • Cancer Susceptibility Genetics
  • Cell biology modeling of cancer
  • Ovarian Cancer
  • Gynecological Disease

Research Overview

Summary: This is a well established research program, which was built-up at UCL, London UK, in 2004 and moved to USC in September 2010The aim of my research laboratory is to combine susceptibility genetics in ovarian cancer, with molecular profiling studies in ovarian tumor tissue banks and functional modeling of ovarian cancers and normal ovarian tissues to identify clinically relevant markers of the disease. The main research aims of this program are:

* To characterize the underlying genetic basis of susceptibility to epithelial ovarian cancer, both in multi-case families and in population based series of ovarian cancer cases unselected for family history.
* To establish the underlying basis of germline genetic susceptibility to clinical characteristics of ovarian cancer, including disease heterogeneity and outcome (patient survival).
* To establish the molecular genetic phenotypes of ovarian tumors that can be used to stratify cancers into clinical phenotypes for improved patient management and treatment.
* To establish a functional rational for rare and common genetic variants and associated genes that predispose individuals to developing ovarian cancer, using cell biology models of disease.
* To identify molecular components of ovarian cancer development that represent small-molecule targets for the treatment of chemo-resistant ovarian cancer.

The specific aims and objectives are:

Genetic Susceptibility

* Identifying common low penetrance susceptibility allele for ovarian cancer
* Fine mapping common low penetrance susceptibility alleles to identify causal alleles
* Establishing a genetic basis for disease heterogeneity
* Identifying rare variant susceptibility alleles for ovarian cancer

Cell Biology modeling

* Functional in vitro/in vivo modeling of ovarian cancer and initiation
* Functional in vitro/in vivo modeling of ovarian cancer micro-environment
* Functional evaluation of common and rare variant susceptibility alleles

Molecular Tumor Profiling

* Identifying molecular profiles of ovarian tumor associated with clinical outcome
* Determining the molecular basis of tumor heterogeneity in population based series of ovarian cancer