Burcu F Darst

Burcu Darst
Assistant Professor. Public Health Sciences Division

Fred Hutchinson Cancer Center

Dr. Burcu Darst’s research is focused on identifying and understanding genetic and multi-omic risk factors of prostate cancer in diverse populations. She has extensive expertise in genetic epidemiology as well as genetic association and metabolomic investigations. Her research focuses on understanding genetic risk of prostate cancer in multi-ancestry populations, particularly using rare variants captured with whole exome sequencing, genome-wide association studies, polygenic risk scores and metabolomics to distinguish aggressive from non-aggressive disease and to understand the stark health disparities that contribute to prostate cancer risk. Currently, she is leading efforts to identify genomic and metabolic mechanisms contributing to prostate cancer risk in men from diverse populations as well as improving the utility of polygenic risk scores and rare genetic variants for the prediction of prostate cancer across patient populations.

Hutch faculty page

Assistant Professor. Public Health Sciences Division

Fred Hutchinson Cancer Center

Dr. Burcu Darst’s research is focused on identifying and understanding genetic and multi-omic risk factors of prostate cancer in diverse populations. She has extensive expertise in genetic epidemiology as well as genetic association and metabolomic investigations. Her research focuses on understanding genetic risk of prostate cancer in multi-ancestry populations, particularly using rare variants captured with whole exome sequencing, genome-wide association studies, polygenic risk scores and metabolomics to distinguish aggressive from non-aggressive disease and to understand the stark health disparities that contribute to prostate cancer risk. Currently, she is leading efforts to identify genomic and metabolic mechanisms contributing to prostate cancer risk in men from diverse populations as well as improving the utility of polygenic risk scores and rare genetic variants for the prediction of prostate cancer across patient populations.

Hutch faculty page