Our group is interested in understanding how inherited genetic variation influences predisposition to cancer. A variety of epidemiological and family-based studies have demonstrated that cancer predisposition is a hereditary trait. Despite this knowledge, the nature of the genetic variation that leads to increased cancer risk among some individuals largely remains a mystery. We are attacking this problem using an integrated combination of experimental and statistical/computational approaches, including state-of-the art genomics technologies. Our hypothesis is that by identifying and understanding the functional consequences of the genetic variants that influence cancer risk, we will gain insight into the underlying biology of cancer. This could lead to the identification of potential new targets for therapeutic intervention. Furthermore, identification of such variants could allow clinicians to predict who is at risk for cancer enabling better-tailored individual screening regimens and early detection. By focusing on inherited genetic variation, we are able perform unbiased, genome-wide screens for novel cancer susceptibility genes.
We approach this problem first by performing forward genetic studies (“genome-wide association studies”) in which we screen population and patient samples for genetic variants that are significantly correlated with cancer incidence. We do theoretical, computer-based work on how to improve the power of these studies, and use these improvements to analyze our data. Once associated loci are identified, understanding how they increase cancer risk requires both identifying the actual functional mutation at the locus and understanding the biology of the gene or genes the mutation influences. We use a combination of bioinformatics and high-throughput genomics data to generate hypotheses about mechanisms of disease susceptibility that can then be tested experimentally.
Current projects in the lab are primarily focused on prostate and pancreatic cancers. We are following up on previously reported genetic associations with prostate cancer to understand the mechanism of cancer predisposition at these loci. We are also developing improved statistical methods for analyzing genome-wide association data, and will be applying this to publically available prostate cancer association data. For pancreatic cancer, we are conducting our own genome-wide association study to identify alleles that increase ones risk of developing this virtually incurable malignancy. We are also involved in numerous collaborations with other investigators at Memorial Sloan-Kettering Cancer Center on diverse cancer types such as breast cancer, gastric cancer, endometrial cancer, and myeloproliferative neoplasms.