We use genetic, genomic, and proteomic data to understand and model the biology of cancer and to develop methods to effectively deploy therapeutic agents. See research interests
Our lab is interested in using genetic, genomic, and proteomic data to understand and model the biology of cancer and to develop methods to effectively deploy therapeutic agents in the age of molecularly guided medicine. Members of my lab use a combiation of conventional molecular biology, high throughput genomic and proteomic assays, and bioinformatics analysis in their work.
My group participates in numerous collaborations to understand the effects of genome aberrations in cancer. These efforts include development of new methodologies for identifying changes in the cancer genome, systematic integration of multiple genomic data types (copy number, expression, and mutation) to better understand the process by which cancer develops, and the application of cell line systems as models for the genetic heterogeneity within cancers. Two major thrusts are the systematic characterization of cancer genomes as part of The Genome Data Analysis Network and the development and application of methods to reconstruct tumor evolution (Durinck et al. Cancer Discover, 2011, Gerstung et al. 2018 BioRxiv <https://www.biorxiv.org/content/early/2018/09/12/161562>).
My lab also works within the Cancer Early Detection Advanced Research Center (CEDAR) to develop approaches to understand, detect, and treat early lethal cancers. In CEDAR I am one of the Co-Directors of the overall effort. Projects in CEDAR that I participate in include developing cohorts for early detection, identify populations at risk for developing cancer, and understanding the early biology of breast cancers.
Finally, my lab uses genomic technologies to monitor the return of cancer and its evolution. Using ctDNA we can track tumor specific mutations after initial treatment (Butler et al. PLoS One 2015). We are deploying these approaches in clinical trials to alter treatment.