I am 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 combination of conventional molecular biology, high throughput genomic and proteomic assays, and bioinformatic analyses in their work.
Two major recent thrusts are the systematic characterization of cancer genomes as part of The Cancer Genome Atlas (TCGA Network, Nature, 2011) and the development and application of methods to reconstruct tumor evolution (Durinck et al. Cancer Discovery, 2011). We aim to push these analyses forward in continued analysis of ovarian cancer genomes as well as kidney and breast cancer genomes.
Modeling of Signaling Systems:
In collaboration with Sach Mukherjee (NKI), Gordon Mills (MD Anderson Cancer Center) and Jim Korkola (OHSU) the group is developing methods for computationally modeling the signaling that occurs in cancer cells. The idea behind the current work is to create Bayesian estimates of signaling systems from both dynamic and static signaling processes.
Immune System Therapies:
It has been observed that the survival of breast cancer patients is related to the presence of immune system signatures and T cell infiltrates in a patient’s tumors. The hypothesis is that stimulating the immune system can be an effective mode of therapy. In collaboration with Peter Lee (City of Hope), Jill Slansky (UC Denver) and John Kappler (Nationwide Jewish) we aim to develop approaches to stimulate the natural immune response in breast cancer patients.
We are funded in these efforts by the NCI Centers for Cancer Systems Biology (icbp.nci.nih.gov/), The Cancer Genome Atlas (cancergenome.nih.gov), a DoD Multi-team award, the Bay Area Breast SPORE, collaborations with private industry, and the Knight Cancer Center at OHSU.