Research Labs

Physician-scientist Nai-Kong Cheung focuses on engineering antibodies and immune cells to treat both solid tumors and liquid tumors in children.

Physician-scientist Ping Chi studies genetic and epigenetic mechanisms of transcriptional regulation by oncogenic factors in GIST, MPNST, melanoma and other solid tumors.

The Choi Lab develops new synthetic biology tools to study cell-fate decisions in development.

Jonathan Coleman is a physician-scientist focused on translational research, cancer genomics, and patient-derived organoid models in the study of urologic malignancies. Ongoing work includes the development of local ablative therapies, their influence on the tumor microenvironment, and implications for therapy response.

Physician-scientist Aimee Crago studies mechanisms by which common genomic events drive initiation and progression of soft tissue tumors.

Yael David’s lab develops and applies methods in chemical biology toward studying epigenetic regulation and its correlation with disease states.

My research involves the elucidation of genetic and biologic insights of human malignant lymphomas. We leverage large-scale unbiased profiling including genomics, transcriptomics, proteomics to identify candidate oncogenes and proteins that are pathogenetically relevant in lymphoma. We utilize molecular technologies, human tumor tissues and patient-derived xenografts and transgenic animal models to determine the functional significance of novel genes and proteins involved in lymphoma pathogenesis. Using primary tumors as our discovery models, the overall goal of our studies is to understand novel mechanisms of oncogenesis, identify tumor biomarkers and vulnerabilities that will facilitate early detection and precision therapies that improve patient outcomes.

Physician-scientist James Fagin focuses on the pathogenesis of thyroid cancer and the role of oncogenic kinases.

Physician-scientist Karuna Ganesh studies stem cell plasticity in metastasis, therapy resistance and tissue regeneration.

The Greenbaum lab utilizes techniques from statistical physics, information theory, and evolutionary biology to better understand the role of self/non-self discrimination in tumor evolution, model response to immunotherapies, and quantify drivers of virus and cancer evolution.