Rebecca Ihrie, Ph.D.
Assistant Professor of Cancer Biology
Assistant Professor of Neurological Surgery
Ihrie completed her Ph.D. in Cancer Biology at Stanford University, in the lab of Laura D. Attardi. She studied a specific gene (Perp) whose activity is driven by p53, a well-known tumor suppressor that is affected in many tumor types. She became expert in a wide variety of techniques, including measurement of proliferation, cell death, and invasion, modeling tumors in the mouse, and working with human tissue samples. The results of her thesis project were published in Current Biology, Cell, and Cell Death and Differentiation, along with additional collaborative papers.
For her postdoctoral work, she wanted to understand the connection between stem cells and cancer in a therapeutically challenging disease: glioma. She joined the laboratory of Arturo Alvarez-Buylla at UC San Francisco. Her research examined the regulation of normal neural precursors in the mouse and human brain and their involvement in gliomas. In collaboration with neurosurgeons and basic neurobiologists, she identified specific signals that drive neural stem cell identity, studied the properties of stem cells in the pediatric human brain, and helped develop a genetically faithful model of human glioma. This work was published in Neuron, Nature, and Proceedings of the National Academy of Sciences.
She is interested in the combinatorial effects of signaling pathways within stem cells: how are multiple generic signals integrated to give a specific result? How are cells with tremendous proliferative capacity so tightly controlled in normal tissue? Her long-term goals are to determine how the normal proliferation and differentiation of stem cells is controlled in the brain, understand how perturbation of these pathways results in cancer, and identify how intrinsic cellular programs can be reversed or altered to treat human disease. Her laboratory is focused on the interface between stem cell biology and cancer biology, and uses a variety of techniques to work with both mouse models and samples from normal and cancerous human brain.