Thomas Graeber *

Thomas G Graeber

Professor, Molecular and Medical Pharmacology, University of California Los Angeles

(310) 206-6122

Laboratory Address:
4338 CNSI, Crump Institute
570 Westwood Plaza
Los Angeles, CA 90095

Lab Number:
(310) 206-7054

Office Address:
4341 CNSI, Crump Institute
570 Westwood Plaza,
Box 951770
Los Angeles, CA 90095

Research Interests

My group is working to understand cancer signaling and metabolism from a systems view. We focus on developing genome-, proteome- and metabolome-wide assays, and applying these assays to measuring and computationally modeling aberrant function in cancer cells. Through collaboration with clinical scientists, we work directly with patient samples and aim to translate our discoveries to clinical applications. We collect high dimensionality data using mass spectrometry-based phosphoproteomic and metabolomic profiling. To integratively analyze this data, we develop computational approaches aimed at overlaying the raw data with known signaling and metabolic network structures. A point of emphasis is how cellular signaling and metabolism is rewired when cancers become resistant to molecularly targeted therapies (e.g. the mutant BRAF kinase inhibitor used in melanoma). Our results have pointed us to the contributions of feedback loops in maintaining cancer signaling and metabolism homeostasis, and we are exploring therapeutic approaches to perturbing these loops synergistically to disrupt cellular equilibrium and induce death in cancer cells. In modeling cancer, one of our goals is to identify minimal sets of informative components that best reflect the state of the cell and serve as molecular targets for diagnostics, imaging, and patient tailored treatment. As with all of systems biology, our research relies on an interdisciplinary approach that merges biology, chemistry, mathematics and computation / bioinformatics.



Thomas Graeber is faculty in the Department of Molecular and Medical Pharmacology and a member of the Crump Institute for Molecular Imaging at UCLA, and is a Melanoma Research Alliance Established Investigator and an American Cancer Society Research Scholar. His background includes physics, cancer biology, signal transduction, metabolism, computational biology, proteomics, and metabolomics. His work builds experimental and computational approaches to studying cancer signaling and metabolism from a systems perspective. His work in cancer biology started with the discovery that hypoxia, a common feature of solid tumors, induces p53 protein levels, and that p53 deficient cells are less prone to undergo apoptosis in low oxygen conditions, conferring a survival advantage. These findings led to a model of hypoxia as a physiological selective force against apoptosis-competent cells in developing tumors, thus explaining the previously unaccounted for high frequency of p53 mutations in cancer. In computational biology, he developed an algorithm to identify potential autocrine signaling loops in cancer using gene expression microarray data. The algorithm integrates biological data (in this case, cognate ligand-receptor partners) into the analysis of raw gene expression data, and a number of leads from this method have been verified to play critical roles in cell signaling. His work in integrated signaling and metabolic networks has repeatedly pointed to the importance of negative and positive feedback loops in cancer phenotypes, and he is investigating approaches to therapeutically disrupting cancer-specific reliance on these feedback mechanisms.


A selected list of publications: