Peter Sorger
The Sorger lab applies experimental and computational methods to the analysis of mechanical and regulatory processes controlling eukaryotic cell division. They seek to construct data-driven, systems-wide models of cellular function that contain detailed mechanistic information on the activities of individual proteins.
Harvard Medical School, Department of Systems Biology
Alpert Building, Room 438
200 Longwood Ave.
Boston, MA 02115
Tel: 617-432-6901
Email: peter_sorger@hms.harvard.edu
Website:
http://sorger.med.harvard.edu/
Lab Size: Over 20
Summary
The Sorger Laboratory studies mammalian cancer biology with a focus on cell signaling networks involved in disease and the therapeutic drugs that target them. We combine cell biological, biochemical and mathematical approaches with the overall aim of deriving novel mechanistic and systems-wide insight into cellular physiology and human disease. Modeling methods range from purely statistical and correlative to physicochemical and mechanistic but in all cases we rigorously link models to experimental data on protein states, signaling biochemistry, and cellular phenotypes.
Our laboratory is particularly interested in death and survival signaling in response to death ligands such as TRAIL and TNF and growth factors such as EGF, IGF and HGF. We study how these ligands affect normal cells and how the signals they provoke are misregulated in cancer. A significant fraction of the lab’s effort is devoted to developing and applying new mathematical methods for model assembly, calibration and validation (including logic-based modeling, rules-based physicochemical modeling, Bayesian calibration and optimal experimental design). We also develop and exploit mouse “models” of cancer that recapitulate key features of human disease (particularly breast cancer and hepatocellular carcinoma). Finally, we develop and apply a wide variety of live-cell microscopy methods as well as multiplex approaches to biochemical measurement. Individual lab members are encouraged to undertake projects that combine computation and experimentation.
Publications
Chen WW, Niepel M, and Sorger PK (2010). Classic and Contemporary Approaches to Modeling Biochemical Reactions. Genes Dev 24, 1861-1875. PMC2932968.
Alexopoulos LG, Saez-Rodriguez J, Cosgrove BD, Lauffenburger DA, and Sorger PK (2010). Networks Inferred from Biochemical Data Reveal Profound Differences in Toll-Like Receptor and Inflammatory Signaling between Normal and Transformed Hepatocytes. Mol Cell Proteomics 9, 1849-1865. PMC2938121.
Lazzara MJ, Lane K, Chan R, Jasper PJ, Yaffe MB, Sorger PK, Jacks T, Neel BG, and Lauffenburger DA (2010). Impaired Shp2-Mediated Extracellular Signal-Regulated Kinase Activation Contributes to Gefitinib Sensitivity of Lung Cancer Cells with Epidermal Growth Factor Receptor-Activating Mutations. Cancer Res 70, 3843-3850. PMC2862125.
Cosgrove BD, Alexopoulos LG, Hang TC, Hendriks BS, Sorger PK, Griffith LG, and Lauffenburger DA (2010). Cytokine-Associated Drug Toxicity in Human Hepatocytes Is Associated with Signaling Network Dysregulation. Mol Biosyst 6, 1195-1206. PMC2943488.
Espelin CW, Goldsipe A, Sorger PK, Lauffenburger DA, de Graaf D, and Hendriks BS (2010). Elevated Gm-Csf and Il-1beta Levels Compromise the Ability of P38 Mapk Inhibitors to Modulate Tnfalpha Levels in the Human Monocytic/Macrophage U937 Cell Line. Mol Biosyst.