Ph.D. in Biochemistry Trinity College Cambridge, 1987
Peter Sorger is Director and PI of the Cell Decision Process Center, an NIH Center of Excellence in Systems Biology. The CDP Center applies computational, microsystems, and cell biology approaches to the study of proliferation and programmed cell death in human cells.
Peter Sorger holds a joint appointment as a Professor of Biology and Biological Engineering at MIT and associate appointments in the MIT Center for Cancer Research and the Broad Institute. He will join the Harvard faculty as a Professor of Systems Biology in September, 2006. Sorger received his A.B. from Harvard College, his Ph.D. from Trinity College Cambridge, U.K., and trained as a postdoctoral fellow with Harold Varmus and Andrew Murray at the University of California, San Francisco. Sorger is a co-founder of two start-up companies, serves on the corporate and scientific advisory boards of three other private companies, chairs the CSF study section at the NIH and is co-founder of the OME open-source image informatics effort. Sorger lives with his wife and twin four-year old sons in Winchester, Massachusetts.
Sorger’s lab of 26 graduate students, postdoctoral fellows and staff scientists is involved in research in both computational and experimental systems biology. The overall goals of lab are to understand the processes controlling death-survival decisions in human cells and the mechanisms responsible for accurate segregation of the genome during cell division. Misregulation of death-survival decisions and chromosome segregation are common in cancer, and the Sorger Lab is actively involved in experiments in human cells and transgenic mice that aim to understand how genomic instability and uncontrolled cell growth promote tumorigenesis. These problems are addressed from a “systems biology” perspective that combines experimental and computational analysis to construct quantitative biological models combining detailed molecular insight with broad system-wide perspective. The Sorger Lab has become increasingly interested in the mechanisms of action of standard and investigational chemotherapeutics and their patient-specific effects. Research into these agents is more mechanistic that genomic medicine and more biological than traditional drug discovery.
Research in the CDP Center
Precise control of cell proliferation and fate by extracellular growth factors is essential for tissue development and homeostasis. Extra-cellular cues drive cell division and programmed cell death via complex signal transduction circuits comprised of receptors, kinases, phosphatases, transcription factors etc. Not surprisingly, many components of these signal transduction circuits are oncogenes or tumor suppressors, underlining the importance of understanding signaling in normal tissues and of targeting aberrant signaling in disease.
Molecular genetics has been extremely successful in identifying the components of signal transduction circuits and in uncovering important interactions among signaling proteins. Understanding the functions of signaling proteins in normal physiology and disease has been elusive however, and most biological regulation can be ascribed not to the actions of a single protein but to networks of proteins interacting in a complex, time-dependent fashion. In the past few years our laboratory has focused on the physiological responses of cells to extracellular cues, and particularly to combinations of ligands that induce conflicting proliferation-apoptosis signals. We build and test systems biology models combining network behavior and precise mechanistic information about individual proteins. These models are numerical, but they are formulated on the basis of extensive empirical data and subjected to rigorous experimental verification.
Our current work focuses on the responses of human cells to epidermal growth factor (EGF and related growth factors), tumor necrosis factor (TNF and other trimeric cell death factors) and insulin (and insulin-like growth factors; IGFs) individually or in combination. Early successes include the collection of an ~10,000 measurement data compendium that quantifies time-varying activities of signaling proteins downstream of TNF and ErbB (the four-member EGFR family) receptors. The application of classifier-based regression to this data has revealed that, in epithelial cells, TNF provokes a multi-step autocrine cascade that plays out over a period of at least 24 hr. Immediately after TNF addition, activated TNFR provokes pro-apoptotic signals and also leads to the release of pre-synthesized TGFα, which binds to the EGF receptor and acts in an anti-apoptotic fashion. Several hours later, the combined actions of TNF and autocrine TGFα lead to IL1α release, activating the IL1 receptor and adding a pro-apoptotic stimulus. In a final twist, release of IL1 receptor antagonist (IL1ra) is induced, terminating IL1R signaling. The overall effect of this three-part autocrine cascade is to add sequential layers of pro and anti-apoptotic signaling that set the level of cell death in a self-limiting fashion. We propose that time-dependent crosstalk among synergistic and antagonistic autrocrine circuits may be a general mechanism of biological control, particularly in complex tissues
Although large-scale modeling of the type described above is useful for constructing course-grained physiological models, we are ultimately interested in explaining cell behavior in terms of molecular mechanism. Working closely with the Lauffenburger lab, we have devoted considerable effort to the construction and training of physico-chemical models of ErbB and TNF receptor networks. These models are being used to explore the basis of cell-type specific variation in responses to EGF and TNF and in exploring the mechanisms of action of receptor-targeting therapeutics. In the case of ErbB receptors, we are attempting to develop predictive models of Erbitux (anti-ErbB1) and Herceptin (anti-ErbB2) efficacy, and to understand how ErbB1 receptor mutations sensitize cells to small molecules such as Gefitinib (Iressa) and lapatinib (CI1033). While sensitivity is closely associated with mutation, over-expression of wild type receptor also causes sensitivity. Moreover, sensitivity cannot be transferred by moving ErbB1 mutant genes into resistant cells, nor by gene replacement in the mouse. This strongly suggests that sensitivity is a property both of the ErbB1 mutation and of the network in which ErbB1 is embedded in tumor cells. Preliminary simulation and experimental data suggest that alterations in receptor trafficking are key aspects of this sensitizing environment.
Selected CDP Publications
Swedlow JR, Goldberg I, Brauner E, Sorger PK. (2003), Informatics and quantitative analysis in biological imaging.” Science, 300, 100-102.
Sorger, P.K (2004) “A Reductionist’s Systems Biology,” Curr Opin Cell Biol 17, 9-11.
Gaudet, S., Janes, K.A., Albeck,J, Pace, E.A., Lauffenburger, D.A. and Sorger, P.K. (2005)“A compendium of signals and responses triggered by prodeath and prosurvival cytokines” Mol Cell Proteomics, 10, 1569-1590
Janes. K.A., Albeck, J.G., Gaudet, S., Sorger, P.K. Lauffenburger, D.A, Yaffe M.B. “A (2005) Systems Model of Signaling Identifies a Molecular Basis Setthat Predicts Cytokine-Induced Apoptosis,” Science, 310, 1646-53.
Janes. K.A., Gaudet, S., Albeck, J.G., Nielsen, U.B., Lauffenburger, D.A. and Sorger, P.K. (2006) “The response of human epithelial cells to TNF involves an inducible autocrine cascade” Cell, 124, 1225-39.
Albeck, J.G., Burke, J.M., Aldridge, B.B., Zhang, M., Lauffenburger, D.A., and Sorger, P.K. (2008a). Quantitative analysis of pathways controlling extrinsic apoptosis in single cells. Mol Cell 30, 11-25.
Albeck, J.G., Burke, J.M., Spencer, S.L., Lauffenburger, D.A., and Sorger, P.K. (2008b). Modeling a snap-action, variable-delay switch controlling extrinsic cell death. PLoS Biol 6, 2831-2852
Spencer, S.L., Gaudet, S., Albeck, J.G., Burke, J.M., and Sorger, P.K. (2009). Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis. Nature, 59(7245):428-32.
Selected other CDP Publications
Meraldi, P., Draviam, V. and Sorger, P.K. (2004) “Timing and checkpoints in the regulation of mitotic progression,” Dev. Cell 7, 45-60.
DeWulf, P.D., McAinsh, A., and Sorger, P.K. (2003) “Hierarchical assembly of the budding yeast kinetochore from multiple subcomplexes” Genes Dev., 23, 2902-2921.
Miranda J.J., De Wulf. P, Sorger, P.K. and Harrison. S.C “The yeast DASH complex forms closed rings on microtubules,” (2005). Nature Struc. Biol. 12, 138-43.
Saez-Rodriguez, J., Goldsipe, A., Muhlich, J., Alexopoulos, L.G., Millard, B., Lauffenburger, D.A., and Sorger, P.K. (2008). Flexible Informatics for Linking Experimental Data to Mathematical Models via DataRail. Bioinformatics 24, 840-847.