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Data & Models
Mitogenesis Networks
Migration Networks
DNA Damage Networks

Mitogenesis Networks

The goal of the Mitogenic Networks Project is the development of high-level statistical and specific physico-chemical models that describe key features of mitogenic signaling networks activated by ErbB receptors and by oncogenic K-ras.

We have made significant progress in developing models of ErbB family mitogenic signaling networks over the past few years. We will extend these efforts to include additional receptor tyrosine kinases while constructing models for EGFR and Ras mutations that are directly associated with poor prognosis in human cancers of the central nervous and respiratory systems. Models will be developed and tested at a variety of scales, including in vitro cell culture systems, murine xenografts, and mouse cancer models. In addition, we will extend our computational models of mitogenic signaling to include transcriptional regulatory networks, to provide a more global, quantitative model of cellular regulation in response to oncogenic mutation. The ultimate goal is to apply these quantitative models to directly test their relevance in predicting responsiveness of human tumors to selected chemotherapeutic agents. We will integrate this mitogenic signaling network program with the other core programs in this Center, to understand how mitogenic signaling networks activated by EGFR and Ras mutants may affect chemotherapeutic sensitivity (DNA Damage Signaling Networks/Therapeutics) and cell invasion and metastasis (Migration Signaling Networks).

Specific Aim 1 - Logic and mechanistic modeling of the ErbB network
Specific Aim 2 - Integrating proteomic and transcriptomic networks
Specific Aim 3 - Network dysregulation by EGFR mutations
Specific Aim 4 - Network dysregulation by K-ras mutations


Aldridge BB, Saez-Rodriguez J, Muhlich JL, Sorger PK, Lauffenburger DA. Fuzzy logic analysis of kinase pathway crosstalk in TNF/EGF/insulin-induced signaling. PLoS Comput Biol. 2009 Apr;5(4):e1000340.

Chen WW, Schoeberl B, Jasper PJ, Niepel M, Nielsen UB, Lauffenburger DA, Sorger PK. Input-output behavior of ErbB signaling pathways as revealed by a mass action model trained against dynamic data. Mol Syst Biol. 2009;5:239.

Haigis KM, Kendall KR, Wang Y, Cheung A, Haigis MC, Glickman JN, Niwa-Kawakita M, Sweet-Cordero A, Sebolt-Leopold J, Shannon KM, Settleman J, Giovannini M, Jacks T. Differential effects of oncogenic K-Ras and N-Ras on proliferation, differentiation and tumor progression in the colon. Nat Genet. 2008 May;40(5):600-8.

Huang PH, Cavenee WK, Furnari FB, White FM. Uncovering therapeutic targets for glioblastoma: a systems biology approach. Cell Cycle. 2007 Aug 20; 6(22): 2750-4.

Huang PH, Mukasa A, Bonavia R, Flynn R, Brewer ZE, Cavenee WK, Furnari FB, White FM. Quantitative analysis of EGFRvIII cellular signaling networks reveals a combinatorial therapeutic strategy for glioblastoma. Proc Natl Acad Sci U.S.A. 2007 Jul 31; 104(31):12867-72.

Kreeger P, Mandhana R, Alford SK, Haigis K, Lauffenburger DA. Ras mutations impact TNF-induced apoptosis in colon carcinoma cells via ERK-modulatory negative and positive feedback circuits along with non-ERK pathway effects. Submitted.

Kumar MS, Erkeland SJ, Pester RE, Chen CY, Ebert MS, Sharp PA, Jacks T. Suppression of non-small cell lung tumor development by the let-7 microRNA family. Proc Natl Acad Sci U S A. 2008 Mar 11;105(10):3903-8.

Lazzara M, Lane K, Chan R, Jasper P, Sorger PK, Jacks T, Yaffe MB, Neel BG, Lauffenburger DA. Incomplete Shp-2 mediated ERK activation in EGFR-mutant lung cancers leads to increased cellular sensitivity to gefitinib. Submitted.

Samaga R, Saez-Rodriguez J, Alexopoulos L, Sorger PK, Klamt S. The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. PLoS Comp Biol, in press.

Saez-Rodriguez J, Alexopoulos L, Epperlein J, Samaga R, Lauffenburger DA, Klamt S, Sorger PK. Discrete logic models as a means to link pathway maps to functional analysis of signal transduction in mammalian cells. Submitted.

White FM. Quantitative phosphoproteomic analysis of signaling network dynamics. Curr Opin Biotechnol. 2008 Aug;19(4):404-9.

Principal Investigators  

Forest White, Ph.D., Project Leader
Associate Professor of Biological Engineering; David H. Koch Institute

Ernest Fraenkel, Ph.D.
Assistant Professor of Biological Engineering

Tyler Jacks, Ph.D.
Professor of Biology; Director, David H. Koch Institute

Douglas Lauffenburger, Ph.D.
Professor of Biological Engineering, Chemical Engineering, and Biology; Head, Dept. of Biological Engineering; David H. Koch Institute

Peter K. Sorger, Ph.D.
Professor of Biology and Biological Engineering, MIT; Professor of Systems Biology, Harvard Medical School

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