Project3 image

Project 3. EGFR signaling network adaptations to overcome RAS-induced membrane stress in glioblastoma

Co-Leads

Matt Lazzara
Professor of Chemical Engineering & Biomedical Engineering
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Kristen Naegle
Associate Professor of Biomedical Engineering
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Benjamin (BJ) Purow
Professor of Neurology
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Research

Receptor tyrosine kinases (RTKs) such as EGFR drive oncogenic RAS (HRAS, NRAS, KRAS) signaling and are widely amplified in glioblastoma, but these brain cancers are interestingly incapable of tolerating unbridled signaling from mutant RAS. Forced RAS hyperactivity causes excessive vacuolization and macropinocytosis, giving rise to a “death by drinking” phenotype termed methuosis. This phenotype is not unique to glioblastoma, suggesting a general stress on endomembranes and plasma-membrane internalization when RAS is chronically hyperactivated in an unbalanced fashion. Since EGFR activates RAS along with membrane-dependent AKT (AKT1, AKT2, AKT3) signaling, it implies that EGFR-amplified cells must identify strategies to ameliorate membrane stress during glioblastomagenesis. The hypothesis of Project 3 is that glioblastomas rebalance RAS activity by altering intracellular traffic of EGFR itself and location-dependent signaling of the protein tyrosine phosphatase SHP2. Glioblastomas are known to acquire vIII deletions in EGFR that render it deficient in internalization and endolysosomal degradation. SHP2 (PTPN11) is capable of transmitting RAS-activating signals between internalized EGFR and the plasma membrane, but links to glioblastoma phenotypes are just beginning to emerge. Systems complexity lies in the tandem SH2 domains of SHP2, which compete for phosphotyrosines on active EGFR with other activators of ERK (SHC1, GAB1), AKT (PIK3R1, PIK3R2), and alternative pathways (PLCG1). The specific aims are to 1) define the key intermolecular interactions in the EGFR signaling network and mechanistically predict the consequences of network adaptations to EGFRvIII expression; 2) map differential EGFR signaling network activation among glioblastoma cells to the methuosis phenotype through a hybrid mechanistic and data-driven computational model; and 3) test model-derived predictions about signaling control of methuosis in vitro and in vivo using new tools to monitor RAS–ERK and AKT activities concurrently and noninvasively. Significance of Project 3 extends past methuosis as a niche phenotype, because RTK–SHP2 signaling at the plasma membrane impacts the response of glioblastomas to DNA-damaging therapeutics.

Related Publications

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A reaction-diffusion model predicts the intracellular length scale over which EGFR-initiated GAB1-SHP2 complexes persist.
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bioRxiv. 2021; 2021.11.08.467801.
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Combined CDK4/6 and mTOR Inhibition Is Synergistic against Glioblastoma via Multiple Mechanisms.
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Computational analysis of the regulation of EGFR by protein tyrosine phosphatases.
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Correction of motion artifact in cardiac optical mapping using image registration.
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Cyclic Immunofluorescence (CycIF), A Highly Multiplexed Method for Single-cell Imaging.
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Data-Driven Computational Modeling Identifies Determinants of Glioblastoma Response to SHP2 Inhibition.
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Decreased internalisation of erbB1 mutants in lung cancer is linked with a mechanism conferring sensitivity to gefitinib.
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Detecting and segmenting cell nuclei in two-dimensional microscopy images.
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Different Epidermal Growth Factor Receptor (EGFR) Agonists Produce Unique Signatures for the Recruitment of Downstream Signaling Proteins.
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Differential parsing of EGFR endocytic flux among parallel internalization pathways in lung cancer cells with EGFR-activating mutations.
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Diversity in Dimerization Topologies Enables Differential Control of Receptor Tyrosine Kinase Phosphorylation Dynamics.
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IEEE J Biomed Health Inform. 2017; 21(6):1625-32.
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PLoS One. 2012; 7(11):e50292.
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FHL2 interacts with EGFR to promote glioblastoma growth.
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Glioblastoma Cell Resistance to EGFR and MET Inhibition Can Be Overcome via Blockade of FGFR-SPRY2 Bypass Signaling.
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Identifying Determinants of EGFR-Targeted Therapeutic Biochemical Efficacy Using Computational Modeling.
Monast CS, Lazzara MJ.
CPT Pharmacometrics Syst Pharmacol. 2014; 3:e141.
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Interpolation artifacts in sub-pixel image registration. IEEE Trans Image Process.
Rohde GK, Aldroubi A, Healy DM, Jr.
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Mol Biol Cell. 2012; 26(22):4046-56.
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KinPred: A unified and sustainable approach for harnessing proteome-level human kinase-substrate predictions.
Xue B, Jordan B, Rizvi S, Naegle KM.
PLoS Comput Biol. 2021; 17(2):e1008681.
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KSTAR: An algorithm to predict patient-specific kinase activities from phosphoproteomic data.
Crowl S, Jordan B, Ma C, Naegle KM.
Nature Communications. 2022; 13:4283.
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Localization dynamics of endogenous fluorescently-labeled RAF1 in EGF-stimulated cells.
Surve SV, Myers PJ, Clayton SA, Watkins SC, Lazzara MJ, Sorkin A.
Mol Biol Cell. 2018; mbcE18080512.
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Localizing and extracting filament distributions from microscopy images.
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J Microsc. 2015; 258(1):13-23.
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microRNA-7 inhibits the epidermal growth factor receptor and the Akt pathway and is down- regulated in glioblastoma.
Kefas B, Godlewski J, Comeau L, Li Y, Abounader R, Hawkinson M, Lee J, Fine H, Chiocca EA, Lawler S, Purow B.
Cancer Res. 2008; 68(10):3566-72.
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Multi-channel registration of diffusion tensor images using directional information.
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Multivariate signaling regulation by SHP2 differentially controls proliferation and therapeutic response in glioma cells.
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Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy.
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ProteomeScout: a repository and analysis resource for post- translational modifications and proteins.
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Radon Cumulative Distribution Transform Subspace Modeling for Image Classification.
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Regulation of EGFR trafficking and cell signaling by Sprouty2 and MIG6 in lung cancer cells.
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Mol Biosyst. 2012; 8(10):2771-82.
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Sprouty2 Drives Drug Resistance and Proliferation in Glioblastoma.
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Systematic analysis of BRAF(V600E) melanomas reveals a role for JNK/c-Jun pathway in adaptive resistance to drug-induced apoptosis.
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The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.
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