Document text
Principal Investigator: William S Hlavacek
Organization: YALE UNIVERSITY
Fiscal Year: 2024
Award: $643,676
Funding agency: National Cancer Institute
PROJECT SUMMARY/ABSTRACT
Small molecule inhibitors targeting the RAF/MEK/ERK pathway have become potent tools in precision medicine,
but their clinical efficacy is highly variable across the diversity of RAS- and BRAF-mutated cancers. Even in
susceptible cancers, these inhibitors rarely give durable responses. Studying the causes of resistance, which
include ‘paradoxical’ ERK pathway activation by RAF inhibitors, has revealed complex molecular adaptations in
the complicated networks comprised of RAF and ERK pathway kinases. These complexities limit our ability to
understand and predict effectiveness of targeted therapies, especially in combination – despite decades of
intense study, including mathematical modeling. Accurate predictions require understanding not only of the
molecular complexities of protein kinase regulation and the intricate systems-level behavior of the networks that
kinase constitute, but also of how these two levels of control are coupled. The challenge of accurately predicting
effectiveness of targeted therapies and their combinations therefore demands an amalgamation of molecular
and systems biology approaches. The systems biology project proposed here aims to identify optimal
combinations of kinase inhibitors through mechanistic models that integrate understanding of both:
1) Conformation selectivity of kinase inhibitors – affecting structural, thermodynamic and kinetic properties of the
targeted kinase(s); and 2) Systems-level network properties, including feedback loops, mutations and
kinase/scaffold abundances, which can modify feedback loops and allow normally inconsequential kinase
isoforms to compensate for isoform-specific kinase inhibition. Combining these features necessitates novel
approaches to modeling cell signaling that directly link molecular/structural and network facets to predict which
inhibitors and their combinations can efficiently suppress oncogenic signaling while disabling or delaying signal
recovery, growth, and drug resistance. We propose to develop such next-generation multiscale models of
oncogenic ERK signaling and drug responses, and to establish a new conceptual foundation for discovering
effective drug combinations by integrating structural, thermodynamic and kinetic information – and combining
short time-scale molecular dynamics (MD) with long time-scale modeling of systems-level dynamics. We will test
our model predictions rigorously by integrating and iterating modeling and experimental studies. Experimental
studies will begin in paired isogenic cancer cell lines with defined mutational differences. Once model predictions
are suitably robust, we will progress to panels of cancer cell lines, then to cell line-derived xenografts in vivo,
and then to patient-derived xenografts and genetically engineered mouse models (GEMMs) of melanoma – as
a presage to clinically integrated predictions. We will determine if the strategy of hitting a kinase by two (or more)
inhibitors with distinct conformation selectivity – as appears promising in our preliminary data – is generally
applicable, can be combined with inhibition of different targets within a pathway, and can be understood at a
detailed mechanistic level using our multiscale models.
Terms: <ATP-protein phosphotransferase><Accounting><Affect><B-raf-1><BAY 54-9085><BRAF><BRAF gene><Behavior><Binding><Biochemical><Biologic Models><Biological Models><CaCo2><Caco-2 Cells><Cancer cell line><Cancers><Cell Body><Cell Communication and Signaling><Cell Growth in Number><Cell Line><Cell Multiplication><Cell Proliferation><Cell Signaling><Cell model><CellLine><Cells><Cellular Proliferation><Cellular model><Clinic><Clinical><Colorectal Cancer><Compensation><Complex><Computer Models><Computerized Models><Coupled><DNA Molecular Biology><Data><Dimerization><Disabling><Drug Combinations><Drug Controls><Drug Targeting><Drug resistance><Drugs><Dryness><Effectiveness><Extracellular Signal-Regulated Kinase Gene><Feedback><Foundations><Free Energy><GEM model><GEMM model><Generalized Growth><Genetic><Genetic Alteration><Genetic Change><Genetic defect><Genetically Engineered Mouse><Goals><Growth><Heterograft><Heterologous Transplantation><In Vitro><Intracellular Communication and Signaling><Isoforms><KSR gene><KSR1><Kinase Family Gene><Kinase Suppressor of RAS-1><Kinases><Kinetics><Knock-out><Knockout><Link><MAP Kinase Gene><MAPK><MEKs><Malignant Melanoma><Malignant Neoplasms><Malignant Tumor><Math Models><Medication><Melanoma><Melanoma Cell><Mitogen-Activated Protein Kinase Gene><Model System><Modeling><Molecular><Molecular Biology><Molecular Configuration><Molecular Conformation><Molecular Dynamics Simulation><Molecular Interaction><Molecular Stereochemistry><Mutate><Mutation><Oncogenic><PDX model><Pathway interactions><Patient derived xenograft><Pharmaceutical Preparations><Phosphotransferase Gene><Phosphotransferases><Position><Positioning Attribute><Predisposition><Property><Protein Dimerization><Protein Isoforms><Protein Kinase><Proteins><RAFB1><RAS driven cancer><RAS driven malignancy><Recovery><Regulation><Resistance><Scaffolding Protein><Signal Pathway><Signal Transduction><Signal Transduction Systems><Signaling><Signaling Factor Proto-Oncogene><Signaling Pathway Gene><Signaling Protein><Sorafenib><Specificity><Strains Cell Lines><Susceptibility><System><Systems Biology><Testing><Therapeutic><Thermodynamic><Thermodynamics><Tissue Growth><Transphosphorylases><Validation><Work><Xenograft><Xenograft procedure><Xenotransplantation><biological signal transduction><cell transformation><clinical efficacy><computational modeling><computational models><computer based models><computer based prediction><computerized modeling><conformation><conformational><conformational state><conformationally><conformations><cultured cell line><drug efficacy><drug resistant><drug sensitivity><drug/agent><experiment><experimental research><experimental study><experiments><genetically engineered mouse model><genetically engineered murine model><genome mutation><glycogen synthase a kinase><hydroxyalkyl protein kinase><in vivo><inhibitor><kinase inhibitor><knock-down><knockdown><malignancy><mathematic model><mathematical model><mathematical modeling><molecular dynamics><multi-scale computational modeling><multi-scale mathematical modeling><multi-scale modeling><multiscale computational modeling><multiscale mathematical modeling><multiscale modeling><neoplasm/cancer><new approaches><next generation><novel><novel approaches><novel strategies><novel strategy><ontogeny><overexpress><overexpression><pathway><patient derived xenograft model><phosphorylase b kinase kinase><precision medicine><precision-based medicine><predictive modeling><prevent><preventing><protein expression><resistance to Drug><resistance to therapy><resistant><resistant to Drug><resistant to therapy><response><scaffold><scaffolding><small molecular inhibitor><small molecule inhibitor><standard of care><success><synergism><targeted drug therapy><targeted drug treatments><targeted therapeutic><targeted therapeutic agents><targeted therapy><targeted treatment><therapeutic resistance><therapy resistant><tool><transformed cells><treatment resistance><tumor><v-raf Murine Sarcoma Viral Oncogene Homolog B1><validations><xeno-transplant><xeno-transplantation>