1
|
Trogdon M, Abbott K, Arang N, Lande K, Kaur N, Tong M, Bakhoum M, Gutkind JS, Stites EC. Systems modeling of oncogenic G-protein and GPCR signaling reveals unexpected differences in downstream pathway activation. NPJ Syst Biol Appl 2024; 10:75. [PMID: 39013872 PMCID: PMC11252164 DOI: 10.1038/s41540-024-00400-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 06/27/2024] [Indexed: 07/18/2024] Open
Abstract
Mathematical models of biochemical reaction networks are an important and emerging tool for the study of cell signaling networks involved in disease processes. One promising potential application of such mathematical models is the study of how disease-causing mutations promote the signaling phenotype that contributes to the disease. It is commonly assumed that one must have a thorough characterization of the network readily available for mathematical modeling to be useful, but we hypothesized that mathematical modeling could be useful when there is incomplete knowledge and that it could be a tool for discovery that opens new areas for further exploration. In the present study, we first develop a mechanistic mathematical model of a G-protein coupled receptor signaling network that is mutated in almost all cases of uveal melanoma and use model-driven explorations to uncover and explore multiple new areas for investigating this disease. Modeling the two major, mutually-exclusive, oncogenic mutations (Gαq/11 and CysLT2R) revealed the potential for previously unknown qualitative differences between seemingly interchangeable disease-promoting mutations, and our experiments confirmed oncogenic CysLT2R was impaired at activating the FAK/YAP/TAZ pathway relative to Gαq/11. This led us to hypothesize that CYSLTR2 mutations in UM must co-occur with other mutations to activate FAK/YAP/TAZ signaling, and our bioinformatic analysis uncovers a role for co-occurring mutations involving the plexin/semaphorin pathway, which has been shown capable of activating this pathway. Overall, this work highlights the power of mechanism-based computational systems biology as a discovery tool that can leverage available information to open new research areas.
Collapse
Affiliation(s)
- Michael Trogdon
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- Pfizer, La Jolla, CA, 92037, USA
| | - Kodye Abbott
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Nadia Arang
- Moores Cancer Center, University of California, San Diego, La Jolla, CA, 92093, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Kathryn Lande
- Razavi Newman Integrative Genomics and Bioinformatics Core, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Navneet Kaur
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Melinda Tong
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Mathieu Bakhoum
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, 06520, USA
- Yale Cancer Center, Yale School of Medicine, New Haven, CT, 06520, USA
| | - J Silvio Gutkind
- Moores Cancer Center, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Pharmacology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Edward C Stites
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, 06520, USA.
- Yale Cancer Center, Yale School of Medicine, New Haven, CT, 06520, USA.
| |
Collapse
|
2
|
Stites EC. Computational Random Mutagenesis to Investigate RAS Mutant Signaling. Methods Mol Biol 2023; 2634:329-335. [PMID: 37074586 PMCID: PMC10530643 DOI: 10.1007/978-1-0716-3008-2_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
This chapter describes how mathematical models can be used to investigate the possible range of behaviors for mutant forms of a protein. A mathematical model of the RAS signaling network that has previously been developed and applied to specific RAS mutants will be adapted for the process of computational random mutagenesis. By using this model to computationally investigate the range of RAS signaling outputs that would be anticipated over a wide range of the relevant parameter space, one can gain intuition about the types of behaviors that would be demonstrated by biological RAS mutants.
Collapse
Affiliation(s)
- Edward C Stites
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
| |
Collapse
|
3
|
McFall T, Diedrich JK, Mengistu M, Littlechild SL, Paskvan KV, Sisk-Hackworth L, Moresco JJ, Shaw AS, Stites EC. A systems mechanism for KRAS mutant allele-specific responses to targeted therapy. Sci Signal 2019; 12:eaaw8288. [PMID: 31551296 PMCID: PMC6864030 DOI: 10.1126/scisignal.aaw8288] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Cancer treatment decisions are increasingly guided by which specific genes are mutated within each patient's tumor. For example, agents inhibiting the epidermal growth factor receptor (EGFR) benefit many colorectal cancer (CRC) patients, with the general exception of those whose tumor includes a KRAS mutation. However, among the various KRAS mutations, that which encodes the G13D mutant protein (KRASG13D) behaves differently; for unknown reasons, KRASG13D CRC patients benefit from the EGFR-blocking antibody cetuximab. Controversy surrounds this observation, because it contradicts the well-established mechanisms of EGFR signaling with regard to RAS mutations. Here, we identified a systems-level, mechanistic explanation for why KRASG13D cancers respond to EGFR inhibition. A computational model of RAS signaling revealed that the biophysical differences between the three most common KRAS mutants were sufficient to generate different sensitivities to EGFR inhibition. Integrated computation with experimentation then revealed a nonintuitive, mutant-specific dependency of wild-type RAS activation by EGFR that is determined by the interaction strength between KRAS and the tumor suppressor neurofibromin (NF1). KRAS mutants that strongly interacted with and competitively inhibited NF1 drove wild-type RAS activation in an EGFR-independent manner, whereas KRASG13D weakly interacted with and could not competitively inhibit NF1 and, thus, KRASG13D cells remained dependent on EGFR for wild-type RAS activity. Overall, our work demonstrates how systems approaches enable mechanism-based inference in genomic medicine and can help identify patients for selective therapeutic strategies.
Collapse
Affiliation(s)
- Thomas McFall
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jolene K Diedrich
- Mass Spectrometry Core for Proteomics and Metabolomics, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Meron Mengistu
- Department of Research Biology, Genentech, South San Francisco, CA 94080, USA
| | - Stacy L Littlechild
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Kendra V Paskvan
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Laura Sisk-Hackworth
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - James J Moresco
- Mass Spectrometry Core for Proteomics and Metabolomics, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Andrey S Shaw
- Department of Research Biology, Genentech, South San Francisco, CA 94080, USA
| | - Edward C Stites
- Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
| |
Collapse
|
4
|
Erickson KE, Rukhlenko OS, Posner RG, Hlavacek WS, Kholodenko BN. New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling. Semin Cancer Biol 2019; 54:162-173. [PMID: 29518522 PMCID: PMC6123307 DOI: 10.1016/j.semcancer.2018.02.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 02/13/2018] [Accepted: 02/22/2018] [Indexed: 01/04/2023]
Abstract
RAS is the most frequently mutated gene across human cancers, but developing inhibitors of mutant RAS has proven to be challenging. Given the difficulties of targeting RAS directly, drugs that impact the other components of pathways where mutant RAS operates may potentially be effective. However, the system-level features, including different localizations of RAS isoforms, competition between downstream effectors, and interlocking feedback and feed-forward loops, must be understood to fully grasp the opportunities and limitations of inhibiting specific targets. Mathematical modeling can help us discern the system-level impacts of these features in normal and cancer cells. New technologies enable the acquisition of experimental data that will facilitate development of realistic models of oncogenic RAS behavior. In light of the wealth of empirical data accumulated over decades of study and the advancement of experimental methods for gathering new data, modelers now have the opportunity to advance progress toward realization of targeted treatment for mutant RAS-driven cancers.
Collapse
Affiliation(s)
- Keesha E Erickson
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Oleksii S Rukhlenko
- Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland
| | - Richard G Posner
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA
| | - William S Hlavacek
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA; University of New Mexico Comprehensive Cancer Center, Albuquerque, NM, USA
| | - Boris N Kholodenko
- Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland; Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Ireland; School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland.
| |
Collapse
|
5
|
Stites EC, Shaw AS. Quantitative Systems Pharmacology Analysis of KRAS G12C Covalent Inhibitors. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2018; 7:342-351. [PMID: 29484842 PMCID: PMC5980551 DOI: 10.1002/psp4.12291] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 12/19/2017] [Accepted: 01/22/2018] [Indexed: 12/24/2022]
Abstract
KRAS has proven difficult to target pharmacologically. Two strategies have recently been described for covalently targeting the most common KRAS mutant in lung cancer, KRAS G12C. Previously, we developed a computational model of the processes that regulate Ras activation. Here, we use this model to investigate KRAS G12C covalent inhibitors. We updated the model to include Ras protein turnover, and validation demonstrates that our model performs well in areas of G12C targeting where conventional wisdom struggles. We then used the model to investigate possible strategies to improve KRAS G12C inhibitors and identified GEF loading as a mechanism that could improve efficacy. Our simulations also found resistance‐promoting mutations may reverse which class of KRAS G12C inhibitor inhibits the system better, suggesting that there may be value to pursuing both types of KRAS G12C inhibitors. Overall, this work demonstrates areas in which systems biology approaches can inform Ras drug development.
Collapse
Affiliation(s)
- Edward C Stites
- Division of Laboratory and Genomic Medicine, Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Andrey S Shaw
- Research Biology, Genentech, South San Francisco, California, USA
| |
Collapse
|