New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling
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.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Univ. College Dublin (United Kingdom)
- Northern Arizona Univ., Flagstaff, AZ (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Univ. of New Mexico Comprehensive Cancer Center, Albuquerque, NM (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1425769
- Report Number(s):
- LA-UR-17-31291
Journal ID: ISSN 1044-579X
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Seminars in Cancer Biology
- Additional Journal Information:
- Journal Volume: 54; Journal ID: ISSN 1044-579X
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; Biological Science; RAS; ERK cascade; Mechanistic modeling; Mathematical modeling; Systems biology
Citation Formats
Erickson, Keesha E., Rukhlenko, Oleksii S., Posner, Richard G., Hlavacek, William S., and Kholodenko, Boris N. New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling. United States: N. p., 2018.
Web. doi:10.1016/j.semcancer.2018.02.008.
Erickson, Keesha E., Rukhlenko, Oleksii S., Posner, Richard G., Hlavacek, William S., & Kholodenko, Boris N. New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling. United States. https://doi.org/10.1016/j.semcancer.2018.02.008
Erickson, Keesha E., Rukhlenko, Oleksii S., Posner, Richard G., Hlavacek, William S., and Kholodenko, Boris N. Mon .
"New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling". United States. https://doi.org/10.1016/j.semcancer.2018.02.008. https://www.osti.gov/servlets/purl/1425769.
@article{osti_1425769,
title = {New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling},
author = {Erickson, Keesha E. and Rukhlenko, Oleksii S. and Posner, Richard G. and Hlavacek, William S. and Kholodenko, Boris N.},
abstractNote = {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.},
doi = {10.1016/j.semcancer.2018.02.008},
journal = {Seminars in Cancer Biology},
number = ,
volume = 54,
place = {United States},
year = {2018},
month = {3}
}
Web of Science
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