Evidence map›Paper›PMID 29518522›Full record

ReviewSeminars in cancer biology2019

New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling.

Keesha E Erickson, Oleksii S Rukhlenko, Richard G Posner, William S Hlavacek, Boris N Kholodenko

Abstract readReview
In one paragraph

Review in Seminars in cancer biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Dynamic regulation of RAS and RAS signaling.The Biochemical journal · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. The Role of the Guanosine Nucleotide-Binding Protein in the Corpus Luteum.Animals : an open access journal from MDPI · 2021
    Review
  12. Regulation of the Small GTPase Ras and Its Relevance to Human Disease.Methods in molecular biology (Clifton, N.J.) · 2021
    Review
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Keesha E EricksonTheoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
Oleksii S RukhlenkoSystems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland.
Richard G PosnerDepartment of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA.
William S HlavacekTheoretical 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 KholodenkoSystems 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. Electronic address: boris.kholodenko@ucd.ie.

Funding

Hardening Software for Rule-based models-Competitive RevisionR01GM111510 · NIGMS · NORTHERN ARIZONA UNIVERSITY · PI HLAVACEK, WILLIAM S, POSNER, RICHARD G · 2014 to 2023
$2.8M
Computational Model of Autophagy-Mediated Survival in Chemoresistant Lung CancerR01CA197398 · NCI · VAN ANDEL RESEARCH INSTITUTE · PI HLAVACEK, WILLIAM S, MACKEIGAN, JEFFREY PAUL · 2015 to 2019
$2.5M
NCI NIH HHS R01 CA197398NIGMS NIH HHS R01 GM111510
6 · The paper itself

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.

Indexed as

Gene Expression RegulationModels, BiologicalSignal TransductionAnimalsCarrier ProteinsDrug DiscoveryExtracellular Signal-Regulated MAP KinasesHumansMutationNeoplasmsProtein BindingProtein Transportras ProteinsSystems BiologyCarrier ProteinsExtracellular Signal-Regulated MAP Kinasesras ProteinsERK cascadeMathematical modelingMechanistic modelingRASSystems biology

Identifiers

PMID29518522
PMCPMC6123307

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.