Discrete dynamic network modeling of oncogenic signaling: Mechanistic insights for personalized treatment of cancer

Jorge G.T. Zañudo, Steven N. Steinway, Réka Albert

Research output: Contribution to journalReview article

11 Citations (Scopus)

Abstract

Targeted drugs disrupting proteins that are dysregulated in cancer have emerged as promising treatments because of their specificity to cancer cell aberrations and thus their improved side effect profile. However, their success remains limited, largely due to existing or emergent therapy resistance. We suggest that this is due to limited understanding of the entire relevant cellular landscape. A class of mathematical models called discrete dynamic network models can be used to understand the integrated effect of an individual tumor's aberrations. We review the recent literature on discrete dynamic models of cancer and highlight their predicted therapeutic strategies. We believe dynamic network modeling can be used to drive treatment decision-making in a personalized manner to direct improved treatments in cancer.

Original languageEnglish (US)
Pages (from-to)1-10
Number of pages10
JournalCurrent Opinion in Systems Biology
Volume9
DOIs
StatePublished - Jun 2018

Fingerprint

Discrete Dynamics
Network Modeling
Dynamic Networks
Dynamic Modeling
Aberrations
Cancer
Aberration
Tumors
Dynamic models
Neoplasms
Dynamic Model
Decision making
Cells
Mathematical models
Proteins
Discrete Model
Pharmaceutical Preparations
Network Model
Therapy
Specificity

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

Cite this

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abstract = "Targeted drugs disrupting proteins that are dysregulated in cancer have emerged as promising treatments because of their specificity to cancer cell aberrations and thus their improved side effect profile. However, their success remains limited, largely due to existing or emergent therapy resistance. We suggest that this is due to limited understanding of the entire relevant cellular landscape. A class of mathematical models called discrete dynamic network models can be used to understand the integrated effect of an individual tumor's aberrations. We review the recent literature on discrete dynamic models of cancer and highlight their predicted therapeutic strategies. We believe dynamic network modeling can be used to drive treatment decision-making in a personalized manner to direct improved treatments in cancer.",
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Discrete dynamic network modeling of oncogenic signaling : Mechanistic insights for personalized treatment of cancer. / G.T. Zañudo, Jorge; Steinway, Steven N.; Albert, Réka.

In: Current Opinion in Systems Biology, Vol. 9, 06.2018, p. 1-10.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Discrete dynamic network modeling of oncogenic signaling

T2 - Mechanistic insights for personalized treatment of cancer

AU - G.T. Zañudo, Jorge

AU - Steinway, Steven N.

AU - Albert, Réka

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