Evidence map›Paper›PMID 28467408›Full record

ArticlePLoS computational biology2017

Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy.

Robert C Jackson, Giovanni Y Di Veroli, Siang-Boon Koh, Ian Goldlust, Frances M Richards, Duncan I Jodrell

Abstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
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

6 authors.

Robert C JacksonPharmacometrics Ltd, Cambridge, United Kingdom.
Giovanni Y Di VeroliCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-5251-8181
Siang-Boon KohCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Ian GoldlustCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Frances M RichardsCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Duncan I JodrellCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-9360-1670

Funding

Cancer Research UK 15678Cancer Research UK C14303/A17197
6 · The paper itself

Abstract

The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed "cyclotherapy". Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs.

Indexed as

Models, BiologicalAntineoplastic AgentsCell Cycle CheckpointsCell Line, TumorComputational BiologyDrug DiscoveryHumansNeoplasmsPharmacologyAntineoplastic Agents

Identifiers

PMID28467408
PMCPMC5435348

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.