Evidence map›Paper›PMID 34958403›Full record

ArticleBulletin of mathematical biology2021

Transition Therapy: Tackling the Ecology of Tumor Phenotypic Plasticity.

Guim Aguadé-Gorgorió, Stuart Kauffman, Ricard Solé

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Modeling tumors as species-rich ecological communities.bioRxiv : the preprint server for biology · 2024
    Article
  7. Article
  8. Article
  9. Updating the Definition of Cancer.Molecular cancer research : MCR · 2023
    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

3 authors.

Guim Aguadé-GorgorióICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003, Barcelona, Spain.ORCID 0000-0001-9467-3027
Stuart KauffmanInstitute for Systems Biology, Seattle, WA, 98109, USA.
Ricard SoléICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003, Barcelona, Spain. ricard.sole@upf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.

Indexed as

Antineoplastic AgentsMelanomaAdaptation, PhysiologicalHumansMathematical ConceptsModels, BiologicalPhenotypeAntineoplastic AgentsCancer ecologyCombination therapiesEpigenetic plasticityPhenotypic switchingTransition therapy

Identifiers

PMID34958403
PMCPMC8712307

What Socratic holds

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LicenceCC BY
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Registered trials

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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.