Evidence map›Paper›PMID 35494017›Full record

ArticleFrontiers in oncology2022

Computational Model of Heterogeneity in Melanoma: Designing Therapies and Predicting Outcomes.

Arran Hodgkinson, Dumitru Trucu, Matthieu Lacroix, Laurent Le Cam, Ovidiu Radulescu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 36% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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 at 5 institutions in 2 countries.

Arran HodgkinsonLiving Systems Institute, University of Exeter, Exeter, United Kingdom.
Dumitru TrucuDivision of Mathematics, University of Dundee, Dundee, United Kingdom.
Matthieu LacroixIRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Univ Montpellier, Institut régional du Cancer de Montpellier, Montpellier, France.
Laurent Le CamIRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Univ Montpellier, Institut régional du Cancer de Montpellier, Montpellier, France.
Ovidiu RadulescuLPHI, University of Montpellier and CNRS UMR 5235, Montpellier, France.
Centre National de la Recherche Scientifique · FRLa Ligue Contre le Cancer · FRUniversité de Montpellier · FRUniversity of Dundee · GBUniversity of Exeter · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cutaneous melanoma is a highly invasive tumor and, despite the development of recent therapies, most patients with advanced metastatic melanoma have a poor clinical outcome. The most frequent mutations in melanoma affect the BRAF oncogene, a protein kinase of the MAPK signaling pathway. Therapies targeting both BRAF and MEK are effective for only 50% of patients and, almost systematically, generate drug resistance. Genetic and non-genetic mechanisms associated with the strong heterogeneity and plasticity of melanoma cells have been suggested to favor drug resistance but are still poorly understood. Recently, we have introduced a novel mathematical formalism allowing the representation of the relation between tumor heterogeneity and drug resistance and proposed several models for the development of resistance of melanoma treated with BRAF/MEK inhibitors. In this paper, we further investigate this relationship by using a new computational model that copes with multiple cell states identified by single cell mRNA sequencing data in melanoma treated with BRAF/MEK inhibitors. We use this model to predict the outcome of different therapeutic strategies. The reference therapy, referred to as "continuous" consists in applying one or several drugs without disruption. In "combination therapy", several drugs are used sequentially. In "adaptive therapy" drug application is interrupted when the tumor size is below a lower threshold and resumed when the size goes over an upper threshold. We show that, counter-intuitively, the optimal protocol in combination therapy of BRAF/MEK inhibitors with a hypothetical drug targeting cell states that develop later during the tumor response to kinase inhibitors, is to treat first with this hypothetical drug. Also, even though there is little difference in the timing of emergence of the resistance between continuous and adaptive therapies, the spatial distribution of the different melanoma subpopulations is more zonated in the case of adaptive therapy.

Indexed as

cancer heterogeneitymathematical modelingmelanomasingle cell datatargeted treatment

Identifiers

PMID35494017
PMCPMC9046868
OpenAlexW4226199352

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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 OpenQuestion graph.