Publikation:

Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model

Lade...
Vorschaubild

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2019

Autor:innen

Almeida, Luís
Bagnerini, Patrizia
Hughes, Barry D.
Lorenzi, Tommaso

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

ESAIM: Mathematical Modelling and Numerical Analysis. 2019, 53(4), pp. 1157-1190. ISSN 0764-583X. eISSN 1290-3841. Available under: doi: 10.1051/m2an/2019010

Zusammenfassung

We consider a phenotype-structured model of evolutionary dynamics in a population of cancer cells exposed to the action of a cytotoxic drug. The model consists of a nonlocal parabolic equation governing the evolution of the cell population density function. We develop a novel method for constructing exact solutions to the model equation, which allows for a systematic investigation of the way in which the size and the phenotypic composition of the cell population change in response to variations of the drug dose and other evolutionary parameters. Moreover, we address numerical optimal control for a calibrated version of the model based on biological data from the existing literature, in order to identify the drug delivery schedule that makes it possible to minimise either the population size at the end of the treatment or the average population size during the course of treatment. The results obtained challenge the notion that traditional high-dose therapy represents a “one-fits-all solution” in anticancer therapy by showing that the continuous administration of a relatively low dose of the cytotoxic drug performs more closely to i.e. the optimal dosing regimen to minimise the average size of the cancer cell population during the course of treatment.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
510 Mathematik

Schlagwörter

cancer modelling / therapy optimisation / nonlocal parabolic equations / exact solutions / numerical optimal control

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690ALMEIDA, Luís, Patrizia BAGNERINI, Giulia FABRINI, Barry D. HUGHES, Tommaso LORENZI, 2019. Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model. In: ESAIM: Mathematical Modelling and Numerical Analysis. 2019, 53(4), pp. 1157-1190. ISSN 0764-583X. eISSN 1290-3841. Available under: doi: 10.1051/m2an/2019010
BibTex
@article{Almeida2019-07-04Evolu-46589,
  year={2019},
  doi={10.1051/m2an/2019010},
  title={Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model},
  number={4},
  volume={53},
  issn={0764-583X},
  journal={ESAIM: Mathematical Modelling and Numerical Analysis},
  pages={1157--1190},
  author={Almeida, Luís and Bagnerini, Patrizia and Fabrini, Giulia and Hughes, Barry D. and Lorenzi, Tommaso}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46589">
    <dc:creator>Almeida, Luís</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-07-31T13:43:02Z</dc:date>
    <dc:creator>Hughes, Barry D.</dc:creator>
    <dc:creator>Fabrini, Giulia</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-07-31T13:43:02Z</dcterms:available>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/46589"/>
    <dc:language>eng</dc:language>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
    <dcterms:title>Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model</dcterms:title>
    <dc:contributor>Lorenzi, Tommaso</dc:contributor>
    <dcterms:abstract xml:lang="eng">We consider a phenotype-structured model of evolutionary dynamics in a population of cancer cells exposed to the action of a cytotoxic drug. The model consists of a nonlocal parabolic equation governing the evolution of the cell population density function. We develop a novel method for constructing exact solutions to the model equation, which allows for a systematic investigation of the way in which the size and the phenotypic composition of the cell population change in response to variations of the drug dose and other evolutionary parameters. Moreover, we address numerical optimal control for a calibrated version of the model based on biological data from the existing literature, in order to identify the drug delivery schedule that makes it possible to minimise either the population size at the end of the treatment or the average population size during the course of treatment. The results obtained challenge the notion that traditional high-dose therapy represents a “one-fits-all solution” in anticancer therapy by showing that the continuous administration of a relatively low dose of the cytotoxic drug performs more closely to i.e. the optimal dosing regimen to minimise the average size of the cancer cell population during the course of treatment.</dcterms:abstract>
    <dc:contributor>Bagnerini, Patrizia</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
    <dcterms:issued>2019-07-04</dcterms:issued>
    <dc:contributor>Fabrini, Giulia</dc:contributor>
    <dc:creator>Lorenzi, Tommaso</dc:creator>
    <dc:contributor>Almeida, Luís</dc:contributor>
    <dc:contributor>Hughes, Barry D.</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Bagnerini, Patrizia</dc:creator>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Ja
Diese Publikation teilen