Fine-tuning anti-tumor immunotherapies via stochastic simulations.
Identifieur interne : 000290 ( PubMed/Curation ); précédent : 000289; suivant : 000291Fine-tuning anti-tumor immunotherapies via stochastic simulations.
Auteurs : Giulio Caravagna [Italie] ; Roberto Barbuti ; Alberto D'OnofrioSource :
- BMC bioinformatics [ 1471-2105 ] ; 2012.
Descripteurs français
- KwdFr :
- MESH :
- immunologie : Tumeurs.
- usage thérapeutique : Interleukines.
- Humains, Immunothérapie, Immunothérapie adoptive, Processus stochastiques, Simulation numérique, Tumeurs.
English descriptors
- KwdEn :
- MESH :
- chemical , therapeutic use : Interleukins.
- immunology : Neoplasms.
- methods : Immunotherapy.
- therapy : Neoplasms.
- Computer Simulation, Humans, Immunotherapy, Adoptive, Stochastic Processes.
Abstract
Anti-tumor therapies aim at reducing to zero the number of tumor cells in a host within their end or, at least, aim at leaving the patient with a sufficiently small number of tumor cells so that the residual tumor can be eradicated by the immune system. Besides severe side-effects, a key problem of such therapies is finding a suitable scheduling of their administration to the patients. In this paper we study the effect of varying therapy-related parameters on the final outcome of the interplay between a tumor and the immune system.
DOI: 10.1186/1471-2105-13-S4-S8
PubMed: 22536975
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Fine-tuning anti-tumor immunotherapies via stochastic simulations.</title><author><name sortKey="Caravagna, Giulio" sort="Caravagna, Giulio" uniqKey="Caravagna G" first="Giulio" last="Caravagna">Giulio Caravagna</name><affiliation wicri:level="1"><nlm:affiliation>Institute for Informatics and Telematics, National Research Council, Pisa, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Institute for Informatics and Telematics, National Research Council, Pisa</wicri:regionArea></affiliation></author><author><name sortKey="Barbuti, Roberto" sort="Barbuti, Roberto" uniqKey="Barbuti R" first="Roberto" last="Barbuti">Roberto Barbuti</name></author><author><name sortKey="D Onofrio, Alberto" sort="D Onofrio, Alberto" uniqKey="D Onofrio A" first="Alberto" last="D'Onofrio">Alberto D'Onofrio</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2012">2012</date><idno type="doi">10.1186/1471-2105-13-S4-S8</idno><idno type="RBID">pubmed:22536975</idno><idno type="pmid">22536975</idno><idno type="wicri:Area/PubMed/Corpus">000290</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000290</idno><idno type="wicri:Area/PubMed/Curation">000290</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000290</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Fine-tuning anti-tumor immunotherapies via stochastic simulations.</title><author><name sortKey="Caravagna, Giulio" sort="Caravagna, Giulio" uniqKey="Caravagna G" first="Giulio" last="Caravagna">Giulio Caravagna</name><affiliation wicri:level="1"><nlm:affiliation>Institute for Informatics and Telematics, National Research Council, Pisa, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Institute for Informatics and Telematics, National Research Council, Pisa</wicri:regionArea></affiliation></author><author><name sortKey="Barbuti, Roberto" sort="Barbuti, Roberto" uniqKey="Barbuti R" first="Roberto" last="Barbuti">Roberto Barbuti</name></author><author><name sortKey="D Onofrio, Alberto" sort="D Onofrio, Alberto" uniqKey="D Onofrio A" first="Alberto" last="D'Onofrio">Alberto D'Onofrio</name></author></analytic><series><title level="j">BMC bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2012" type="published">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computer Simulation</term><term>Humans</term><term>Immunotherapy (methods)</term><term>Immunotherapy, Adoptive</term><term>Interleukins (therapeutic use)</term><term>Neoplasms (immunology)</term><term>Neoplasms (therapy)</term><term>Stochastic Processes</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Humains</term><term>Immunothérapie ()</term><term>Immunothérapie adoptive</term><term>Interleukines (usage thérapeutique)</term><term>Processus stochastiques</term><term>Simulation numérique</term><term>Tumeurs ()</term><term>Tumeurs (immunologie)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="therapeutic use" xml:lang="en"><term>Interleukins</term></keywords><keywords scheme="MESH" qualifier="immunologie" xml:lang="fr"><term>Tumeurs</term></keywords><keywords scheme="MESH" qualifier="immunology" xml:lang="en"><term>Neoplasms</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Immunotherapy</term></keywords><keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Neoplasms</term></keywords><keywords scheme="MESH" qualifier="usage thérapeutique" xml:lang="fr"><term>Interleukines</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Humans</term><term>Immunotherapy, Adoptive</term><term>Stochastic Processes</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Humains</term><term>Immunothérapie</term><term>Immunothérapie adoptive</term><term>Processus stochastiques</term><term>Simulation numérique</term><term>Tumeurs</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Anti-tumor therapies aim at reducing to zero the number of tumor cells in a host within their end or, at least, aim at leaving the patient with a sufficiently small number of tumor cells so that the residual tumor can be eradicated by the immune system. Besides severe side-effects, a key problem of such therapies is finding a suitable scheduling of their administration to the patients. In this paper we study the effect of varying therapy-related parameters on the final outcome of the interplay between a tumor and the immune system.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">22536975</PMID><DateCreated><Year>2012</Year><Month>04</Month><Day>27</Day></DateCreated><DateCompleted><Year>2012</Year><Month>11</Month><Day>06</Day></DateCompleted><DateRevised><Year>2015</Year><Month>02</Month><Day>25</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2105</ISSN><JournalIssue CitedMedium="Internet"><Volume>13 Suppl 4</Volume><PubDate><Year>2012</Year></PubDate></JournalIssue><Title>BMC bioinformatics</Title><ISOAbbreviation>BMC Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>Fine-tuning anti-tumor immunotherapies via stochastic simulations.</ArticleTitle><Pagination><MedlinePgn>S8</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/1471-2105-13-S4-S8</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Anti-tumor therapies aim at reducing to zero the number of tumor cells in a host within their end or, at least, aim at leaving the patient with a sufficiently small number of tumor cells so that the residual tumor can be eradicated by the immune system. Besides severe side-effects, a key problem of such therapies is finding a suitable scheduling of their administration to the patients. In this paper we study the effect of varying therapy-related parameters on the final outcome of the interplay between a tumor and the immune system.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">This work generalizes our previous study on hybrid models of such an interplay where interleukins are modeled as a continuous variable, and the tumor and the immune system as a discrete-state continuous-time stochastic process. The hybrid model we use is obtained by modifying the corresponding deterministic model, originally proposed by Kirschner and Panetta. We consider Adoptive Cellular Immunotherapies and Interleukin-based therapies, as well as their combination. By asymptotic and transitory analyses of the corresponding deterministic model we find conditions guaranteeing tumor eradication, and we tune the parameters of the hybrid model accordingly. We then perform stochastic simulations of the hybrid model under various therapeutic settings: constant, piece-wise constant or impulsive infusion and daily or weekly delivery schedules.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Results suggest that, in some cases, the delivery schedule may deeply impact on the therapy-induced tumor eradication time. Indeed, our model suggests that Interleukin-based therapies may not be effective for every patient, and that the piece-wise constant is the most effective delivery to stimulate the immune-response. For Adoptive Cellular Immunotherapies a metronomic delivery seems more effective, as it happens for other anti-angiogenesis therapies and chemotherapies, and the impulsive delivery seems more effective than the piece-wise constant. The expected synergistic effects have been observed when the therapies are combined.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Caravagna</LastName><ForeName>Giulio</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Institute for Informatics and Telematics, National Research Council, Pisa, Italy.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Barbuti</LastName><ForeName>Roberto</ForeName><Initials>R</Initials></Author><Author ValidYN="Y"><LastName>d'Onofrio</LastName><ForeName>Alberto</ForeName><Initials>A</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2012</Year><Month>03</Month><Day>28</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC 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