Loading…
Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model
In this paper we consider a combination therapy of cancer. One drug is a vaccine which activates dendritic cells so that they induce more T cells to infiltrate the tumor. The other drug is a checkpoint inhibitor, which enables the T cells to remain active against the cancer cells. The two drugs are...
Saved in:
Published in: | PloS one 2017-05, Vol.12 (5), p.e0178479-e0178479 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3 |
---|---|
cites | cdi_FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3 |
container_end_page | e0178479 |
container_issue | 5 |
container_start_page | e0178479 |
container_title | PloS one |
container_volume | 12 |
creator | Lai, Xiulan Friedman, Avner |
description | In this paper we consider a combination therapy of cancer. One drug is a vaccine which activates dendritic cells so that they induce more T cells to infiltrate the tumor. The other drug is a checkpoint inhibitor, which enables the T cells to remain active against the cancer cells. The two drugs are positively correlated in the sense that an increase in the amount of each drug results in a reduction in the tumor volume. We consider the question whether a treatment with combination of the two drugs at certain levels is preferable to a treatment by one of the drugs alone at 'roughly' twice the dosage level; if that is the case, then we say that there is a positive 'synergy' for this combination of dosages. To address this question, we develop a mathematical model using a system of partial differential equations. The variables include dendritic and cancer cells, CD4+ and CD8+ T cells, IL-12 and IL-2, GM-CSF produced by the vaccine, and a T cell checkpoint inhibitor associated with PD-1. We use the model to explore the efficacy of the two drugs, separately and in combination, and compare the simulations with data from mouse experiments. We next introduce the concept of synergy between the drugs and develop a synergy map which suggests in what proportion to administer the drugs in order to achieve the maximum reduction of tumor volume under the constraint of maximum tolerated dose. |
doi_str_mv | 10.1371/journal.pone.0178479 |
format | article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1902478597</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A492822015</galeid><doaj_id>oai_doaj_org_article_7a0c85c0fd374943ad9053ea1a6b4ea5</doaj_id><sourcerecordid>A492822015</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3</originalsourceid><addsrcrecordid>eNqNk11r2zAUhs1YWbtu_2BshsFYL5Lpy5a9i0EI-wgUCvu6FceSHCuzpVSyu_XfT2mcEo9eDIN8kJ7z6uiVTpK8wGiOKcfvNm7wFtr51lk9R5gXjJePkjNcUjLLCaKPj-LT5GkIG4QyWuT5k-SUFBkjGWdnSbN0XWUs9MbZtG-0h-1t6upUgpXap79N3xziG5DSWJ2CVanpuiGGstHy19YZ26fGNqYyvfPhfbpIO4hacTAS2rRzSrfPkpMa2qCfj__z5Menj9-XX2aXV59Xy8XlTOYl6WeVJBnGRUbzUpZFQQjNpaQVpqWqOK9xnUvNCKeMUCIRQ5hkUmFCJAeV1UrR8-TVXnfbuiBGk4LAJSKMF1nJI7HaE8rBRmy96cDfCgdG3E04vxbgY-WtFhyQLDKJakU5KxkFVUYPNWDIK6Yhi1ofxt2GqtNKatt7aCei0xVrGrF2NyJjjBUsjwJvRwHvrgcdetGZIHXbgtVuuKub4hxhyiL6-h_04dON1BriAYytXdxX7kTFgpUkOorwru75A1T8lO6MjC-qNnF-knAxSYhMr__0axhCEKtvX_-fvfo5Zd8csY2Gtm-Ca4fdewxTkO1B6V0IXtf3JmMkdg1xcEPsGkKMDRHTXh5f0H3SoQPoX4wGBY8</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1902478597</pqid></control><display><type>article</type><title>Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model</title><source>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</source><source>PubMed Central</source><creator>Lai, Xiulan ; Friedman, Avner</creator><contributor>Haass, Nikolas K.</contributor><creatorcontrib>Lai, Xiulan ; Friedman, Avner ; Haass, Nikolas K.</creatorcontrib><description>In this paper we consider a combination therapy of cancer. One drug is a vaccine which activates dendritic cells so that they induce more T cells to infiltrate the tumor. The other drug is a checkpoint inhibitor, which enables the T cells to remain active against the cancer cells. The two drugs are positively correlated in the sense that an increase in the amount of each drug results in a reduction in the tumor volume. We consider the question whether a treatment with combination of the two drugs at certain levels is preferable to a treatment by one of the drugs alone at 'roughly' twice the dosage level; if that is the case, then we say that there is a positive 'synergy' for this combination of dosages. To address this question, we develop a mathematical model using a system of partial differential equations. The variables include dendritic and cancer cells, CD4+ and CD8+ T cells, IL-12 and IL-2, GM-CSF produced by the vaccine, and a T cell checkpoint inhibitor associated with PD-1. We use the model to explore the efficacy of the two drugs, separately and in combination, and compare the simulations with data from mouse experiments. We next introduce the concept of synergy between the drugs and develop a synergy map which suggests in what proportion to administer the drugs in order to achieve the maximum reduction of tumor volume under the constraint of maximum tolerated dose.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0178479</identifier><identifier>PMID: 28542574</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Animals ; Antigens ; Antineoplastic agents ; Biology and Life Sciences ; Breast cancer ; Cancer ; Cancer therapies ; Cancer treatment ; Cancer vaccines ; Cancer Vaccines - immunology ; Cancer Vaccines - pharmacology ; CD4 antigen ; CD4-Positive T-Lymphocytes - drug effects ; CD4-Positive T-Lymphocytes - immunology ; CD8 antigen ; CD8-Positive T-Lymphocytes - drug effects ; CD8-Positive T-Lymphocytes - immunology ; Cell death ; Cell division ; Cell Line, Tumor ; Chemotherapy ; Clinical trials ; Combination drug therapy ; Combination therapy ; Combined Modality Therapy - methods ; Dendritic cells ; Dendritic Cells - drug effects ; Dendritic Cells - immunology ; Differential equations ; Dosage ; Dosage and administration ; Drugs ; Gene expression ; Granulocyte-macrophage colony-stimulating factor ; Granulocyte-Macrophage Colony-Stimulating Factor - immunology ; Humans ; Immune checkpoint ; Immunosuppressive agents ; Immunotherapy ; Inhibitors ; Interleukin 12 ; Interleukin 2 ; Interleukin-12 - immunology ; Interleukin-2 - immunology ; Lung cancer ; Lymphocytes ; Lymphocytes T ; Mathematical models ; Medicine and Health Sciences ; Mice ; Models, Theoretical ; Neoplasms - drug therapy ; Neoplasms - immunology ; Ordinary differential equations ; Partial differential equations ; PD-1 protein ; Physical Sciences ; Rodents ; Treatment outcome ; Tumor Burden - drug effects ; Tumor Burden - immunology ; Tumors ; Vaccines</subject><ispartof>PloS one, 2017-05, Vol.12 (5), p.e0178479-e0178479</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Lai, Friedman. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2017 Lai, Friedman 2017 Lai, Friedman</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3</citedby><cites>FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3</cites><orcidid>0000-0002-2764-8937</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1902478597/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1902478597?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28542574$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Haass, Nikolas K.</contributor><creatorcontrib>Lai, Xiulan</creatorcontrib><creatorcontrib>Friedman, Avner</creatorcontrib><title>Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>In this paper we consider a combination therapy of cancer. One drug is a vaccine which activates dendritic cells so that they induce more T cells to infiltrate the tumor. The other drug is a checkpoint inhibitor, which enables the T cells to remain active against the cancer cells. The two drugs are positively correlated in the sense that an increase in the amount of each drug results in a reduction in the tumor volume. We consider the question whether a treatment with combination of the two drugs at certain levels is preferable to a treatment by one of the drugs alone at 'roughly' twice the dosage level; if that is the case, then we say that there is a positive 'synergy' for this combination of dosages. To address this question, we develop a mathematical model using a system of partial differential equations. The variables include dendritic and cancer cells, CD4+ and CD8+ T cells, IL-12 and IL-2, GM-CSF produced by the vaccine, and a T cell checkpoint inhibitor associated with PD-1. We use the model to explore the efficacy of the two drugs, separately and in combination, and compare the simulations with data from mouse experiments. We next introduce the concept of synergy between the drugs and develop a synergy map which suggests in what proportion to administer the drugs in order to achieve the maximum reduction of tumor volume under the constraint of maximum tolerated dose.</description><subject>Analysis</subject><subject>Animals</subject><subject>Antigens</subject><subject>Antineoplastic agents</subject><subject>Biology and Life Sciences</subject><subject>Breast cancer</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Cancer treatment</subject><subject>Cancer vaccines</subject><subject>Cancer Vaccines - immunology</subject><subject>Cancer Vaccines - pharmacology</subject><subject>CD4 antigen</subject><subject>CD4-Positive T-Lymphocytes - drug effects</subject><subject>CD4-Positive T-Lymphocytes - immunology</subject><subject>CD8 antigen</subject><subject>CD8-Positive T-Lymphocytes - drug effects</subject><subject>CD8-Positive T-Lymphocytes - immunology</subject><subject>Cell death</subject><subject>Cell division</subject><subject>Cell Line, Tumor</subject><subject>Chemotherapy</subject><subject>Clinical trials</subject><subject>Combination drug therapy</subject><subject>Combination therapy</subject><subject>Combined Modality Therapy - methods</subject><subject>Dendritic cells</subject><subject>Dendritic Cells - drug effects</subject><subject>Dendritic Cells - immunology</subject><subject>Differential equations</subject><subject>Dosage</subject><subject>Dosage and administration</subject><subject>Drugs</subject><subject>Gene expression</subject><subject>Granulocyte-macrophage colony-stimulating factor</subject><subject>Granulocyte-Macrophage Colony-Stimulating Factor - immunology</subject><subject>Humans</subject><subject>Immune checkpoint</subject><subject>Immunosuppressive agents</subject><subject>Immunotherapy</subject><subject>Inhibitors</subject><subject>Interleukin 12</subject><subject>Interleukin 2</subject><subject>Interleukin-12 - immunology</subject><subject>Interleukin-2 - immunology</subject><subject>Lung cancer</subject><subject>Lymphocytes</subject><subject>Lymphocytes T</subject><subject>Mathematical models</subject><subject>Medicine and Health Sciences</subject><subject>Mice</subject><subject>Models, Theoretical</subject><subject>Neoplasms - drug therapy</subject><subject>Neoplasms - immunology</subject><subject>Ordinary differential equations</subject><subject>Partial differential equations</subject><subject>PD-1 protein</subject><subject>Physical Sciences</subject><subject>Rodents</subject><subject>Treatment outcome</subject><subject>Tumor Burden - drug effects</subject><subject>Tumor Burden - immunology</subject><subject>Tumors</subject><subject>Vaccines</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11r2zAUhs1YWbtu_2BshsFYL5Lpy5a9i0EI-wgUCvu6FceSHCuzpVSyu_XfT2mcEo9eDIN8kJ7z6uiVTpK8wGiOKcfvNm7wFtr51lk9R5gXjJePkjNcUjLLCaKPj-LT5GkIG4QyWuT5k-SUFBkjGWdnSbN0XWUs9MbZtG-0h-1t6upUgpXap79N3xziG5DSWJ2CVanpuiGGstHy19YZ26fGNqYyvfPhfbpIO4hacTAS2rRzSrfPkpMa2qCfj__z5Menj9-XX2aXV59Xy8XlTOYl6WeVJBnGRUbzUpZFQQjNpaQVpqWqOK9xnUvNCKeMUCIRQ5hkUmFCJAeV1UrR8-TVXnfbuiBGk4LAJSKMF1nJI7HaE8rBRmy96cDfCgdG3E04vxbgY-WtFhyQLDKJakU5KxkFVUYPNWDIK6Yhi1ofxt2GqtNKatt7aCei0xVrGrF2NyJjjBUsjwJvRwHvrgcdetGZIHXbgtVuuKub4hxhyiL6-h_04dON1BriAYytXdxX7kTFgpUkOorwru75A1T8lO6MjC-qNnF-knAxSYhMr__0axhCEKtvX_-fvfo5Zd8csY2Gtm-Ca4fdewxTkO1B6V0IXtf3JmMkdg1xcEPsGkKMDRHTXh5f0H3SoQPoX4wGBY8</recordid><startdate>20170525</startdate><enddate>20170525</enddate><creator>Lai, Xiulan</creator><creator>Friedman, Avner</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2764-8937</orcidid></search><sort><creationdate>20170525</creationdate><title>Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model</title><author>Lai, Xiulan ; Friedman, Avner</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Analysis</topic><topic>Animals</topic><topic>Antigens</topic><topic>Antineoplastic agents</topic><topic>Biology and Life Sciences</topic><topic>Breast cancer</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Cancer treatment</topic><topic>Cancer vaccines</topic><topic>Cancer Vaccines - immunology</topic><topic>Cancer Vaccines - pharmacology</topic><topic>CD4 antigen</topic><topic>CD4-Positive T-Lymphocytes - drug effects</topic><topic>CD4-Positive T-Lymphocytes - immunology</topic><topic>CD8 antigen</topic><topic>CD8-Positive T-Lymphocytes - drug effects</topic><topic>CD8-Positive T-Lymphocytes - immunology</topic><topic>Cell death</topic><topic>Cell division</topic><topic>Cell Line, Tumor</topic><topic>Chemotherapy</topic><topic>Clinical trials</topic><topic>Combination drug therapy</topic><topic>Combination therapy</topic><topic>Combined Modality Therapy - methods</topic><topic>Dendritic cells</topic><topic>Dendritic Cells - drug effects</topic><topic>Dendritic Cells - immunology</topic><topic>Differential equations</topic><topic>Dosage</topic><topic>Dosage and administration</topic><topic>Drugs</topic><topic>Gene expression</topic><topic>Granulocyte-macrophage colony-stimulating factor</topic><topic>Granulocyte-Macrophage Colony-Stimulating Factor - immunology</topic><topic>Humans</topic><topic>Immune checkpoint</topic><topic>Immunosuppressive agents</topic><topic>Immunotherapy</topic><topic>Inhibitors</topic><topic>Interleukin 12</topic><topic>Interleukin 2</topic><topic>Interleukin-12 - immunology</topic><topic>Interleukin-2 - immunology</topic><topic>Lung cancer</topic><topic>Lymphocytes</topic><topic>Lymphocytes T</topic><topic>Mathematical models</topic><topic>Medicine and Health Sciences</topic><topic>Mice</topic><topic>Models, Theoretical</topic><topic>Neoplasms - drug therapy</topic><topic>Neoplasms - immunology</topic><topic>Ordinary differential equations</topic><topic>Partial differential equations</topic><topic>PD-1 protein</topic><topic>Physical Sciences</topic><topic>Rodents</topic><topic>Treatment outcome</topic><topic>Tumor Burden - drug effects</topic><topic>Tumor Burden - immunology</topic><topic>Tumors</topic><topic>Vaccines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lai, Xiulan</creatorcontrib><creatorcontrib>Friedman, Avner</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints (Gale)</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lai, Xiulan</au><au>Friedman, Avner</au><au>Haass, Nikolas K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2017-05-25</date><risdate>2017</risdate><volume>12</volume><issue>5</issue><spage>e0178479</spage><epage>e0178479</epage><pages>e0178479-e0178479</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In this paper we consider a combination therapy of cancer. One drug is a vaccine which activates dendritic cells so that they induce more T cells to infiltrate the tumor. The other drug is a checkpoint inhibitor, which enables the T cells to remain active against the cancer cells. The two drugs are positively correlated in the sense that an increase in the amount of each drug results in a reduction in the tumor volume. We consider the question whether a treatment with combination of the two drugs at certain levels is preferable to a treatment by one of the drugs alone at 'roughly' twice the dosage level; if that is the case, then we say that there is a positive 'synergy' for this combination of dosages. To address this question, we develop a mathematical model using a system of partial differential equations. The variables include dendritic and cancer cells, CD4+ and CD8+ T cells, IL-12 and IL-2, GM-CSF produced by the vaccine, and a T cell checkpoint inhibitor associated with PD-1. We use the model to explore the efficacy of the two drugs, separately and in combination, and compare the simulations with data from mouse experiments. We next introduce the concept of synergy between the drugs and develop a synergy map which suggests in what proportion to administer the drugs in order to achieve the maximum reduction of tumor volume under the constraint of maximum tolerated dose.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28542574</pmid><doi>10.1371/journal.pone.0178479</doi><tpages>e0178479</tpages><orcidid>https://orcid.org/0000-0002-2764-8937</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2017-05, Vol.12 (5), p.e0178479-e0178479 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_1902478597 |
source | Publicly Available Content Database (Proquest) (PQ_SDU_P3); PubMed Central |
subjects | Analysis Animals Antigens Antineoplastic agents Biology and Life Sciences Breast cancer Cancer Cancer therapies Cancer treatment Cancer vaccines Cancer Vaccines - immunology Cancer Vaccines - pharmacology CD4 antigen CD4-Positive T-Lymphocytes - drug effects CD4-Positive T-Lymphocytes - immunology CD8 antigen CD8-Positive T-Lymphocytes - drug effects CD8-Positive T-Lymphocytes - immunology Cell death Cell division Cell Line, Tumor Chemotherapy Clinical trials Combination drug therapy Combination therapy Combined Modality Therapy - methods Dendritic cells Dendritic Cells - drug effects Dendritic Cells - immunology Differential equations Dosage Dosage and administration Drugs Gene expression Granulocyte-macrophage colony-stimulating factor Granulocyte-Macrophage Colony-Stimulating Factor - immunology Humans Immune checkpoint Immunosuppressive agents Immunotherapy Inhibitors Interleukin 12 Interleukin 2 Interleukin-12 - immunology Interleukin-2 - immunology Lung cancer Lymphocytes Lymphocytes T Mathematical models Medicine and Health Sciences Mice Models, Theoretical Neoplasms - drug therapy Neoplasms - immunology Ordinary differential equations Partial differential equations PD-1 protein Physical Sciences Rodents Treatment outcome Tumor Burden - drug effects Tumor Burden - immunology Tumors Vaccines |
title | Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T08%3A20%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Combination%20therapy%20of%20cancer%20with%20cancer%20vaccine%20and%20immune%20checkpoint%20inhibitors:%20A%20mathematical%20model&rft.jtitle=PloS%20one&rft.au=Lai,%20Xiulan&rft.date=2017-05-25&rft.volume=12&rft.issue=5&rft.spage=e0178479&rft.epage=e0178479&rft.pages=e0178479-e0178479&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0178479&rft_dat=%3Cgale_plos_%3EA492822015%3C/gale_plos_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c692t-bc251185369c9882236cc3b139db77f1f6ce42734232c040125cd122c7ad5fdd3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1902478597&rft_id=info:pmid/28542574&rft_galeid=A492822015&rfr_iscdi=true |