{"database":"BioModels","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Txt":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=curation_notes.txt"],"Owl":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2-biopax2.owl","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2-biopax3.owl"],"Xml":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2.xml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=manifest.xml"],"Other":["https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2.ode","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=curation_image.png","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2.sedml","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=metadata.rdf","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2-matlab.m","https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000767?filename=Macnamara2015_2.cps"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"submitter":["Jinghao Men"],"curationStatus":["Manually curated"],"modellingApproach":["ordinary differential equation model"],"levelVersion":["L3V1"],"submitter_keywords":["Immuno-oncology"],"full_dataset_link":["https://www.ebi.ac.uk/biomodels/BIOMD0000000767"],"publication_pubmed":["25882747"],"isPrivate":["false"],"repository":["BioModels"],"non_derived_xrefs":["BIOMD0000000766 biomodels.db MODEL1907290002 biomodels.db"],"modelFormat":["SBML"],"omics_type":["Models"],"tokenised_name":["Macnamara2015/2   virotherapy virus free submodel"],"publication_year":["2015"],"submissionId":["MODEL1907290003"],"first_author":["Cicely Macnamara"],"publication_authors":["Cicely Macnamara, R Eftimie"],"publication":["25882747,\n                            The main priority when designing cancer immuno-therapies has been to seek viable biological mechanisms that lead to permanent cancer eradication or cancer control. Understanding the delicate balance between the role of effector and memory cells on eliminating cancer cells remains an elusive problem in immunology. Here we make an initial investigation into this problem with the help of a mathematical model for oncolytic virotherapy; although the model can in fact be made general enough to be applied also to other immunological problems. According to this model, we find that long-term cancer control is associated with a large number of persistent effector cells (irrespective of the initial peak in effector cell numbers). However, this large number of persistent effector cells is sustained by a relatively large number of memory cells. Moreover, the results of the mathematical model suggest that cancer control from a dormant state cannot be predicted by the size of the memory population.. null, 377.\n                            Division of Mathematics, University of Dundee, Dundee DD1 4HN, United Kingdom. Electronic address: c.k.macnamara@dundee.ac.uk."],"submitter_mail":["jm2187@cam.ac.uk"],"submitter_affiliation":["University of Cambridge"],"publicationId":["BIOMD0000000767"],"pubmed_abstract":["The main priority when designing cancer immuno-therapies has been to seek viable biological mechanisms that lead to permanent cancer eradication or cancer control. Understanding the delicate balance between the role of effector and memory cells on eliminating cancer cells remains an elusive problem in immunology. Here we make an initial investigation into this problem with the help of a mathematical model for oncolytic virotherapy; although the model can in fact be made general enough to be applied also to other immunological problems. According to this model, we find that long-term cancer control is associated with a large number of persistent effector cells (irrespective of the initial peak in effector cell numbers). However, this large number of persistent effector cells is sustained by a relatively large number of memory cells. Moreover, the results of the mathematical model suggest that cancer control from a dormant state cannot be predicted by the size of the memory population."],"pubmed_title":["Memory versus effector immune responses in oncolytic virotherapies."],"pubmed_authors":["Macnamara Cicely C, Eftimie Raluca R"],"additional_accession":[]},"is_claimable":false,"name":"Macnamara2015/2 - virotherapy virus-free submodel","description":"The paper describes a  submodel of oncolytic virotherapy. \nCreated by COPASI 4.25 (Build 207) \n\nThis model is described in the article: \nMemory versus effector immune responses in oncolytic virotherapies\nCicely Macnamara, Raluca Eftimie \n\nAbstract: \nThe main priority when designing cancer immuno-therapies has been to seek viable biological mechanisms that lead to permanent cancer eradica- tion or cancer control. Understanding the delicate balance between the role of effector and memory cells on eliminating cancer cells remains an elusive problem in immunology. Here we make an initial investigation into this problem with the help of a mathematical model for oncolytic virotherapy; although the model can in fact be made general enough to be applied also to other immunological problems. Our results show that long-term cancer con- trol is associated with a large number of persistent effector cells (irrespective of the initial peak in effector cell numbers). However, this large number of persistent effector cells is sustained by a relatively large number of memory cells. Moreover, we show that cancer control from a dormant state cannot be predicted by the size of the memory population.\n\nTo cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . \nTo the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. \nPlease refer to CC0 Public Domain Dedication for more information.","dates":{"last_modification":"2024-08-22","publication":"2024-09-02","submission":"2019-07-29"},"accession":"BIOMD0000000767","cross_references":{"sbo":["SBO:0000610","SBO:0000179","SBO:0000661","SBO:0000393","SBO:0000281"],"pubmed":["25882747"],"ncit":["C94498","C25636","C62713","C122731","C28241"],"biomodels__db":["MODEL1907290002","BIOMD0000000766","BIOMD0000000767","MODEL1907290003"],"go":["GO:0008219","GO:0008283","GO:0002419"],"cl":["CL:0001064"],"taxonomy":["9606"]}}