Modeling and Simulation of Genotypic TMB and Phenotypic immunogenicity Biomarkers in Cancer Immunoediting with Ising-Hamiltonian Characterization

Modeling and Simulation of Genotypic TMB and Phenotypic immunogenicity Biomarkers in Cancer Immunoediting with Ising-Hamiltonian Characterization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Modeling and Simulation of Genotypic TMB and Phenotypic immunogenicity Biomarkers in Cancer Immunoediting with Ising-Hamiltonian Characterization Alfonso Rojas-Domínguez, Irving Ulises Martínez-Vargas, Matías Alvarado This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4751986/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Objective: In the Tumor Micro-Environment, cancerprogression and its relationship with the Immune System (IS) is described interms of cancer immunoediting (CI) phases, each of which is characterized bydifferent types and levels of interaction between the tumor cells and elements ofthe IS, such as CD8+T cells. Said interactions are governed by genotypical (TumorMutational Burden, TMB) and phenotypical aspects pertaining to the tumor, aswell as by the strength of the IS. In this work, a computational model of CI ispresented which incorporates the TMB and the biomarker Tumor Immunogenic Phenotype (TIP) as its control parameters, and which employs the Ising-modelHamiltonian to characterize the system with respect to the CI phases. Methods: Our model is a probabilistic multi-agent system with agents for tumorcells and for the IS. A basic version of this model was presented before; for thiswork we have produced a new implementation of our system, improved throughthe inclusion of the TMB and the TIP (i.e. whether a tumor is hot or cold). Thenew elements are integrated under a Michaelis-Menten relationship that isemployed to regulate the recruitment rate of CD8+T cells (and other IS elements),thus controlling the interactions between tumor cells and the IS. Results: Our simulations confirm that the proposed system is capable ofconsistently generating different phases of CI, and that by varying the introducedparameters, the system is effectively controlled. However, beyond the expectedbehaviors, we also found unanticipated effects that nevertheless match well withthe literature regarding the combination of the genotypical and phenotypicalbiomarkers discussed. Moreover, the Ising-model Hamiltonian is confirmed as avaluable tool for the broad characterization of tumor-IS interaction, by reflectingclear and distinct patterns related to the phases of CI. Conclusions: The presented model, although formed by relatively simple agents,generate emergent behaviors with which the phases of CI can be identified. Themodel is robust to the choice of its control parameters and, more importantly,provides a plausible explanation for the mechanics through which tumors withhigh TMB and high immunogenicity (i.e. hot tumors) exhibit a higher probabilityof responding to treatment by immunotherapy. Characterization via theIsing-model Hamiltonian also contributes to said explanation, by summarizing thesystem’s dynamics in a way that facilitates its analysis and future improvements. Multi-agent system simulation Mathematical modeling TumorMutational Burden Cancer Immune Response Hot- and Cold-Tumors. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4751986","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":333678140,"identity":"a1ca3e13-20ea-4ae8-b5e8-468393e0cfdb","order_by":0,"name":"Alfonso Rojas-Domínguez","email":"","orcid":"","institution":"Instituto Tecnológico de León","correspondingAuthor":false,"prefix":"","firstName":"Alfonso","middleName":"","lastName":"Rojas-Domínguez","suffix":""},{"id":333678141,"identity":"24803948-2676-4abf-94a1-fe018cb7e472","order_by":1,"name":"Irving Ulises Martínez-Vargas","email":"","orcid":"","institution":"Center for Research and Advanced Studies of the National Polytechnic Institute","correspondingAuthor":false,"prefix":"","firstName":"Irving","middleName":"Ulises","lastName":"Martínez-Vargas","suffix":""},{"id":333678142,"identity":"a3e5feea-0493-4652-8cf3-e8cfc3e7afa4","order_by":2,"name":"Matías Alvarado","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3Qv4rCMBzA8Z8X0CWH6y2SJxDicpPYV0kJdKqDW8eKEJceN/sWPsKvZC3XteIkAScXcXEoaBSktxg7OuQz/QL5kj8AnvemEGD8GFoht51Rk9A2iaWb9ctkuCxzPNclYynZ6ZkaB0Gv4B8b9Tz5LiTkP2o7WmOX65WKwozGnMSFI0EJ+JluBbc30rTQgkIkSJw4ktJAXtd/gqX35BLQ/t4m3JFU0u7sogC8JQl2si+J7lMqw/VAydFa27fQRIZZZVA731KG5nioJ4wtF+ZE+STo/YZzM3X8WIP8m7FN4Hme5z13BZ3MUrDEDXWnAAAAAElFTkSuQmCC","orcid":"","institution":"Center for Research and Advanced Studies of the National Polytechnic Institute","correspondingAuthor":true,"prefix":"","firstName":"Matías","middleName":"","lastName":"Alvarado","suffix":""}],"badges":[],"createdAt":"2024-07-16 19:06:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4751986/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4751986/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61545884,"identity":"09683366-79cf-4b20-b3fa-06d662df907e","added_by":"auto","created_at":"2024-08-01 04:50:34","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1125401,"visible":true,"origin":"","legend":"","description":"","filename":"ModelSimul.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4751986/v1_covered_cea1400a-c422-4f41-9ac2-c5ca6a37a2d1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Modeling and Simulation of Genotypic TMB and Phenotypic immunogenicity Biomarkers in Cancer Immunoediting with Ising-Hamiltonian Characterization","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multi-agent system simulation, Mathematical modeling, TumorMutational Burden, Cancer Immune Response, Hot- and Cold-Tumors.","lastPublishedDoi":"10.21203/rs.3.rs-4751986/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4751986/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Objective:\u003c/strong\u003e In the Tumor Micro-Environment, cancerprogression and its relationship with the Immune System (IS) is described interms of cancer immunoediting (CI) phases, each of which is characterized bydifferent types and levels of interaction between the tumor cells and elements ofthe IS, such as CD8+T cells. Said interactions are governed by genotypical (TumorMutational Burden, TMB) and phenotypical aspects pertaining to the tumor, aswell as by the strength of the IS. In this work, a computational model of CI ispresented which incorporates the TMB and the biomarker Tumor Immunogenic Phenotype (TIP) as its control parameters, and which employs the Ising-modelHamiltonian to characterize the system with respect to the CI phases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Our model is a probabilistic multi-agent system with agents for tumorcells and for the IS. A basic version of this model was presented before; for thiswork we have produced a new implementation of our system, improved throughthe inclusion of the TMB and the TIP (i.e. whether a tumor is hot or cold). Thenew elements are integrated under a Michaelis-Menten relationship that isemployed to regulate the recruitment rate of CD8+T cells (and other IS elements),thus controlling the interactions between tumor cells and the IS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Our simulations confirm that the proposed system is capable ofconsistently generating different phases of CI, and that by varying the introducedparameters, the system is effectively controlled. However, beyond the expectedbehaviors, we also found unanticipated effects that nevertheless match well withthe literature regarding the combination of the genotypical and phenotypicalbiomarkers discussed. Moreover, the Ising-model Hamiltonian is confirmed as avaluable tool for the broad characterization of tumor-IS interaction, by reflectingclear and distinct patterns related to the phases of CI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e The presented model, although formed by relatively simple agents,generate emergent behaviors with which the phases of CI can be identified. Themodel is robust to the choice of its control parameters and, more importantly,provides a plausible explanation for the mechanics through which tumors withhigh TMB and high immunogenicity (i.e. hot tumors) exhibit a higher probabilityof responding to treatment by immunotherapy. Characterization via theIsing-model Hamiltonian also contributes to said explanation, by summarizing thesystem’s dynamics in a way that facilitates its analysis and future improvements.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Modeling and Simulation of Genotypic TMB and Phenotypic immunogenicity Biomarkers in Cancer Immunoediting with Ising-Hamiltonian Characterization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-01 04:42:27","doi":"10.21203/rs.3.rs-4751986/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f46843bc-ac9a-4ba6-8e5b-e2ec03329fc8","owner":[],"postedDate":"August 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-01T04:42:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-01 04:42:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4751986","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4751986","identity":"rs-4751986","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}