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Computer simulations were run only up to clinical diagnosis, calibrated with whole-exome sequencing plus clinical data from 1000+ non-small-cell patients, to determine when intrinsic resistance emerges and how fast early tumors progress.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/mathematical-model-of-intrinsic-drug-resistance-in-lung-cancer/383063/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/mathematical-model-of-intrinsic-drug-resistance-in-lung-cancer/383063.png","ImageObject",300,407,{"name":42,"@type":43},"Ben ","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-27","2026-09-24",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",5,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What problem does the model address in lung cancer treatment?","Question",{"text":63,"@type":64},"It addresses how intrinsic drug resistance emerges after targeted therapies, including how resistant cells can be present at diagnosis and whether they are detectable.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How is the mathematical model calibrated?",{"text":68,"@type":64},"Calibration uses whole-exome sequencing data combined with clinical information from over 1000 non-small-cell lung cancer patients.",{"name":70,"@type":61,"acceptedAnswer":71},"Until when are simulations performed, and what questions are tested?",{"text":72,"@type":64},"Simulations are run only until clinical diagnosis. The study asks when intrinsic drug resistance emerges and how long it takes for early-stage tumors to reach advanced stages.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},383063,1790728758,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,100,105,109,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":107,"slug":108},7,40,"healthcare",{"id":110,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},8,"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":55,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":106,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145},2336478951081,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Article  \nMathematical Model of Intrinsic Drug Resistance in Lung Cancer  \nEmilia Kozłowska  and Andrzej Swierniak *  \nCitation: Kozłowsk, E.; Swierniak, A. Mathematical Model of Intrinsic Drug Resistance in Lung Cancer. Int.  \nJ. Mol. Sci. 2023, 24, 15801 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)ijms242115801  \nAcademic Editors: Robert Arthur Kratzke and David Mu  \nReceived: 5 September 2023  \nRevised: 25 September 2023  \nAccepted: 28 October 2023  \nPublished: 31 October 2023  \nCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \nDepartment of Systems Biology and Engineering, Silesian University of Technology, 44100 Gliwie, Poland; [emilia.kozlowska@polsl.pl](emilia.kozlowska@polsl.pl)  \n* Correspondence: [andrzej.swierniak@polsl.pl](andrzej.swierniak@polsl.pl)  \nAbstract: Drug resistance is a bottleneck in cancer treatment. Commonly, a molecular treatment for cancer leads to the emergence of drug resistance in the long term. Thus, some drugs, despite their initial excellent response, are withdrawn from the market. Lung cancer is one of the most mutated cancers, leading to dozens of targeted therapeutics available against it. Here, we have developed a mechanistic mathematical model describing sensitization to nine groups of targeted therapeuticsand the emergence of intrinsic drug resistance. As we focus only on intrinsic drug resistance, we perform the computer simulations of the model only until clinical diagnosis. We have utilized, for model calibration, the whole-exome sequencing data combined with clinical information from over 1000 non-small-cell lung cancer patients. Next, the model has been applied to find an answer to the following questions: When does intrinsic drug resistance emerge? And how long does it take for early-stage lung cancer to grow to an advanced stage? The results show that drug resistance is inevitable at diagnosis but not always detectable and that the time interval between early and advanced-stage tumors depends on the selection advantage of cancer cells.  \nKeywords: lung cancer; mathematical modeling; branching process model; targeted treatment  \n1. Introduction  \nIn the paper, we have developed a multiple-type branching process mathematical model to investigate the emergence of intrinsic drug resistance to the most frequently applied targeted therapeutic drugs in non-small-cell lung cancer. Our focus is on drug resistance in treatment-naive patients. Thus, we performed the simulation only until diagnosis. The model considers nine genes that, if mutated, could sensitize lung cancer patients to aspecific group of targeted therapeutics drugs. We have aimed at the quantification of cells that are drug-resistant at diagnosis. The developed model is the most extensive model of targeted treatment in lung cancer as it gathers information about drug sensitivity and drug resistance to nine types of inhibitors. Also, previously researchers have focused only on the process of the emergence of drug resistance and assumed that mutation leading to drug sensitivity is already present in cancer initiating cell.  \nThe developed model that is discrete time has limitations. For example, the model assumes that all cancer cells are synchronized. In addition, the model does not consider interactions between cancer cells. Despite those limitations, the model is accurately calibrated to whole-exome sequencing data. All model limitations are discussed in details in the Discussion section.  \nLung cancer is the one with a high mutational burden. Indeed, the number of somatic mutations per megabit in lung cancer is about ten [1,2] . It gives the potential for finding actionable mutations","cbCaiiG4amXCD1gd","https://ap.wps.com/l/cbCaiiG4amXCD1gd","pdf",486337,13,"English","# Introduction\n## Problem background and motivation\n## Model construction and assumptions\n## Therapeutic context in NSCLC\n## Drug resistance types and relevance","[{\"question\":\"What problem does the model address in lung cancer treatment?\",\"answer\":\"It addresses how intrinsic drug resistance emerges after targeted therapies, including how resistant cells can be present at diagnosis and whether they are detectable.\"},{\"question\":\"How is the mathematical model calibrated?\",\"answer\":\"Calibration uses whole-exome sequencing data combined with clinical information from over 1000 non-small-cell lung cancer patients.\"},{\"question\":\"Until when are simulations performed, and what questions are tested?\",\"answer\":\"Simulations are run only until clinical diagnosis. The study asks when intrinsic drug resistance emerges and how long it takes for early-stage tumors to reach advanced stages.\"}]","Mathematical Model of Intrinsic Drug Resistance in Lung Cancer | PDF",1790253942,33]