[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-353755-105":59,"doc-detail-353755-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","can-evolutionary-therapy-be-applied-in-non-small-cell-lung-cancer","Can evolutionary therapy be applied in non-small cell lung cancer?","","Evolutionary therapy (ET) uses evolutionary biology and data-driven mathematical models to steer tumour dynamics and delay treatment resistance. This study evaluates whether ET protocols—specifically Zhang et al.’s method for metastatic castrate-resistant prostate cancer—could be theoretically effective for fast-growing stage IV non-small-cell lung cancer (NSCLC). Using longitudinal tumour-burden data from erlotinib-treated patients, 26 two-population differential-equation models are compared, identifying a minimal structure capturing resistance-driven regrowth, with best fit from a Gompertzian log-kill model including density- and frequency-dependent interactions. The protocol prolongs median time-to-progression to 42.3 months versus 24.8 months under maximum tolerated dose, supporting ET feasibility and future translation.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/can-evolutionary-therapy-be-applied-in-non-small-cell-lung-cancer/353755/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/can-evolutionary-therapy-be-applied-in-non-small-cell-lung-cancer/353755.png","ImageObject",300,407,{"name":92,"@type":93},"Miles","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does evolutionary therapy aim to solve in metastatic cancer?","Question",{"text":112,"@type":113},"It targets the emergence of treatment resistance by steering tumour dynamics, typically using evolutionary principles and mathematical models to delay resistant regrowth.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the study evaluated for NSCLC?",{"text":117,"@type":113},"The authors used longitudinal tumour-burden data from NSCLC patients treated with erlotinib and systematically assessed 26 two-population differential-equation models with different interaction and pharmacokinetic/death assumptions.",{"name":119,"@type":110,"acceptedAnswer":120},"What modelling result supports ET as feasible for NSCLC?",{"text":121,"@type":113},"The analysis identifies the minimal model structure that reproduces resistance-driven regrowth, with the best fit from a Gompertzian model featuring log-kill dynamics and both density- and frequency-dependent interactions.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},353755,1790198432,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},13056703019404,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nCan evolutionary therapy be applied in non-small cell lung cancer?  \nLaura R. Jansén-Storbacka1,6􀀍, Kailas S. Honasoge1,6, Eva Molnárová1, Arina Soboleva1, Bram C. Agema3, Marthe S. Paats2, Dirk JanA. R. Moes4, G. D. Marijn Veerman2, Alethea B. T. Barbaro5, Roel Dobbe1, Irene Grossmann1, SepinoudAzimi1,  \nRon H. J. Mathijssen3, Anne-Marie C. Dingemans2,7 & Kateřina Staňková1,7  \nEvolutionary therapy (ET) applies principles of evolutionary biology to steer tumour dynamics and forestall or delay treatment resistance, typically guided by data-driven mathematical models. Our aim is to assess whether ET protocols, and specifically Zhang et al.’s protocol proposed for metastatic castrate-resistant prostate cancer, can be theoretically effective for fast-growing metastatic cancers such as stage IV non-small-cell lung cancer (NSCLC). Using longitudinal tumour-burden data from NSCLC patients treated with erlotinib, we systematically evaluate 26 two-population differentialequation models based on classical tumour-growth dynamics, with varying assumptions about densityand frequency-dependent interactions, pharmacokinetics, and treatment-induced death. Previous work by Yin et al. on the same dataset employed an exponential model that omitted density-and frequency-dependent interactions; although it provided a good fit to tumour-burden data, its structure would theoretically lead to poorer outcomes under ET protocols. In contrast, our analysis identifies the minimal model structure required to reproduce the resistance-driven regrowth observed in NSCLC, with the Gompertzian model featuring log-kill dynamics and both density-and frequency-dependent interactions providing the best fit. In this model, Zhang et al.’s protocol prolonged median time-toprogression to 42.3 months compared with 24.8 months under maximum tolerated dose. These results indicate that ET is theoretically a viable treatment strategy for NSCLC. This study offers a practical framework for assessing ET feasibility using clinical data and supports future clinical translation of ETin NSCLC.  \nKeywords Mathematical oncology, metastatic cancer, PK/PD, evolutionary therapy, Zhang et al.’s protocol, non-small cell lung cancer, treatment-induced resistance  \nResistance to therapy remains one of the most formidable challenges in the treatment of metastatic cancer. While many tumours initially respond to therapy, sustained responses are rare due to the evolution of drugresistant cell populations. This is particularly problematic in metastatic disease, where tumour heterogeneity and evolutionary pressures are prevalent1. Traditional treatment protocols that rely on maximum tolerated dose (MTD) often accelerate resistance and compromising long-term outcomes2–9. Moreover, MTD-based regimens frequently reduce patient quality of life due to high drug toxicity.  \nIn metastatic non-small cell lung cancer (NSCLC), the leading cause of cancer-related death worldwide2, the introduction of tyrosine kinase inhibitors (TKIs) has markedly improved survival in patients with actionable driver mutations10. Erlotinib, a first-generation EGFR-TKI, is commonly used in this context, but resistance to therapy eventually develops in nearly all patients11, 12. This challenge has motivated the exploration of alternative dosing strategies that can delay resistance evolution while reducing toxicity. Intermittent and metronomic regimens have shown promise in some cancers, such as prostate and melanoma13–15, and improved quality of  \n1Institute for Health Systems Science, Delft University ofTechnology, Faculty ofTechnology, Policy and Management, Delft, The Netherlands. 2Department of Respiratory Medicine, Erasmus Medical Center Cancer Institute, Rotterdam, The Netherlands. 3Department of Medical Oncology, Erasmus Medical Center Cancer Institute, Rotterdam, The Netherlands. 4Department of Clinical Pharmacy and Toxicology, Leiden Univ","cbCaivHzAO8gd28N","https://ap.wps.com/l/cbCaivHzAO8gd28N","pdf",4460649,28,"English","# Evolutionary therapy framework\n## Motivation: resistance and limits of MTD\n## NSCLC context and EGFR-TKI resistance\n## Alternative dosing strategies\n## Evolutionary therapy concept and prior prostate cancer trial\n## Role of mathematical modelling in exploring ET","[{\"question\":\"What problem does evolutionary therapy aim to solve in metastatic cancer?\",\"answer\":\"It targets the emergence of treatment resistance by steering tumour dynamics, typically using evolutionary principles and mathematical models to delay resistant regrowth.\"},{\"question\":\"How was the study evaluated for NSCLC?\",\"answer\":\"The authors used longitudinal tumour-burden data from NSCLC patients treated with erlotinib and systematically assessed 26 two-population differential-equation models with different interaction and pharmacokinetic/death assumptions.\"},{\"question\":\"What modelling result supports ET as feasible for NSCLC?\",\"answer\":\"The analysis identifies the minimal model structure that reproduces resistance-driven regrowth, with the best fit from a Gompertzian model featuring log-kill dynamics and both density- and frequency-dependent interactions.\"}]","Can evolutionary therapy be applied in non-small cell lung cancer? | PDF",1790107068,71]