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Target antigen heterogeneity is treated as a key barrier associated with therapeutic resistance and treatment failure in solid tumours. Simulations indicate that higher CART-cell dosing can reduce tumour size and growth rate, but may not fully eliminate tumours at single dosing, while increasing free CART cells and side-effect risk. Dosimetry strategies such as enhancing long-term persistence or applying multiple dosing are assessed as “effective yet safe” options. Emergent shielding structures with low antigen expression protect high-antigen cells, and multi-antigen recognition can overcome antigen escape while increasing side-effect risk. Results support computational frameworks to model treatment combinations across scenarios.",{"@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":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/in-silico-study-of-heterogeneous-tumour-derived-organoid-response-to-car-t-cell-therapy/332108/",{"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/in-silico-study-of-heterogeneous-tumour-derived-organoid-response-to-car-t-cell-therapy/332108.png","ImageObject",300,407,{"name":92,"@type":93},"Ivy","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-04","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is target antigen heterogeneity important for CAR T-cell therapy outcomes?","Question",{"text":112,"@type":113},"Target antigen heterogeneity is linked to therapeutic resistance and treatment failure in solid tumours. Distinct tumour cell populations within the same specimen can make effective targeting harder.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What does the model suggest about using a single CAR T-cell dose?",{"text":117,"@type":113},"A single dose is expected to reduce tumour size and growth rate, but may not be sufficient to completely eliminate the tumour. Increasing dosage also raises the amount of free CART cells and the risk of side effects.",{"name":119,"@type":110,"acceptedAnswer":120},"How can the therapy strategy address antigen escape and tumour heterogeneity?",{"text":121,"@type":113},"The study tests multi-antigen recognition therapy to overcome antigen escape. It can eliminate the organoid at larger dosages, but it increases the risk of side effects, so an appropriate low-dosage dosimetry strategy is needed.","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},332108,1790230472,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"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":36,"preview_page_count":4},549758252649,"https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nIn silico study of heterogeneous tumour‑derived organoid response to CART‑cell therapy  \nLuciana Melina Luque1*, Carlos Manuel Carlevaro2,3, Enrique Rodriguez‑Lomba4 & Enrique Lomba 5  \nChimeric antigen receptor (CAR) T‑cell therapy is a promising immunotherapy for treating cancers. This method consists in modifying the patients’T‑cells to directly target antigen‑presenting cancer cells. One of the barriers to the development of this type of therapies, is target antigen heterogeneity.  \nIt is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency. In this work we introduce an agent‑based model (ABM), built upon a previous ABM, to rationalise the outcomes of different CART‑cells therapies strategies over heterogeneous tumour‑derived organoids. We found that one dose of CART‑cell therapy should be expected to reduce the tumour size as well as its growth rate, however it may not be enough to completely eliminate it. Moreover, the amount of free CART‑cells (i.e. CART‑cells that did not kill any cancer cell) increases as we increase the dosage, and so does the risk of side effects. We tested different strategies to enhance smaller dosages, such as enhancing the CART‑cells long‑term persistence and multiple dosing. For both approaches an appropriate dosimetry strategy is necessary to produce “effective yet safe” therapeutic results. Moreover, an interesting emergent phenomenon results from the simulations, namely the formation of a shield‑like structure of cells with low antigen expression. This shield turns out to protect cells with high antigen expression. Finally we tested a multi‑antigen recognition therapy to overcome antigen escape and heterogeneity. Our studies suggest that larger dosages can completely eliminate the organoid, however the multi‑ antigen recognition increases the risk of side effects. Therefore, an appropriate small dosages dosimetry strategy is necessary to improve the outcomes. Based on our results, it is clear that a proper therapeutic strategy could enhance the therapies outcomes. In that direction, our computational approach provides a framework to model treatment combinations in different scenarios and to explore the characteristics of successful and unsuccessful treatments.  \nChimeric antigen receptor (CAR) T-cell therapy is a promising new immunotherapy that combines advancesin cellular engineering and personalised medicine for patient-specific, targeted cancer treatment. This therapy involves collecting, purifying, and genetically modifying a patient’s own T-cells to express a CAR that specifically targets the patient’s tumour. These engineered cells are expanded ex vivo and then re-infused into the patient where the CAR T-cells target and kill antigen-expressing tumour cells1–3. So far, the FDA-approved CAR T-cell therapies and many studies expanding CAR designs exclusively target “liquid” cancers, against which they have shown great success in the clinic with response rates between 70–90%4. In contrast, response rates for solid cancers are significantly lower ranging from 4–16%4.  \nOne of the barriers to the development of effective cellular therapies in solid tumours, specifically CART-cells, is target antigen intratumour heterogeneity4,5. Intratumour heterogeneity (also known as intralesion heterogeneity) refers to distinct tumour cell populations with different molecular and phenotypic profiles within the same tumour specimen6,7, and it is associated with poor prognosis and outcome8–11. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure  \n1Centre for Regenerative Medicine, University of Edinburgh, Edinburgh EH16 4UU, UK. 2Instituto de","cbCaij9QY5tWNXMe","https://ap.wps.com/l/cbCaij9QY5tWNXMe","pdf",4380684,16,"English","# Introduction\n## CAR T-cell therapy and antigen heterogeneity\n## Solid vs liquid cancers: response-rate context\n# Modeling approach\n## Agent-based model for heterogeneous organoid outcomes\n## Dosage effects and free CART-cell dynamics\n# Strategies and simulation outcomes\n## Persistence enhancement and multiple dosing\n## Dosimetry for effective yet safe results\n## Emergent low-antigen shielding phenomenon\n## Multi-antigen recognition to address antigen escape","[{\"question\":\"Why is target antigen heterogeneity important for CAR T-cell therapy outcomes?\",\"answer\":\"Target antigen heterogeneity is linked to therapeutic resistance and treatment failure in solid tumours. Distinct tumour cell populations within the same specimen can make effective targeting harder.\"},{\"question\":\"What does the model suggest about using a single CAR T-cell dose?\",\"answer\":\"A single dose is expected to reduce tumour size and growth rate, but may not be sufficient to completely eliminate the tumour. Increasing dosage also raises the amount of free CART cells and the risk of side effects.\"},{\"question\":\"How can the therapy strategy address antigen escape and tumour heterogeneity?\",\"answer\":\"The study tests multi-antigen recognition therapy to overcome antigen escape. It can eliminate the organoid at larger dosages, but it increases the risk of side effects, so an appropriate low-dosage dosimetry strategy is needed.\"}]","In silico study of heterogeneous tumour-derived organoid response to CAR T-cell therapy | PDF",1789996822]