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This study develops an artificial intelligence–based immunoscore and evaluates its patho-immunoscore value for predicting clinical outcomes. The analyzer is trained on 1,333 TCGA-LUAD whole-slide images and validated in CPTAC-LUAD and ORIENT-11 cohorts, where high patho-immunoscore associates with longer progression-free survival under chemoimmunotherapy.",{"@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/association-of-artificial-intelligence-based-immunoscore-with-the-efficacy-of-chemoimmunotherapy-in-advanced-non-squamous-non-small-cell-lung-cancer-a-multicentre-retrospective-study/343816/",{"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/association-of-artificial-intelligence-based-immunoscore-with-the-efficacy-of-chemoimmunotherapy-in-advanced-non-squamous-non-small-cell-lung-cancer-a-multicentre-retrospective-study/343816.png","ImageObject",300,407,{"name":92,"@type":93},"Eden","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-24","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main purpose of the study?","Question",{"text":112,"@type":113},"To develop an artificial intelligence-based immunoscore and assess the value of patho-immunoscore in predicting clinical outcomes in patients with advanced non-squamous NSCLC receiving chemoimmunotherapy.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the AI-based immunoscore developed and validated?",{"text":117,"@type":113},"It was developed using 1,333 TCGA-LUAD whole-slide images, then its predictive performance was validated in the CPTAC-LUAD cohort and the biomarker cohort of ORIENT-11, with further evaluation of clinical significance in the ORIENT-11 study cohort.",{"name":119,"@type":110,"acceptedAnswer":120},"What outcome differences were observed with chemoimmunotherapy?",{"text":121,"@type":113},"Among 259 patients treated with chemoimmunotherapy, those with high patho-immunoscore had significantly longer median progression-free survival than those with low patho-immunoscore; no significant difference was observed for patients treated with chemotherapy only.","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},343816,1790219653,{"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":14,"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":41},1374391974468,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","TYPE Original Research PUBLISHED 06 November 2024 DOI 10.3389/fimmu.2024.1485703  \nOPEN ACCESS  \nEDITED BY  \nYanqing Liu,  \nColumbia University, United States  \nREVIEWED BY  \nLi Li,  \nUniversity of California, San Francisco, United States  \nMeizi Liu,  \nWashington University in St. Louis, United States  \nYuan Liu,  \nUniversity of Illinois at Urbana-Champaign, United States  \n*CORRESPONDENCE  \nYunpeng Yang  \n [yangyp@sysucc.org.cn](yangyp@sysucc.org.cn)[ ](yangyp@sysucc.org.cn)Li Zhang  \n [zhangli6@mail.sysu.edu.cn](zhangli6@mail.sysu.edu.cn)  \n†These authors have contributed equally to this work  \nRECEIVED 24 August 2024  \nACCEPTED 17 October 2024  \nPUBLISHED 06 November 2024  \nCITATION  \nLiu J, Sun D, Xu S, Shen J, Ma W, Zhou H, Ma Y, Zhang Y, Fang W, Zhao Y, Hong S, Zhan J, Hou X, Zhao H, Huang Y, He B, Yang Y and Zhang L (2024) Association of artificial intelligence-based immunoscore with the efficacy of chemoimmunotherapy in patients with advanced non-squamous non-small cell lung cancer: a multicentre retrospective study.  \nFront. Immunol. 15:1485703 .  \ndoi: 10.3389/fimmu.2024.1485703  \nCOPYRIGHT  \n© 2024 Liu, Sun, Xu, Shen, Ma, Zhou, Ma, Zhang, Fang, Zhao, Hong, Zhan, Hou, Zhao, Huang, He, Yang and Zhang. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nAssociation of artificial intelligence-based immunoscore with the efficacy of chemoimmunotherapy inpatients with advanced  \nnon-squamous non-small cell lung cancer: a multicentre retrospective study  \nJiaqing Liu 1,2,3,4†, Dongchen Sun 1,2,3,5†, Shuoyu Xu 6†,  \nJiayi Shen 1,2,3,7†, Wenjuan Ma 1,2,3,4†, Huaqiang Zhou 1,2,3,5, Yuxiang Ma 1,2,3,5, Yaxiong Zhang 1,2,3,5, Wenfeng Fang 1,2,3,5, Yuanyuan Zhao 1,2,3,5, Shaodong Hong 1,2,3,5, Jianhua Zhan 1,2,3,5, Xue Hou 1,2,3,5, Hongyun Zhao 1,2,3,5, Yan Huang 1,2,3,5, Bingdou He 6, Yunpeng Yang 1,2,3,5* and Li Zhang 1,2,3,5*  \n1State Key Laboratory of Oncology in South China, Guangzhou, China, 2Collaborative Innovation Center for Cancer Medicine, Guangzhou, China, 3Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China, 4 Department of Intensive Care Unit, Sun Yat-sen University Cancer Center, Guangzhou, China, 5 Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China, 6 Bio-totem Pte Ltd, Suzhou, China, 7 Department of Anesthesiology, Sun Yat-sen University Cancer Center, Guangzhou, China  \nPurpose: Currently, chemoimmunotherapy is effective only in a subset of patients with advanced non-squamous non-small cell lung cancer. Robust biomarkers for predicting the efficacy of chemoimmunotherapy would be useful to identify patients who would benefit from chemoimmunotherapy. The primary objective of our study was to develop an artificial intelligence-based immunoscore and to evaluate the value of patho-immunoscore in predicting clinical outcomes in patients with advanced non-squamous non-small cell lung cancer (NSCLC) .  \nMethods: We have developed an artificial intelligence–powered immunoscore analyzer based on 1,333 whole-slide images from TCGA-LUAD. The predictive efficacy of the model was further validated in the CPTAC-LUAD cohort and the biomarker cohort of the ORIENT-11 study, a randomized, double-blind, phase 3 study. Finally, the clinical significance of the patho-immunoscore was evaluated using the ORIENT-11 study cohort.  \nResults: Our immunoscore analyzer achieved good accuracy in all the three cohort mentioned above (TCGA-LUAD, mean AUC: 0.783; ORIENT-11 cohort, AUC: 0 .741; CPTAC-LUAD cohort, AUC: 0 .769) . In the 259 patients treated with chemoimmunotherapy, those with high patho-immu","cbCaim3qFUSYFjPm","https://ap.wps.com/l/cbCaim3qFUSYFjPm","pdf",13347012,12,"English","# Purpose\n# Methods\n# Results\n# Conclusion\n# Introduction\n## Background on lung cancer and NSCLC\n## Rationale for immunoscore and predictive biomarkers","[{\"question\":\"What is the main purpose of the study?\",\"answer\":\"To develop an artificial intelligence-based immunoscore and assess the value of patho-immunoscore in predicting clinical outcomes in patients with advanced non-squamous NSCLC receiving chemoimmunotherapy.\"},{\"question\":\"How was the AI-based immunoscore developed and validated?\",\"answer\":\"It was developed using 1,333 TCGA-LUAD whole-slide images, then its predictive performance was validated in the CPTAC-LUAD cohort and the biomarker cohort of ORIENT-11, with further evaluation of clinical significance in the ORIENT-11 study cohort.\"},{\"question\":\"What outcome differences were observed with chemoimmunotherapy?\",\"answer\":\"Among 259 patients treated with chemoimmunotherapy, those with high patho-immunoscore had significantly longer median progression-free survival than those with low patho-immunoscore; no significant difference was observed for patients treated with chemotherapy only.\"}]","Association of artificial intelligence-based immunoscore with the efficacy of chemoimmunotherapy in patients with advanced non-squamous non-small cell lung cancer - a multicentre retrospective study | PDF",1790052226]