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Artificial Intelligence-Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as a Potential Biomarker for Immune Checkpoint Inhibitors in Patients with Biliary Tract Cancer

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dc.contributor.authorBang, Yeong Hak-
dc.contributor.authorLee, Choong-kun-
dc.contributor.authorBang, Kyunghye-
dc.contributor.authorKim, Hyung-Don-
dc.contributor.authorKim, Kyu-pyo-
dc.contributor.authorJeong, Jae Ho-
dc.contributor.authorPark, Inkeun-
dc.contributor.authorRyoo, Baek-Yeol-
dc.contributor.authorLee, Dong Ki-
dc.contributor.authorChoi, Hye Jin-
dc.contributor.authorChung, Taek-
dc.contributor.authorJeon, Seung Hyuck-
dc.contributor.authorShin, Eui-Cheol-
dc.contributor.authorOum, Chiyoon-
dc.contributor.authorKim, Seulki-
dc.contributor.authorLim, Yoojoo-
dc.contributor.authorPark, Gahee-
dc.contributor.authorAhn, Chang Ho-
dc.contributor.authorLee, Taebum-
dc.contributor.authorFinn, Richard S.-
dc.contributor.authorOck, Chan-Young-
dc.contributor.authorShin, Jinho-
dc.contributor.authorYoo, Changhoon-
dc.contributor.author이동기-
dc.date.accessioned2026-04-23T07:19:47Z-
dc.date.available2026-04-23T07:19:47Z-
dc.date.created2025-07-01-
dc.date.issued2024-10-
dc.identifier.issn1078-0432-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/211904-
dc.description.abstractPurpose: Recently, anti-programmed cell death-1/anti-programmed cell death ligand-1 (anti-PD1/L1) immunotherapy has been demonstrated for its efficacy when combined with cytotoxic chemotherapy in randomized phase 3 trials for advanced biliary tract cancer (BTC). However, no biomarker predictive of benefit has been established for anti-PD1/L1 in BTC. Here, we evaluated tumor-infiltrating lymphocytes (TIL) using artificial intelligence-powered immune phenotype (AI-IP) analysis in advanced BTC treated with anti-PD1. Experimental Design: Pretreatment hematoxylin and eosin (H&E)-stained whole-slide images from 339 patients with advanced BTC who received anti-PD1 as second-line treatment or beyond, were employed for AI-IP analysis and correlative analysis between AI-IP and efficacy outcomes with anti-PD1. Next, data and images of the BTC cohort from The Cancer Genome Atlas (TCGA) were additionally analyzed to evaluate the transcriptomic and mutational characteristics of various AI-IP in BTC. Results: Overall, AI-IP were classified as inflamed [high intratumoral TIL (iTIL)] in 40 patients (11.8%), immune-excluded (low iTIL and high stromal TIL) in 167 patients (49.3%), and immune-desert (low TIL overall) in 132 patients (38.9%). The inflamed IP group showed a substantially higher overall response rate compared with the noninflamed IP groups (27.5% vs. 7.7%, P < 0.001). Median overall survival and progression-free survival were significantly longer in the inflamed IP group than in the noninflamed IP group (OS, 12.6 vs. 5.1 months; P = 0.002; PFS, 4.5 vs. 1.9 months; P < 0.001). In the TCGA cohort analysis, the inflamed IP showed increased cytolytic activity scores and IFN gamma signature compared with the noninflamed IP. Conclusions: AI-IP based on spatial TIL analysis was effective in predicting the efficacy outcomes in patients with BTC treated with anti-PD1 therapy. Further validation is necessary in the context of anti-PD1/L1 plus gemcitabine-cisplatin.-
dc.languageEnglish-
dc.publisherAmerican Association for Cancer Research-
dc.relation.isPartOfCLINICAL CANCER RESEARCH-
dc.relation.isPartOfCLINICAL CANCER RESEARCH-
dc.titleArtificial Intelligence-Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as a Potential Biomarker for Immune Checkpoint Inhibitors in Patients with Biliary Tract Cancer-
dc.typeArticle-
dc.contributor.googleauthorBang, Yeong Hak-
dc.contributor.googleauthorLee, Choong-kun-
dc.contributor.googleauthorBang, Kyunghye-
dc.contributor.googleauthorKim, Hyung-Don-
dc.contributor.googleauthorKim, Kyu-pyo-
dc.contributor.googleauthorJeong, Jae Ho-
dc.contributor.googleauthorPark, Inkeun-
dc.contributor.googleauthorRyoo, Baek-Yeol-
dc.contributor.googleauthorLee, Dong Ki-
dc.contributor.googleauthorChoi, Hye Jin-
dc.contributor.googleauthorChung, Taek-
dc.contributor.googleauthorJeon, Seung Hyuck-
dc.contributor.googleauthorShin, Eui-Cheol-
dc.contributor.googleauthorOum, Chiyoon-
dc.contributor.googleauthorKim, Seulki-
dc.contributor.googleauthorLim, Yoojoo-
dc.contributor.googleauthorPark, Gahee-
dc.contributor.googleauthorAhn, Chang Ho-
dc.contributor.googleauthorLee, Taebum-
dc.contributor.googleauthorFinn, Richard S.-
dc.contributor.googleauthorOck, Chan-Young-
dc.contributor.googleauthorShin, Jinho-
dc.contributor.googleauthorYoo, Changhoon-
dc.identifier.doi10.1158/1078-0432.CCR-24-1265-
dc.relation.journalcodeJ00564-
dc.identifier.pmid39150517-
dc.contributor.affiliatedAuthorLee, Choong-kun-
dc.contributor.affiliatedAuthorLee, Dong Ki-
dc.contributor.affiliatedAuthorChoi, Hye Jin-
dc.contributor.affiliatedAuthorChung, Taek-
dc.identifier.scopusid2-s2.0-85206399430-
dc.identifier.wosid001338631000028-
dc.citation.volume30-
dc.citation.number20-
dc.citation.startPage4635-
dc.citation.endPage4643-
dc.identifier.bibliographicCitationCLINICAL CANCER RESEARCH, Vol.30(20) : 4635-4643, 2024-10-
dc.identifier.rimsid87234-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordPlusOPEN-LABEL-
dc.subject.keywordPlusMULTICENTER-
dc.subject.keywordPlusCHOLANGIOCARCINOMA-
dc.subject.keywordPlusPHASE-2-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryOncology-
dc.relation.journalResearchAreaOncology-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers

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