Cited 4 times in

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

DC Field Value Language
dc.contributor.author이동기-
dc.contributor.author이충근-
dc.contributor.author최혜진-
dc.date.accessioned2024-12-06T03:42:47Z-
dc.date.available2024-12-06T03:42:47Z-
dc.date.issued2024-10-
dc.identifier.issn1078-0432-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/201218-
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 IFNγ 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.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherAmerican Association for Cancer Research-
dc.relation.isPartOfCLINICAL CANCER RESEARCH-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAged-
dc.subject.MESHArtificial Intelligence*-
dc.subject.MESHBiliary Tract Neoplasms* / drug therapy-
dc.subject.MESHBiliary Tract Neoplasms* / immunology-
dc.subject.MESHBiliary Tract Neoplasms* / pathology-
dc.subject.MESHBiomarkers, Tumor*-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHImmune Checkpoint Inhibitors* / pharmacology-
dc.subject.MESHImmune Checkpoint Inhibitors* / therapeutic use-
dc.subject.MESHLymphocytes, Tumor-Infiltrating* / drug effects-
dc.subject.MESHLymphocytes, Tumor-Infiltrating* / immunology-
dc.subject.MESHLymphocytes, Tumor-Infiltrating* / metabolism-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPrognosis-
dc.subject.MESHProgrammed Cell Death 1 Receptor / antagonists & inhibitors-
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.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorYeong Hak Bang-
dc.contributor.googleauthorChoong-Kun Lee-
dc.contributor.googleauthorKyunghye Bang-
dc.contributor.googleauthorHyung-Don Kim-
dc.contributor.googleauthorKyu-Pyo Kim-
dc.contributor.googleauthorJae Ho Jeong-
dc.contributor.googleauthorInkeun Park-
dc.contributor.googleauthorBaek-Yeol Ryoo-
dc.contributor.googleauthorDong Ki Lee-
dc.contributor.googleauthorHye Jin Choi-
dc.contributor.googleauthorTaek Chung-
dc.contributor.googleauthorSeung Hyuck Jeon-
dc.contributor.googleauthorEui-Cheol Shin-
dc.contributor.googleauthorChiyoon Oum-
dc.contributor.googleauthorSeulki Kim-
dc.contributor.googleauthorYoojoo Lim-
dc.contributor.googleauthorGahee Park-
dc.contributor.googleauthorChang Ho Ahn-
dc.contributor.googleauthorTaebum Lee-
dc.contributor.googleauthorRichard S Finn-
dc.contributor.googleauthorChan-Young Ock-
dc.contributor.googleauthorJinho Shin-
dc.contributor.googleauthorChanghoon Yoo-
dc.identifier.doi10.1158/1078-0432.ccr-24-1265-
dc.contributor.localIdA02723-
dc.contributor.localIdA03259-
dc.contributor.localIdA04219-
dc.relation.journalcodeJ00564-
dc.identifier.pmid39150517-
dc.identifier.urlhttps://aacrjournals.org/clincancerres/article/30/20/4635/748799-
dc.contributor.alternativeNameLee, Dong Ki-
dc.contributor.affiliatedAuthor이동기-
dc.contributor.affiliatedAuthor이충근-
dc.contributor.affiliatedAuthor최혜진-
dc.citation.volume30-
dc.citation.number20-
dc.citation.startPage4635-
dc.citation.endPage4643-
dc.identifier.bibliographicCitationCLINICAL CANCER RESEARCH, Vol.30(20) : 4635-4643, 2024-10-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.