{"id":1815,"date":"2023-10-20T13:46:18","date_gmt":"2023-10-20T13:46:18","guid":{"rendered":"https:\/\/www.lunit.io\/publication\/artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc\/"},"modified":"2025-11-01T05:44:44","modified_gmt":"2025-11-01T05:44:44","slug":"artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc","status":"publish","type":"publication","link":"https:\/\/www.lunit.io\/en\/publication\/artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc\/","title":{"rendered":"Artificial intelligence (AI)-powered analysis of human epidermal growth factor receptor-2 (HER2) and tumor-infiltrating lymphocytes (TILs) in advanced biliary tract cancer (BTC)"},"content":{"rendered":"<h3>Artificial intelligence (AI)-powered analysis of human epidermal growth factor receptor-2 (HER2) and tumor-infiltrating lymphocytes (TILs) in advanced biliary tract cancer (BTC)<\/h3>\n<p>Hong Jae Chon, Beodeul Kang, Chan Kim, Gwangil Kim, Seunghwan Shin, Taebum Lee, Sanghoon Song, Sukjun Kim, Mohammad Mostafavi, Heon Song, Sergio Pereira<\/p>\n<p><strong>ESMO, 2023<\/strong><\/p>\n<p><strong>Background<\/strong><br \/>\nHER2 is overexpressed in a subset of BTC patients, and recent developments in HER2-targeted agents are expanding therapeutic options. However, accurately assessing HER2 expression is challenging in BTC, especially at a low-expression level. We evaluated HER2 expression as well as TILs density through AI models in BTC.<\/p>\n<p><strong>Methods<\/strong><br \/>\nWhole-slide images (WSI) of pre-treatment HER2 immunohistochemistry (IHC) slides, matched H&amp;E-stained slides and clinicopathological data were obtained from advanced or metastatic BTC patients at CHA Bundang Medical Center in South Korea, between 2019 and 2022. An AI-powered HER2 analyzer classifies tumor cells by HER2 staining intensity (H0, H1, H2, or H3) and quantifies the cells in each staining category. Then, it calculates HER2 categories (0\/1+\/2+\/3+) following the latest ASCO\/CAP HER2 IHC guidelines. For evaluating immune landscape, a separate WSI analyzer identified and quantified. TILs within the cancer epithelium or stroma from H&amp;E-stained slides.<\/p>\n<p><strong>Results<\/strong><br \/>\nIn a total of 328 patients, the AI-scored HER2 categories were 0 in 92 (28.9%), 1+ in 137 (43.1%), 2+ in 68 (21.4%), and 3+ in 21 (6.6%). The overall concordance of HER2 categories between the AI and pathologists\u2019 readings was 75.3%. HER2 3+ rates by AI in intrahepatic, extrahepatic, gallbladder, and Ampulla of Vater are estimated to be 3.1%, 3.4%, 21.4%, and 5.9%, respectively. HER2-expressing tumors (1+, 2+, and 3+) have significantly higher densities of stromal TILs (983.2 \u00b1 1347.5 \/ mm2) than HER2-negative tumors (683.5 \u00b1 739.7 \/ mm2, p=0.012) and there were no significant TIL density differences between HER2-high expressing (3+) and low expressing tumors (1+, 2+), which were consistent with either by the AI or pathologists.<\/p>\n<p><strong>Conclusions<\/strong><br \/>\nAI-powered HER2 scoring showed good agreement with pathologists\u2019 scoring, and HER2-expressing tumors harbored high stromal TIL in BTC. Objective expression analysis and the associated differences in immunogenicity will be important for future treatment strategies.<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.annalsofoncology.org\/article\/S0923-7534(23)02253-6\/fulltext\"><strong>View abstract<\/strong><\/a><\/p>\n","protected":false},"featured_media":0,"template":"","publication-oncology":[95,79,134,70,77,93],"publication-region":[],"publication-type":[],"radiology":[],"class_list":["post-1815","publication","type-publication","status-publish","hentry","publication-oncology-conference-posters","publication-oncology-gi","publication-oncology-lunit-scope-her2","publication-oncology-product","publication-oncology-tumor-type","publication-oncology-type-of-evidence"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Artificial intelligence (AI)-powered analysis of human epidermal growth factor receptor-2 (HER2) and tumor-infiltrating lymphocytes (TILs) in advanced biliary tract cancer (BTC) - Lunit<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.lunit.io\/en\/publication\/artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Artificial intelligence (AI)-powered analysis of human epidermal growth factor receptor-2 (HER2) and tumor-infiltrating lymphocytes (TILs) in advanced biliary tract cancer (BTC) - Lunit\" \/>\n<meta property=\"og:description\" content=\"Artificial intelligence (AI)-powered analysis of human epidermal growth factor receptor-2 (HER2) and tumor-infiltrating lymphocytes (TILs) in advanced biliary tract cancer (BTC) Hong Jae Chon, Beodeul Kang, Chan Kim, Gwangil Kim, Seunghwan Shin, Taebum Lee, Sanghoon Song, Sukjun Kim, Mohammad Mostafavi, Heon Song, Sergio Pereira ESMO, 2023 Background HER2 is overexpressed in a subset of BTC [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.lunit.io\/en\/publication\/artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc\/\" \/>\n<meta property=\"og:site_name\" content=\"Lunit\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-01T05:44:44+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@lunit_ai\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.lunit.io\\\/en\\\/publication\\\/artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc\\\/\",\"url\":\"https:\\\/\\\/www.lunit.io\\\/en\\\/publication\\\/artificial-intelligence-ai-powered-analysis-of-human-epidermal-growth-factor-receptor-2-her2-and-tumor-infiltrating-lymphocytes-tils-in-advanced-biliary-tract-cancer-btc\\\/\",\"name\":\"Artificial intelligence (AI)-powered analysis of human epidermal growth factor receptor-2 (HER2) and tumor-infiltrating lymphocytes (TILs) in advanced biliary tract cancer (BTC) - 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