{"id":1829,"date":"2023-12-01T13:46:21","date_gmt":"2023-12-01T13:46:21","guid":{"rendered":"https:\/\/www.lunit.io\/publication\/artificial-intelligence-powered-spatial-analysis-of-tumor-microenvironment-tme-in-nasopharyngeal-carcinoma-npc-patients-treated-with-immune-checkpoint-inhibitors-ici\/"},"modified":"2025-11-01T05:25:47","modified_gmt":"2025-11-01T05:25:47","slug":"artificial-intelligence-powered-spatial-analysis-of-tumor-microenvironment-tme-in-nasopharyngeal-carcinoma-npc-patients-treated-with-immune-checkpoint-inhibitors-ici","status":"publish","type":"publication","link":"https:\/\/www.lunit.io\/en\/publication\/artificial-intelligence-powered-spatial-analysis-of-tumor-microenvironment-tme-in-nasopharyngeal-carcinoma-npc-patients-treated-with-immune-checkpoint-inhibitors-ici\/","title":{"rendered":"Artificial intelligence-powered spatial analysis of tumor microenvironment (TME) in nasopharyngeal carcinoma (NPC) patients treated with immune checkpoint inhibitors (ICI)"},"content":{"rendered":"

Artificial intelligence-powered spatial analysis of tumor microenvironment (TME) in nasopharyngeal carcinoma (NPC) patients treated with immune checkpoint inhibitors (ICI)<\/h3>\n

Bhumsuk Keam, Darren Wan-Teck Lim, Chan-Young Ock, Taebum Lee, Chiyoon Oum, Hsiang-Fong Kao, Joe Yeong, Boon Cher Goh, Sze Huey Tan, Edwin P Hui, Hyun Ae Jung, Keon-Uk Park, Sanghee Cho, Keun-Wook Lee, Anthony TC Chan, Brigette Ma<\/p>\n

ESMO ASIA, 2023<\/strong><\/p>\n

Background<\/strong>
\nICI have promising activity in phase II trials of patients (pts) with recurrent or metastatic NPC. We investigated whether AI-powered spatial tumor infiltrating lymphocyte analysis (AI-STIL) of NPC TME cell subpopulations correlate with clinical outcome in pts treated with ICI-based therapy.<\/p>\n

Methods<\/strong>
\nA total of 73 NPC pts treated with Nivolumab+Gemcitabine (Niv+Gem; KCSG HN17-11), Niv+Ipilimumab (Niv+Ipi, NCT03097939), Niv alone (Niv, NCT02339558), or Avelumab+Axitinib (Ave+Axi, NCT04562441) who have matched H&E slides before treatment were included in this exploratory post-hoc analysis. Lunit SCOPE IO (Lunit, Korea) was applied to spatially analyze TIL, macrophages (MP), fibroblasts (FB), and endothelial cells (EC) in the intratumoral area and adjacent stroma. Cell populations were analyzed.<\/p>\n

Results<\/strong>
\nIn all merged dataset, the median progression-free survival (mPFS) and overall survival (mOS) were 7.3 mo and 30 mo, respectively. ORR\/mPFS by each regimen were 38.7%\/13.8 m in Niv+Gem (n=31), 36.4%\/5.4 m in Niv+Ipi (n=22), 36.4%\/3.7 m in Niv (n=11), and 0%\/5.4 m in Ave+Axi (n=9), respectively. In TIL subgroup analysis, mPFS was significantly higher in high intratumoral TIL (iTIL) than low iTIL group (hazard ratio, HR 0.44, p=0.0081), but no difference in stromal TIL (sTIL, HR 1.14, p=0.6681). mPFS was longer in the high intratumoral MP subgroup (HR 0.5, p=0.0209), but not the stromal MP subgroup (HR 0.9, p=0.7278). In FB and EC analyses, mOS was lower in high stromal FB (sFB) than low sFB (HR 2.44, p=0.0148), but there were no significant differences in survival outcomes across the other cell subgroups.<\/p>\n

Conclusions<\/strong>
\nInteractive TME analysis powered by AI suggested that intratumoral TIL or macrophage, not stromal residues, are clinically significant in the NPC patients treated with ICI.<\/p>\n

View abstract<\/strong><\/a><\/p>\n","protected":false},"featured_media":0,"template":"","publication-oncology":[95,83,133,77,93],"publication-region":[],"publication-type":[],"radiology":[],"class_list":["post-1829","publication","type-publication","status-publish","hentry","publication-oncology-conference-posters","publication-oncology-head-and-neck","publication-oncology-lunit-scope-io","publication-oncology-tumor-type","publication-oncology-type-of-evidence"],"acf":[],"yoast_head":"\nArtificial intelligence-powered spatial analysis of tumor microenvironment (TME) in nasopharyngeal carcinoma (NPC) patients treated with immune checkpoint inhibitors (ICI) - 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-powered-spatial-analysis-of-tumor-microenvironment-tme-in-nasopharyngeal-carcinoma-npc-patients-treated-with-immune-checkpoint-inhibitors-ici\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Artificial intelligence-powered spatial analysis of tumor microenvironment (TME) in nasopharyngeal carcinoma (NPC) patients treated with immune checkpoint inhibitors (ICI) - 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