Announcement • May 24

Lunit Presents Ai-Powered Ihc Biomarker Quantification and Spatial Tumor Microenvironment Analysis At Asco 2026

Lunit announced that five studies featuring its AI biomarker platforms are being presented at the 2026 American Society of Clinical Oncology (ASCO) Annual Meeting, taking place May 29–June 2 in Chicago, IL. This year's presentations reflect Lunit's expanding biomarker research beyond conventional immune profiling toward integrated AI-powered HER2/IHC biomarker quantification and spatial tumor microenvironment (TME) analysis. Using AI to characterize HER2 expression, immune phenotypes, tertiary lymphoid structures (TLS), tumor-infiltrating lymphocytes (TILs), and endothelial cells, the studies highlight the potential of integrated biomarker analysis to improve precision patient stratification across multiple cancer types. The five presentations include studies across biliary tract cancer (BTC), non-small cell lung cancer (NSCLC), adenoid cystic carcinoma (ACC), microsatellite-stable (MSS), metastatic colorectal cancer and advanced gastric cancer (AGC). One of the featured studies, led by researchers at Yonsei University College of Medicine, evaluates a first-line quadruplet regimen consisting of trastuzumab, nivolumab, gemcitabine, and cisplatin in HER2-positive advanced BTC. Using AI-powered whole-slide image (WSI) analysis, researchers analyze HER2 expression and immune phenotypes within tumor tissue. Among 40 patients enrolled in the multi-center phase Ib/II trial, the combination of therapy demonstrates an objective response rate (ORR) of 55%, disease control rate (DCR) of 95%, and median progression-free survival (PFS) of 10.6 months. Patients with HER2 IHC 3+ tumor cell proportions =10%, as identified by AI analysis, achieve substantially higher response rates compared to those below the threshold (80% vs. 36.4%). The study demonstrates how integrated AI-powered HER2 and spatial tumor microenvironment analysis may help identify patients more likely to benefit from HER2-targeted combination therapies. Another study characterizes the tumor microenvironment landscape of HER2-overexpressing NSCLC using AI-powered spatial analysis. Across more than 2,000 NSCLC whole-slide images, HER2-overexpressing tumors demonstrate significantly reduced tumor-infiltrating lymphocyte density and lower proportions of inflamed immune phenotype compared to non-overexpressing tumors. The immune-cold phenotype becomes more pronounced in tumors with higher proportions of HER2 3+ cells. The study provides additional insight into the biological relationship between HER2 overexpression and tumor immune status, while highlighting the broader potential of combining AI-powered HER2 analysis with spatial tumor microenvironment characterization in biomarker research. Another featured study, conducted with Seoul National University Hospital, explores AI-powered spatial tumor microenvironment analysis in adenoid cystic carcinoma (ACC), a rare cancer with limited treatment options. Researchers identify a subgroup of ACC patients with high endothelial cell and tumor-infiltrating lymphocyte (TIL) densities who demonstrate significantly prolonged progression-free survival following axitinib treatment (19.6 months vs. 11.1 months). The findings suggest that AI-based spatial profiling may help distinguish responder populations that are difficult to stratify using conventional biomarkers alone. Researchers at Asan Medical Center investigate AI-powered tumor microenvironment analysis in MSS metastatic colorectal cancer, which is generally considered resistant to immune checkpoint inhibitors (ICIs). Researchers find that patients with larger tertiary lymphoid structure (TLS) regions identified by AI demonstrate improved progression-free survival and overall survival following immunotherapy. The findings highlight the potential of AI-powered spatial analysis to identify MSS colorectal cancer patients more likely to benefit from immunotherapy.

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Lunit Presents Ai-Powered Ihc Biomarker Quantification and Spatial Tumor Microenvironment Analysis At Asco 2026

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