# 在 ASCO 2026，Lunit 將展示透過 AI 驅動的 HER2/IHC 生物標記量化及空間腫瘤微環境分析，實現精準病人分層與生物標記驅動的腫瘤學研究。 *genai, biotech · news · 2026-05-21 · The Manila Times* ## Key points - Lunit 的 AI 生物標記平台將在 ASCO 2026 的五項研究中亮相。 - AI 驅動的 HER2 與腫瘤微環境分析識別出 HER2 IHC 3+ ≥10% 的患者為強效反應者。 - AI 分析顯示 HER2 過度表達的非小細胞肺癌，其腫瘤浸潤淋巴細胞密度顯著低於非過度表達腫瘤。 - 在腺樣囊性癌中，AI 識別的高內皮細胞與 TIL 密度預測使用 axitinib 後有較長的無進展存活期。 - AI 識別的 MSS 轉移性結直腸癌中較大的第三淋巴結構區域預測較佳的免疫治療效果。 At ASCO 2026, Lunit will present precision patient stratification and biomarker-driven oncology research through AI-powered HER2/IHC biomarker quantification and spatial tumor microenvironment analysis. SEOUL, South Korea, May 22, 2026 /PRNewswire/ -- Lunit, a leading provider of AI for cancer diagnostics and precision oncology, today announces 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. The study is selected as a Rapid Oral Presentation at ASCO 2026. 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. "These studies demonstrate how AI-powered biomarker analysis is evolving beyond conventional immune profiling toward integrated HER2/IHC quantification and spatial tumor microenvironment analysis," said Brandon Suh, CEO of Lunit. "We believe integrated biomarker analysis will play an increasingly important role in precision oncology research, patient stratification, and treatment-response assessment." Lunit will be exhibiting at ASCO 2026, where attendees can learn more about the company's AI biomarker platforms and research collaborations. ### Lunit's featured AI biomarker studies at ASCO 2026 include: [Rapid Oral #4016] A phase Ib/II trial of First-line Trastuzumab, Nivolumab, Gemcitabine and Cisplatin in HER2-positive biliary tract cancer (HERBOT): a multi-institutional study from the Korean Cancer Study Group [Poster #8545/335] AI-powered characterization of the tumor microenvironment landscape in HER2-overexpressing non-small cell lung cancer [Poster #6122/579] Artificial Intelligence-Powered Spatial Analysis of Endothelial Cells and Tumor-Infiltrating Lymphocytes Predicts Response to Axitinib in Adenoid Cystic Carcinoma [Poster #2532/322] AI-powered spatial tumor microenvironment analysis in metastatic microsatellite-stable colorectal cancer receiving immunotherapy [Poster #2612/402] Potential effects of TGF-β inhibition on immune resistance by targeting immunosuppressive microenvironment in advanced gastric cancer (AGC): Multi-omics post-hoc analysis of the K-Umbrella-06 Trial About Lunit Founded in 2013, Lunit (KRX: 328130) is a global leader on a mission to conquer cancer through AI. Our clinically validated solutions span medical imaging, breast health, and biomarker analysis-empowering earlier detection, smarter treatment decisions, and more precise outcomes across the cancer care continuum. Lunit offers a comprehensive suite spanning risk prediction and early detection to precision oncology. Our FDA-cleared Lunit INSIGHT Breast Suite and breast health solutions support cancer screening in thousands of medical institutions worldwide, while the Lunit SCOPE platform is used in research partnership with global pharma and laboratory leaders for biomarker research, and companion diagnostic development. **Companies:** Lunit **Countries:** South Korea, United States [Read the full story on The Manila Times](https://www.manilatimes.net/2026/05/22/tmt-newswire/pr-newswire/lunit-highlights-ai-powered-ihc-and-tumor-microenvironment-research-at-asco-2026/2349718) --- Canonical: https://newsio.io/zh-TW/n/eb88b037-8acc-4278-8759-a680bbb7549e/asco-2026lunit-ai-her2ihc Summarized by Newsio from The Manila Times. https://newsio.io/how-it-works