Lunit to Present Six AI Studies at AACR 2026 Highlighting Advances in Precision Oncology and Real-World Clinical Application

Lunit's AACR 2026 presentations showed how AI-driven biomarkers can improve the efficiency of clinical workflows, uncover spatial features of the tumor microenvironment not captured by conventional methods, and enable integrated analysis to better support treatment decision-making.

SEOUL, South Korea, April 17, 2026 /PRNewswire/ -- Lunit (KRX:328130), a leading provider of AI for cancer diagnostics and precision oncology, presented six studies at the American Association for Cancer Research (AACR) Annual Meeting 2026, taking place from April 17 to 22 in San Diego, California.

The presentations highlighted Lunit's continued advancements in AI-driven biomarker development, tumor microenvironment (TME) analysis, and real-world clinical applicability. Several studies were conducted in collaboration with global partners, including Agilent Technologies.

In a study conducted with Agilent Technologies and Ajou University Medical Center, researchers used Lunit SCOPE IO and uIHC to analyze over 25,000 non-small cell lung cancer (NSCLC) samples. The results showed that tumors with high c-MET expression exhibited a significant reduction in immune cell density within 30 μm of tumor cells (p<0.001), revealing a spatial immune exclusion pattern not captured by conventional analysis. These findings suggest a potential link between c-MET overexpression and immune evasion, supporting combination strategies involving MET-targeted therapy and immunotherapy.

Researchers also present findings from an exploratory analysis of the phase II MOUNTAINEER trial, demonstrating that AI- quantified HER2 expression is strongly associated with treatment response in patients with HER2-positive metastatic colorectal cancer treated with tucatinib plus trastuzumab. The overall objective response rate (ORR) was 43.4%, increasing to as high as 80% in patients with higher HER2 expression, indicating a clearer dose-dependent relationship. Tumor-Infiltrating Lymphocyte (TIL) density independently predicted progression-free survival. Notably, patients with low stromal TIL levels showed no response (ORR 0%) and a significantly higher risk of disease progression.

These findings highlight the increasing complexity of biomarker assessment, where both tumor characteristics and immune context need to be considered, underscoring the potential role of AI in supporting treatment decision-making.

In addition to these representative studies, Lunit presented additional research abstracts at AACR 2026, further demonstrating the breadth of its AI-powered oncology research. These include studies on

• AI-based analysis of tumor-infiltrating lymphocyte in NSCLC in collaboration with Dr. David Rimm's lab at Yale University School of Medicine
• AI-based target discovery for bi-specific antibodies
• Biomarker research in CD47-targeted therapies

"Our AACR presentations reflect how AI is increasingly translating into real-world clinical impact" said Brandon Suh, CEO of Lunit. "Across these studies, we demonstrate how AI-driven biomarkers can enhance precision, deepen our understanding of tumor biology and increasingly support treatment decision-making in clinical practice."

Visit Lunit at Booth #2248 during AACR 2026 to learn more about its latest research and AI-powered solutions in cancer diagnostics and therapeutics.

Lunit's featured presentations at AACR 2026 include:

[Poster #0011/11] Artificial intelligence-based spatial analysis of the local tumor microenvironment in relation to c-MET expression in non-small cell lung cancer
April 19, 2:00 PM - 5:00 PM, Section 1

[Poster #7735/26] HER2 expression and tumor-infiltrating lymphocytes predict response to tucatinib plus trastuzumab in HER2-positive metastatic colorectal cancer (MOUNTAINEER): Exploratory analysis of a multicenter, Phase II trial
April 22, 9:00 AM - 12:00 PM, Section 41

[Poster #4415/23] AI-powered analysis of millions of IHC images identifies 19 spatially highly co-expressed protein pairs to enable bispecific antibody development
April 21, 9:00 AM - 12:00 PM, Section 11

[Poster #0080/11] Quantitative assessment of tumor-infiltrating lymphocytes using AI in non-small cell lung cancer and association with immunotherapy response
April 19, 2:00 PM - 5:00 PM, Section 4

[Poster #4355/26] Cryo EM-based structural characterization of IMC-002, a next-generation anti-CD47 antibody with a unique binding site and biomarker candidates, supporting evidence of enhanced safety and efficacy
April 21, 9:00 AM - 12:00 PM, Section 9

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.

Trusted by over 10,000 sites in more than 65 countries, Lunit combines deep medical expertise with continuously evolving datasets to deliver measurable impact—for patients, clinicians, and researchers alike. Headquartered in Seoul with global offices, Lunit is driving the worldwide fight against cancer. Learn more at lunit.io.

About Lunit SCOPE

Lunit SCOPE is a suite of AI-powered software that analyzes tissue slide images for digital pathology and AI biomarker development, aiming to optimize workflow and facilitate more accurate and predictive clinical data for clinicians and researchers. Lunit SCOPE platform offers multiple AI-powered tissue analysis products and assays that can streamline digital pathology workflow and diagnostics and enhance the drug development process. Lunit SCOPE IO analyzes the tumor microenvironment (TME) based on H&E analysis and provides AI-based predictive clinical outcome information. In addition, AI-driven Immunohistochemistry (IHC) slide analysis services are offered through products such as Lunit SCOPE PD-L1, Lunit SCOPE HER2, Lunit SCOPE ER/PR, and others.

SOURCE Lunit