Lunit, a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, has announced a groundbreaking study published in the Journal for ImmunoTherapy of Cancer (JITC) that demonstrates the predictive value of its AI-powered biomarker, Lunit SCOPE IO. The study shows that SCOPE IO can accurately predict favorable outcomes of patients with the Inflamed Immune Phenotype (IIP) who are treated with Immune Checkpoint Inhibitor (ICI) therapy across multiple types of cancer.
The study, conducted on a real-world multicenter cohort of 1,806 ICI-treated patients across 27 tumor types, reveals a correlation between the Inflamed Immune Phenotype and positive treatment responses to ICIs. This is significant because there is a critical need for improved immunotherapy biomarkers, and Lunit SCOPE IO addresses this need by quantifying immune phenotype from H&E stained slides, making it a broadly accessible biomarker for immunotherapy.
Using advanced machine learning models, Lunit SCOPE IO segments tissue into cancer area (CA) and cancer stroma (CS) within whole slide images (WSIs) and detects Tumor-Infiltrating Lymphocytes (TILs) using a cell detection model trained on over 17,000 WSIs spanning various solid tumor types. Based on TIL density, the model classifies tumors into one of three immune phenotypes: Inflamed (IIP), Immune Excluded (IEP), and Immune Desert (IDP).
The study demonstrates that in an independent real-world dataset of ICI-treated patients, Lunit SCOPE IO has predictive power for objective response rates (ORR), progression-free survival (PFS), and overall survival (OS). In particular, IIP patients showed significantly more favorable clinical outcomes post-ICI treatment, including higher ORRs, prolonged PFS, and increased OS. These findings hold true regardless of the ICI regimen or PD-L1 expression.
The dataset used in the study reflects global diversity, with data coming from renowned institutions such as Stanford University, Samsung Medical Center, Seoul National University Bundang Hospital, Chonnam National University Hospital, and Northwestern Memorial Hospital.
This study is a major advancement in the field of immunotherapy biomarkers, as it leverages AI to analyze the tumor microenvironment and quantitatively determine immune phenotype, thereby predicting patient responses to ICI therapy. Lunit SCOPE IO holds significant promise for personalized treatment strategies, delivering improved outcomes and potentially redefining the standard of care for patients across various cancer types where predictive biomarkers are lacking.
The study’s findings were published in the Journal for ImmunoTherapy of Cancer (JITC), the official journal of the Society for Immunotherapy of Cancer (SITC). SITC is a leading member-driven organization focused on advancing the science and application of cancer immunotherapy, comprising over 4,650 members from 35 medical specialties across 63 countries worldwide.
Lunit, founded in 2013, is dedicated to utilizing AI to conquer cancer by ensuring accurate diagnosis and optimal treatment for each patient. Their AI-powered medical image analytics and AI biomarkers have been featured in major peer-reviewed journals like the Journal of Clinical Oncology and the Lancet Digital Health, as well as international conferences including ASCO and RSNA.
With FDA clearance and the CE Mark, Lunit’s flagship product, Lunit INSIGHT, is currently used in approximately 3,000+ hospitals and medical institutions across 40+ countries. Lunit is headquartered in South Korea but has offices and representatives worldwide.
Lunit SCOPE is a suite of AI-powered software designed to analyze tissue slide images for digital pathology and AI biomarker development, with a focus on optimizing workflow and facilitating more accurate and predictive clinical data for clinicians and researchers. Lunit SCOPE IO specifically analyzes the tumor microenvironment based on H&E analysis and provides AI-based predictive clinical outcome information. Additionally, Lunit offers AI-driven Immunohistochemistry (IHC) slide analysis services through products like Lunit SCOPE PD-L1, Lunit SCOPE HER2, and Lunit SCOPE ER/PR.
The study conducted by Lunit showcases the immense potential of AI in improving patient selection for immunotherapy and providing personalized and effective strategies for cancer treatment. This research is a critical step towards better biomarkers for immunotherapy, enabling more precise diagnoses and tailored therapies that can ultimately enhance cancer patient outcomes.
