New Study Demonstrates Predictive Value of Lunit SCOPE IO to Predict Outcomes of Immune Checkpoint Inhibitor Therapy Across Diverse Tumors - published in the JITC

 - A new study published in the Journal for ImmunoTherapy of Cancer (JITC) shows that Lunit's AI-powered biomarker "Lunit SCOPE IO" can predict favorable outcomes of Inflamed Immune Phenotype patients treated with Immune Checkpoint Inhibitor across multiple cancer types

SEOUL, South Korea, Feb. 16, 2024 /PRNewswire/ -- Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced a groundbreaking study published in the Journal for ImmunoTherapy of Cancer (JITC). The study demonstrates the ability of Lunit SCOPE IO, to enable quantitative immune phenotyping from H&E stained slides as a broadly accessible biomarker for immunotherapy.

The study, conducted on a real-world multicenter cohort of 1,806 Immune Checkpoint Inhibitor (ICI)-treated patients across 27 tumor types, showcases a correlation between the Inflamed Immune Phenotype and positive ICI treatment responses. There is an unmet need for improved immunotherapy biomarkers, and this study highlights the importance of Lunit SCOPE IO's ability to quantify immune phenotype (IP) as Inflamed, Excluded, or Desert, purely from H&E whole slide images (WSIs).

Utilizing advanced machine learning (ML) models, Lunit SCOPE IO segments tissue into cancer area (CA) and cancer stroma (CS) within WSIs. The model also detects Tumor-Infiltrating Lymphocytes (TILs) using a cell detection model trained on over 17,000 WSIs spanning multiple solid tumor types.

Based on TIL density, the model classifies the tumor into one of three immune phenotypes: Inflamed (IIP; high TIL density within CA), Immune Excluded (IEP; TILs within CS but excluded from CA), and Immune Desert (IDP; low TIL density within both CA and CS).

In an independent real-world dataset of ICI-treated patients, Lunit SCOPE IO demonstrated predictive power for clinical outcomes, including objective response rates (ORR), progression-free survival (PFS), and overall survival (OS). In the study, IIP patients showed significantly favorable clinical outcomes post-ICI treatment. More favorable ORRs (26.3% vs 15.8%), prolonged PFS (5.3 vs. 3.1 months) and OS (25.3 vs. 13.6 months) were observed in IIP patients, irrespective of ICI regimen or programmed death-ligand 1 (PD-L1) expression. The dataset reflected global diversity, with data coming from Stanford University, Samsung Medical Center, Seoul National University Bundang Hospital, Chonnam National University Hospital, and Northwestern Memorial Hospital, and more.

This study paves the way for more precise patient selection with a time-efficient and labor-efficient analysis at scale in immunotherapy. Lunit plans to further validate and deploy Lunit SCOPE IO, ultimately enabling more personalized and effective immunotherapy strategies, especially under the current limitations of traditional biomarkers.

"This study marks a major step towards better biomarkers for immunotherapy driven by AI, analyzing the tumor microenvironment to determine immune phenotype quantitatively and predict patient responses to ICI therapy," said Brandon Suh CEO of Lunit. "Our commitment to advancing cancer care through innovation has never been clearer. By providing a robust tool for personalized treatment strategies, Lunit SCOPE IO promises improved outcomes and could redefine the standard of care for patients in several cancer types where predictive biomarkers are lacking."

Published in the JITC, the official journal of the Society for Immunotherapy of Cancer (SITC), the study also contributes to SITC's mission of enhancing cancer patient outcomes by advancing the science and application of cancer immunotherapy. SITC is the world's leading member-driven organization that includes over 4,650 members from 35 medical specialties across 63 countries worldwide.

About Lunit

Founded in 2013, Lunit is a deep learning-based medical AI company on a mission to conquer cancer. We are committed to harnessing AI to ensure accurate diagnosis and optimal treatment for each cancer patient using AI-powered medical image analytics and AI biomarkers.

As a medical AI company grounded on clinical evidence, our findings are presented in major peer-reviewed journals, such as the Journal of Clinical Oncology and the Lancet Digital Health, and global conferences, including ASCO and RSNA.

After receiving FDA clearance and the CE Mark, our flagship Lunit INSIGHT suite is clinically used in approximately 3,000+ hospitals and medical institutions across 40+ countries. Lunit is headquartered in Seoul, South Korea, with offices and representatives worldwide. For more information, please visit 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