Lunit AI Identifies Immune Phenotyping as Predictive Biomarker in Biliary Tract Cancer

Lunit, a prominent provider of AI-driven cancer diagnostics and therapeutics, has revealed that its AI tool, Lunit SCOPE IO®, shows considerable promise in predicting immunotherapy responses for advanced biliary tract cancer (BTC) patients. This revelation comes from a groundbreaking study conducted in collaboration with researchers from Asan Medical Center and Severance Hospital in Seoul, Korea. The findings have been published in Clinical Cancer Research (CCR), an AACR journal.

BTC is notorious for its grim prognosis and limited treatment options. Recent advancements have suggested that combining immunotherapy, such as anti-PD-1 inhibitors, with standard chemotherapy could be beneficial. However, the field has lacked effective predictive tools to guide these treatment decisions. Lunit SCOPE IO aims to fill this gap.

The study analyzed pre-treatment pathology samples, specifically hematoxylin and eosin (H&E) slides, from 339 patients with advanced BTC. These patients received anti-PD-1 monotherapy as a second-line or later treatment. Utilizing Lunit SCOPE IO, researchers conducted detailed analyses of the tumor microenvironment. They classified patients' immune phenotypes into three categories: inflamed (high intratumoral tumor-infiltrating lymphocytes, or TILs), immune-excluded (low intratumoral TILs and high stromal TILs), and immune desert (low TILs overall). These immune phenotypes are increasingly recognized as pan-cancer biomarkers, supported by leaders in the immuno-oncology field.

The study uncovered several key findings. Patients with an "inflamed" immune phenotype experienced significantly better treatment outcomes compared to those with non-inflamed phenotypes, in line with previous studies. Specifically, the inflamed group exhibited longer overall survival (12.6 months vs. 5.1 months) and progression-free survival (4.5 months vs. 1.9 months). They also had higher overall response rates to the treatment (27.5% vs. 7.7%).

Lunit SCOPE IO demonstrated an ability to provide objective and efficient assessments of the tumor microenvironment. This capability addresses the limitations of manual evaluation techniques and highlights the high feasibility of AI-powered analysis of immune phenotypes and TILs.

Importantly, the study suggests that immune phenotyping can serve as a predictive biomarker for potential responses to immunotherapy in BTC patients. This finding addresses a long-standing gap in personalized treatment approaches for these cancers, which have a high unmet need.

Brandon Suh, CEO at Lunit, emphasized the significance of Lunit SCOPE IO in the precision medicine landscape for cancer treatment. According to Suh, the AI technology provides a deeper understanding of the tumor microenvironment, particularly immune phenotyping. This empowers clinicians to make informed treatment decisions, identifying patients most likely to benefit from immunotherapy and paving the way for personalized treatment strategies in challenging cancer types.

Founded in 2013, Lunit is dedicated to using AI to combat cancer. The company employs AI-powered medical image analytics and AI biomarkers to ensure accurate diagnosis and optimal treatment for each cancer patient. Their FDA-cleared Lunit INSIGHT suite for cancer screening is utilized by over 3,500 hospitals and medical institutions in more than 50 countries.

Lunit's clinical studies have been featured in top journals like the Journal of Clinical Oncology and the Lancet Digital Health. They have also been presented at global conferences such as ASCO and RSNA. In 2024, Lunit acquired Volpara Health Technologies, enhancing their capabilities, particularly in breast health and screening technologies. Headquartered in Seoul, South Korea, with a global network of offices, Lunit remains at the forefront of the global fight against cancer.

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