Lunit Highlights AI's Potential in Predicting Immunotherapy Response for Rare Cancers at SITC 2024

SEONGNAM, South Korea, November 8, 2024 – Lunit (KRX:328130.KQ), a prominent provider of AI-driven diagnostic and therapeutic cancer solutions, has unveiled significant research showcasing the capability of its AI to predict outcomes of immunotherapy in patients with rare tumors. This research, conducted in collaboration with The University of Texas MD Anderson Cancer Center, will be highlighted at the Society for Immunotherapy of Cancer (SITC) 2024 Annual Meeting in Houston, Texas, from November 6-10. The study, which has been accepted as a Rapid Oral presentation, will be presented by research scientist Mohamed Derbala, M.D., and is recognized as one of the SITC TOP 100 abstracts, emphasizing its potential impact in immunotherapy research.

Immunotherapy, especially immune checkpoint inhibitors like pembrolizumab, has revolutionized cancer treatment. However, the response to this therapy varies among patients, particularly in rare tumor types where treatment options and data are scarce. The study, led by principal investigator Dr. Aung Naing, professor of Investigational Cancer Therapeutics at MD Anderson, utilized Lunit's AI-powered whole-slide image analyzer, Lunit SCOPE IO®, to evaluate tumor microenvironment features in pre-treatment and on-treatment biopsies from patients with rare tumors undergoing pembrolizumab therapy. The study examined over 500 slides from more than 10 different rare tumor types.

The findings reveal that Lunit SCOPE IO can effectively identify specific patterns in tumor samples that correlate with improved treatment outcomes. The study demonstrated that patients whose tumor samples showed AI-detected changes in both intratumoral immune cell (intratumoral tumor-infiltrating lymphocyte; iTIL) presence and tumor content were significantly more likely to respond positively to immunotherapy.

Key findings from the study include:
- In certain tumor types, patients with higher pre-treatment iTIL density exhibited a 51% lower risk of disease progression or death, indicating improved progression-free survival (PFS; HR: 0.49).
- Patients with a greater increase in iTIL density during therapy showed a 35% lower risk of disease progression or death (HR: 0.65) and a 41% lower risk of death (improved overall survival, OS; HR: 0.59).
- Patients with a greater decrease in tumor content during therapy had a 49% lower risk of disease progression or death (HR: 0.51) and a 46% lower risk of death (HR: 0.54).
- Notably, patients who experienced both an increase in iTIL density and a decrease in tumor content had significantly better outcomes, with a 68% lower risk of disease progression or death and a 72% lower risk of death.

Brandon Suh, CEO of Lunit, commented, "These findings demonstrate how our AI technology can provide deep insights into the intricate tumor microenvironment in rare cancers, representing a critical advancement in our understanding of rare tumor biology. This study highlights the value of Lunit SCOPE IO in clinical settings, showing its potential to personalize treatment for patients with limited therapeutic options. We believe these advancements underscore the transformative impact AI can have on oncology and patient outcomes."

By enhancing the capabilities of Lunit SCOPE IO, Lunit aims to continue collaborating with leading cancer research institutions to deliver innovative solutions for patients with limited treatment options, ultimately transforming cancer care.

For more details about the study and its findings, visit Lunit's booth at the SITC 2024 Annual Meeting. The abstract titled "Artificial Intelligence-powered assessment of tumor microenvironment in pre-treatment and on-treatment biopsies informs treatment outcomes to pembrolizumab in patients with rare tumors" will be presented on November 9 at 1:08 p.m. in the George R. Brown Convention Center.