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AI Shows Promise in Predicting Immunotherapy Response for Rare Cancer Patients, Lunit Reveals at SITC 2024

• By John K. Waters
• 11/18/2024

Lunit a leading AI-powered cancer diagnostics and therapeutics company, unveiled research at the Society for Immunotherapy of Cancer (SITC) 2024 Annual Meeting showcasing the potential of its AI technology to predict immunotherapy outcomes for patients with rare cancers. Conducted in collaboration with The University of Texas MD Anderson Cancer Center, the study highlights the transformative role AI could play in personalizing treatment for patients with limited options.

The research, led by Dr. Aung Naing of MD Anderson, utilized Lunit's AI-driven whole-slide image analyzer, Lunit SCOPE IO, to examine tumor microenvironment dynamics in more than 500 biopsy slides from rare tumor patients receiving pembrolizumab, a leading immune checkpoint inhibitor. Accepted as a Rapid Oral presentation and recognized among SITC's TOP 100 abstracts, the study underscores the growing impact of AI in advancing immunotherapy.

The study focused on rare tumor types where treatment data is limited, offering new hope for improved outcomes. Results showed that Lunit SCOPE IO identified specific immune and tumor-related patterns correlating with better responses to pembrolizumab. Key findings include:

• Improved Progression-Free Survival (PFS): Patients with higher pre-treatment tumor-infiltrating lymphocyte (iTIL) density experienced a 51% lower risk of disease progression or death (HR: 0.49).

• Enhanced Overall Survival (OS): Increased iTIL density in on-treatment biopsies resulted in a 35% reduction in disease progression risk (HR: 0.65) and a 41% lower risk of death (HR: 0.59).

• Tumor Content Analysis: Patients showing greater tumor content reduction at on-treatment biopsy had a 49% lower progression risk (HR: 0.51) and a 46% lower mortality risk (HR: 0.54).

• Combination Effects: Those experiencing both increased iTIL density and reduced tumor content had the most significant benefits, with a 68% lower progression risk and a 72% lower mortality risk.

"These findings provide critical insights into the challenging tumor microenvironment of rare cancers, demonstrating how AI can personalize and optimize treatment," said Brandon Suh, CEO of Lunit, in a statement.

Immunotherapy has emerged as a revolutionary treatment in oncology, but its efficacy varies widely among patients, particularly in rare cancers with limited therapeutic data. By harnessing the advanced analytical capabilities of Lunit SCOPE IO, the study demonstrated the potential for AI to address this challenge, offering a new level of precision in predicting treatment outcomes.

"This research underscores our mission to harness AI for meaningful advancements in oncology," Suh added. "We are committed to delivering innovative solutions that transform cancer care, especially for patients with limited options."