• Collaborative research with Japan’s largest oncology practice shows Lunit SCOPE's potential in predicting clinical outcomes for rectal cancer

  
  

Lunit, a global provider of AI-powered cancer diagnostic solutions, today announced collaboration with the National Cancer Center Hospital East (NCCHE) to evaluate and validate its AI pathology solution for tissue data analysis.

This partnership aims to leverage the capabilities of Lunit SCOPE, an AI-biomarker platform, in analyzing Immunohistochemistry and H&E tissue slide data from various clinical trials, including NCCHE's molecular profiling projects such as SCRUM-Japan MONSTAR-SCREEN. The primary objective is to assess AI's ability to accurately read known biomarkers such as HER2 and PD-L1 and evaluate the performance of emerging biomarkers like immune phenotype, as read by Lunit SCOPE IO, in predicting clinical outcomes in multiple treatment settings.

“Our collaborative research using Lunit's outstanding AI analysis technology has demonstrated that in addition to assisting in pathological diagnosis, a single slide can predict a response based on biological mechanisms. Working with Lunit and the SCRUM project will bring a new approach to cancer treatment,” said the principal investigator of SCRUM-Japan MONSTAR-SCREEN project, Dr. Takayuki Yoshino of the National Cancer Center Hospital East (Kashiwa City, Chiba Prefecture). "We are pleased to collaborate with Lunit and look forward to working towards our goal of leading to further personalized medicine for cancer patients around the world."

This collaboration's first set of findings will be unveiled at the American Society of Clinical Oncology (ASCO) annual meeting. The finding includes the analysis of AI-assessed tumor-infiltrating lymphocyte (TIL) density in the tumor microenvironment of microsatellite stable (MSS) locally advanced rectal cancer (LARC) samples. The study shows a strong correlation between changes in TIL density during preoperative chemoradiotherapy (CRT) and pathologic complete response (pCR) rate of MSS LARC patients. This finding underscores the potential of tumor microenvironment (TME) analysis by Lunit SCOPE IO to predict favorable outcomes.

Lunit and NCCHE remain committed to conducting studies to further validate the findings and to explore AI analysis in additional treatment settings. Additional results and validations from ongoing studies will be shared at future congresses, ensuring transparency and driving further AI-powered tissue data analysis advancements.

"We are delighted to partner with the National Cancer Center Hospital East in the validation of our Lunit SCOPE suite, marking a significant step towards advancing precision oncology and improving optimized patient treatment," said Brandon Suh, CEO of Lunit. "Through this collaboration, we aim to unlock the full potential of Lunit SCOPE to provide an accurate and efficient analysis of tissue slide data. Our goal is to equip clinicians and researchers with powerful tools that can transform oncology practices, drive more informed clinical decision-making and ultimately improve patient outcomes."