-BostonGene, developer of the leading AI foundation model for cancer and the immune system, and Kyoto University, a research institution known for its groundbreaking advancements in medicine and science announced today a research collaboration to develop advanced biological signatures to enhance targeted treatment strategies for patients with esophageal squamous cell carcinoma (ESCC).

"Through this collaboration, we will apply cutting-edge AI-powered analytics to clinical data, enabling us to identify biomarkers that can directly inform treatment decisions and improve patient outcomes."

This research will leverage BostonGene’s AI-powered, multi-scale, omnimodal platform to analyze tumor molecular profiles and assess their correlation with response to a novel immune checkpoint inhibitor (ICI) and chemoradiotherapy (CRT) combination therapy. The study builds on the NOBEL trial, an investigator-initiated clinical study led by Dr. Manabu Muto of Kyoto University, by integrating genomic and transcriptomic profiling from ESCC patients to identify immune-related biomarkers that drive drug development, optimize clinical trial design and enable more accurate patient stratification.

As part of the collaboration, Kyoto University will provide clinical samples and patient data and BostonGene will apply its AI-powered molecular analytics to uncover key biological pathways and associated biomarkers influencing treatment response.

"This collaboration will generate actionable insights into the tumor microenvironment and immune landscape of esophageal cancer," said Yukimasa Shiotsu, PhD, President of BostonGene Japan. "Combining Kyoto University’s clinical expertise and BostonGene’s AI-powered analytics, we will refine and advance precision treatment strategies for ESCC patients."

"Understanding the molecular and immune characteristics of ESCC is essential for developing more effective treatment strategies," said Dr. Manabu Muto, Professor at Kyoto University and Principal Investigator of the NOBEL trial. "Through this collaboration, we will apply cutting-edge AI-powered analytics to clinical data, enabling us to identify biomarkers that can directly inform treatment decisions and improve patient outcomes."