A recent study published in Nature reveals that a Chinese research team has created an artificial intelligence tool capable of predicting liver cancer recurrence risk with 82.2% accuracy. Liver cancer ranks third globally in cancer-related deaths, with a recurrence rate post-surgery as high as 70%. Accurately forecasting recurrence has been a significant challenge.
Led by Sun Cheng from the University of Science and Technology of China, the team developed a scoring system called TIMES. This system evaluates the likelihood of relapse by analyzing spatial distribution patterns of immune cells within the tumor microenvironment. It marks the world’s first liver cancer recurrence prediction tool to integrate spatial immune data. The study underscores that clinical outcomes hinge not only on the quantity but also on the spatial organization of immune cells.
Employing spatial transcriptomics, proteomics, multispectral immunohistochemistry, and AI-driven spatial analysis, the researchers devised a novel approach for assessing the tumor microenvironment. The system was trained using liver cancer tissue samples from 61 patients. The team has also launched a free online version of TIMES, allowing global users to upload pathological staining images for instant risk assessment.
Sun Cheng emphasized that their goal is to furnish a groundbreaking decision-making tool to aid doctors in optimizing personalized treatments, particularly in settings with limited resources. The team is actively collaborating with industry partners to standardize clinical applications of their innovation.
