Liver cancer, the third leading cause of cancer-related deaths worldwide, has a postoperative recurrence rate as high as 70%. Accurately predicting recurrence has long been a critical challenge.

Researchers from the University of Science and Technology of China, led by Sun Cheng, have developed a scoring system named TIMES, which quantifies spatial distribution patterns of immune cells within the tumour microenvironment to assess relapse likelihood.

The system is the world’s first liver cancer recurrence-prediction tool that integrates spatial immune data.

The study demonstrates that immune cell spatial organisation, not just their quantity, determines clinical outcomes. Using liver-cancer tissue samples from 61 patients, the team established a novel method for tumour microenvironment assessment.

The researchers then opened a free online version of TIMES, allowing global users to upload pathological staining images for instant risk evaluation.

Ultimately, they aim to provide a revolutionary decision-making tool to help doctors optimise personalised treatments, especially in resource-limited settings, Sun said, adding that they are actively collaborating with industry partners to standardise clinical applications.