UM’s latest breakthrough identifies high-risk liver cancer subtype and reveals AI-guided precision treatment strategy

MACAU, October 14 - A team led by Associate Professor Joong Sup Shim in the Faculty of Medicine (FMD) at the University of Macau (UM), in collaboration with researchers from Asan Medical Center, Pohang University of Science and Technology (POSTECH), and Hanyang University College of Medicine in South Korea, Harvard Medical School in the United States, and other international partners, has made a breakthrough in liver cancer research. The team revealed that the inactivation of the tumour suppressor gene RB1 is associated with an aggressive form of hepatocellular carcinoma (HCC). The researchers also developed an artificial intelligence (AI)-based tool to rapidly identify patients with RB1 inactivation and discovered that their tumours respond particularly well to a specific combination treatment. These findings offer a new direction for precision medicine in liver cancer. The study has been published in Signal Transduction and Targeted Therapy (STTT), a leading international journal in biomedical sciences.

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer and a major cause of cancer-related deaths worldwide. It is particularly common in East Asian countries, including China, Mongolia, and South Korea, which together account for up to half of global HCC cases. Despite recent advances in systemic therapies, durable responses remain limited, and many patients lack actionable biomarkers to guide personalised treatment. RB1 is a well-known tumour suppressor that plays a central role in cell-cycle regulation and genomic stability. However, the biological and clinical consequences of complete (biallelic) RB1 inactivation in HCC have remained unclear. Understanding how RB1-deficient tumours develop and progress is therefore essential for improving patient outcomes.

Through multi-omics analysis of large HCC patient cohorts, the research team found that approximately 14.6% of liver cancer patients exhibit biallelic RB1 loss, meaning both copies of the RB1 gene are deleted or inactivated. These patients showed poor tumour differentiation, rapid disease progression, and a 3.32-fold higher risk of death compared with other HCC patients, establishing biallelic RB1 loss as a strong and independent prognostic factor for HCC. To facilitate clinical application without relying on costly genomic sequencing, the team also developed a deep-learning-based pathology AI model capable of identifying this high-risk group directly from routine hematoxylin and eosin (H&E)-stained slides. This innovation enables clinicians to rapidly and accurately detect RB1-deficient tumours using standard diagnostic procedures.

The discovery of this high-risk subtype prompted the team to conduct large-scale drug screening to identify potential therapeutic vulnerabilities. The researchers found that RB1-deficient liver cancer cells exhibit synthetic lethal sensitivity to inhibitors targeting mitotic regulators (AURKA, PLK1, and KSP inhibitors) and DNA damage response pathways (PARP inhibitors). In cell and animal models, combination therapy using mitotic inhibitors and PARP inhibitors produced strong anti-tumour synergy without causing liver toxicity or other notable side effects. The findings suggest a powerful and selective treatment strategy for HCC patients with biallelic RB1 loss. Overall, the study shows that HCC with biallelic RB1 loss is highly proactive in its malignant progression and represents a clinically actionable subtype with clear diagnostic and therapeutic avenues. According to the research team, the study marks an important milestone, as it establishes a full-cycle framework for addressing a previously difficult-to-treat, high-risk subgroup of liver cancer—from discovering new therapeutic targets through multi-omics analysis, to developing AI-based pathological diagnostics, and ultimately proposing a powerful, personalised combination therapy strategy for patients who have shown limited response to standard treatments.

Joong Sup Shim, as well as Ju Hyun Shim and Chang Ohk Sung from Asan Medical Center, and Associate Professor Sang Hyun Park from POSTECH are the co-corresponding authors of this study. Associate Professor Jihyun An from Hanyang University College of Medicine, postdoctoral fellow Wonkyung Kim from Asan Medical Center, UM FMD PhD student Xiumei Zhang, research fellow Philip Chikontwe from Harvard Medical School, and PhD student Jin-Sung Ju from Asan Medical Center are the co-first authors. Other contributors include researchers from UM, Asan Medical Center, Ajou University, and POSTECH. The research project was funded by the University of Macau (Grant No.: MYRG-GRG2024-00056-FHS), the Science and Technology Development Fund of the Macao SAR (Grant No.: 0139/2024/AFJ), and the Shenzhen Science and Technology Innovation Commission (Grant No.: SGDX20220530111004031). The full version of the research article can be viewed at: https://doi.org/10.1038/s41392-026-02815-0.

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