Patient-Derived Organoid Screen Identifies Triple-Drug Combination Against Liver Cancer
核心洞察
Researchers at the University of Basel screened 1,642 compounds across patient-derived hepatocellular carcinoma (搜索) organoids to identify effective drug combinations.
A triple combination of regorafenib, selinexor, and ixazomib slowed tumor growth more effectively than regorafenib alone in mouse models without significant additional toxicity.
The 35-organoid collection, built partly from diagnostic needle biopsies, captures advanced tumors and diverse disease stages previously underrepresented in existing models.
A research team at the University of Basel in Switzerland has identified several promising drug combinations against hepatocellular carcinoma (搜索) (HCC), the most common form of liver cancer (搜索), using a novel collection of patient-derived tumor organoids. The study screened more than 1,600 drug compounds and found that certain two- and three-drug combinations outperformed individual drugs, with one triple combination demonstrating superior tumor control in mouse models.
Liver cancer (搜索) remains difficult to treat partly because tumors vary considerably from one patient to another. Tumors may differ in their biological characteristics, genetic alterations, and underlying causes, all of which can influence how they respond to treatment. Immunotherapy is considered a promising approach, but it does not work for everyone.
Building a Diverse Organoid Collection
To address this biological diversity, the researchers created a collection of 35 tumor organoid lines representing hepatocellular carcinoma (搜索). These organoids consist of living cancer cells grown in three-dimensional structures that retain some of the key characteristics of the original tumors.
An important feature of the model is that several organoids were developed from small tissue samples obtained during diagnostic needle biopsies. This enabled the researchers to represent advanced tumors that have been underrepresented in previous organoid collections.
"Our collection reflects different stages of the disease, as well as liver tumors with various causes," explained Sandro Nuciforo, the study's first author. This variety allowed the team to assess drug effectiveness across a broad range of biological tumor profiles.
Screening 1,642 Compounds
The researchers initially conducted an automated screening of 1,642 compounds across four selected organoid models. The compounds included cancer drugs, experimental molecules, and approved medications used to treat other diseases. Compounds that showed promising activity were subsequently tested across a larger collection of organoids.
Several drugs demonstrated strong anti-tumor activity, prompting the team to investigate combinations of drugs that work through different mechanisms. Some two- and three-drug combinations were more effective than the individual drugs used alone. Several triple-drug combinations also appeared to target cancer cells more selectively, while having a lower impact on non-cancerous liver organoids.
"Rather than focusing on a single vulnerability of the tumor, we combine drugs with different mechanisms of action," said Markus Heim, who led the research team. "This could allow the treatment to remain effective even when the vulnerabilities differ from tumor to tumor."
Promising Results in Mice
The researchers then tested one promising combination—regorafenib, selinexor, and ixazomib—in mice carrying tumors derived from patient-derived organoid models. The three-drug treatment slowed tumor growth more effectively than regorafenib alone, without causing significant additional toxicity in the animal model used in the study.
Study Limitations and Next Steps
The researchers emphasized that the findings remain at the preclinical stage and that further studies are needed before the combination can be evaluated in patients. The organoid models also do not fully reproduce the complex tumor microenvironment, including blood vessels and immune cells.
Overall, the study highlights the potential of patient-derived organoids as a tool for systematically screening large numbers of drugs and identifying combination therapies that account for the substantial biological diversity found in liver cancer (搜索) tumors.