Severance team develops 3D organoid to predict pancreatic cancer drug response

A research team at Severance Hospital announced Wednesday that they have successfully created a 3D organoid model using cells from pancreatic cancer patients, which replicates the effects of anticancer drugs while preserving the patients’ genetic characteristics. The hospital said this improved organoid model is expected to enable more accurate prediction of drug efficacy.

The study was led by Professors Bang Seung-min and Leem Ga-lam from the Department of Gastroenterology at Severance Hospital, along with Kim Jin-su, assistant professor in the Department of Internal Medicine at Yonsei University College of Medicine.

The findings were published in the latest issue of Molecular Cancer (IF 27.7), a world-leading journal in cancer research.

Pancreatic cancer remains one of the deadliest forms of cancer, with a five-year survival rate of only about 10 percent despite advances in diagnostics and treatment. Most patients are diagnosed at an advanced stage when surgery is no longer an option and must rely on chemotherapy.

However, no biomarkers currently exist to predict treatment effectiveness, leaving the selection of anticancer drugs solely to physician experience and patient condition. As such, there is an urgent need to develop a model that can accurately forecast individualized treatment responses.

Moreover, due to the limited efficacy of first-line treatments, many guidelines recommend early participation in clinical trials. Yet pancreatic cancer lacks reliable preclinical models that can predict patient-specific responses, making the design of new clinical studies difficult.

Previous efforts to develop pancreatic cancer organoid models aimed at predicting treatment response and testing new drugs faced limitations. Prolonged exposure to growth factors during cultivation often altered the organoids’ original characteristics, reducing prediction accuracy. Additionally, these models could only forecast the response to single agents, not drug combinations.

Using patient-derived pancreatic cancer cell lines accumulated over the past decade, the research team successfully developed a 3D organoid model that reflects patient-specific genetic traits. When treated with the same combinations of anticancer drugs administered to patients, the model produced outcomes that closely matched actual treatment results.

Notably, the team created a platform that maintains organoids without the use of growth factors -- unlike conventional methods -- allowing the preservation of original characteristics even during long-term culture. This advancement is expected to significantly support the design of clinical trials, the development of new drugs, and personalized treatment strategies.

“By developing a model that can accurately predict each patient's response to treatment in advance, we have opened up the possibility of providing optimal anticancer drugs in a personalized manner,” said Professor Bang.

“This research is expected to improve the success rate of clinical trials and dramatically reduce the cost and time required for drug development,” added Professor Leem.