Background: The effectiveness of radiotherapy for pancreatic cancer is debated. Patient-derived organoids (PDOs) already mimicked clinical radiation response in other cancer types, which could be valuable in pancreatic cancer as well. This study aimed to investigate whether PDOs can be used to model RT response in pancreatic cancer and to explore the presence of a dose-response correlation.
Methods: PDOs derived from two pancreatic cancer patients (HUB-08-B2-022A and HUB-08-B2-026B) were irradiated with doses ranging from 0 to 40 Gray. Viability assessments were conducted after seven and 10 days by measuring ATP-levels. Results were normalized, defining the viability at 0 Gray as 100 % and an absolute viability of 0 as 0 %. The relative area under the curve (rAUC) was calculated (0 = total sensitivity, 1 = total resistance).
Results: With a readout time of seven days, both HUB-08-B2-022A and HUB-08-B2-026B exhibited viability above 50 % at the highest dose of 12 Gy (rAUC of 0.79 and 0.69, respectively). With a readout time of 10 days, both PDOs showed a dose-response relation although HUB-08-B2-022A was more sensitive than HUB-08-B2-026B (rAUC of 0.37 and 0.51, respectively). Increasing the radiation dose to 40 Gy did not further affect viability, but the dose-response relation remained present (rAUC of 0.13 and 0.26, respectively). In the final experiment with a readout time of 10 days and a maximum dose of 14 Gy, the dose-response correlation was paramount in both PDOs (rAUC 0.28 and 0.45, respectively), with HUB-08-B2-022A being most sensitive.
Conclusions: In this setup, both pancreatic cancer PDOs showed an irradiation dose-response correlation. These preliminary findings suggest that pancreatic cancer PDOs are suitable for assessing radiation response . Further experiments are needed to eventually simulate treatment responses to personalized treatment strategies.
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http://dx.doi.org/10.1016/j.ctro.2024.100829 | DOI Listing |
Mol Ther
January 2025
Department of Hematology and Oncology, Shenzhen University General Hospital, International Cancer Center, Shenzhen Key Laboratory, Hematology Institution of Shenzhen University, Shenzhen University Health Science Center, Shenzhen University, Shenzhen, China; Shenzhen University-Haoshi Cell Therapy Institute, Shenzhen, China. Electronic address:
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College of Pharmacy and Health Sciences, St. John's University, Queens, NY 11439, USA.
In the original publication [...
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Hybrid Technology Hub, Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, 0372 Oslo, Norway.
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Department of General, Visceral and Transplantation Surgery, University of Heidelberg, 69120 Heidelberg, Germany.
Despite the significant advancements of liver surgery in the last few decades, the survival rate of patients with liver and pancreatic cancers has improved by only 10% in 30 years. Precision medicine offers a patient-centered approach, which, when combined with machine learning, could enhance decision making and treatment outcomes in surgical management of ihCC. This study aims to develop a decision support model to optimize treatment strategies for patients with ihCC, a prevalent primary liver cancer.
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