Patient-derived organoids (PDO) are based on advanced three-dimensional (3D) culture technology and closely resemble original patient tumors. Organoid research has been an emerging field in the past decade since they have the potential to provide better cancer drug screening. Moreover, they can be used to predict response to radiotherapy and to understand mechanisms of resistance.
There are challenges facing the routine use of PDO in precision radiation oncology. Some of these include tissue collecting for PDOs, storage of tissues, calibration of PDO models for clinical decision-making, time taken to establish individual patient-derived models, and the high cost. Despite these drawbacks, PDOs have tremendous potential for discovering novel drugs or optimizing combined radiation therapies to improve outcomes and reduce toxicity for cancer patients. Further advancements in PDO technology would allow the PDO models to be incorporated in mainstream cancer diagnosis and therapy.
The goal of this Research Topic is to further understanding of the use of PDOs in radiotherapy . We welcome Original Research and Review Articles that focus on the following themes:
- The use of PDOs to predict response to radiotherapy and combined radiotherapies
- Using PDOs to predict resistance to radiotherapy and the understand resistance mechanisms
- Reducing toxicity from radiotherapy using PDOs.
Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) will not be accepted in any of the sections of Frontiers in Oncology.
Patient-derived organoids (PDO) are based on advanced three-dimensional (3D) culture technology and closely resemble original patient tumors. Organoid research has been an emerging field in the past decade since they have the potential to provide better cancer drug screening. Moreover, they can be used to predict response to radiotherapy and to understand mechanisms of resistance.
There are challenges facing the routine use of PDO in precision radiation oncology. Some of these include tissue collecting for PDOs, storage of tissues, calibration of PDO models for clinical decision-making, time taken to establish individual patient-derived models, and the high cost. Despite these drawbacks, PDOs have tremendous potential for discovering novel drugs or optimizing combined radiation therapies to improve outcomes and reduce toxicity for cancer patients. Further advancements in PDO technology would allow the PDO models to be incorporated in mainstream cancer diagnosis and therapy.
The goal of this Research Topic is to further understanding of the use of PDOs in radiotherapy . We welcome Original Research and Review Articles that focus on the following themes:
- The use of PDOs to predict response to radiotherapy and combined radiotherapies
- Using PDOs to predict resistance to radiotherapy and the understand resistance mechanisms
- Reducing toxicity from radiotherapy using PDOs.
Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) will not be accepted in any of the sections of Frontiers in Oncology.