Radiation-induced lymphopenia (RIL) is a long-known and frequent toxicity of radiotherapy and is the direct consequence of cell death of lymphocytes crossing the radiation field during treatment. In recent years, interest and evidence have been growing for the negative influence of RIL on treatment outcomes and survival of patients with solid tumors. Especially since the rise of immunotherapy, which is largely reliant on vital lymphocytes. Insight into clinical and dosimetric risk factors can help identify patients with an increased risk of RIL and possible management. Methods to mitigate RIL aim to reduce unintentional exposure of the circulating blood pool and secondary lymphoid organs to radiotherapy, with the ultimate goal of improving survival.
The purpose of this Research Topic is to provide an overview of the new insights into the clinical relevance of radiation-induced lymphopenia (RIL) and discuss possibilities to mitigate RIL. Recent advances that can be discussed in this Research Topic include studies on the relationship of RIL with immunotherapy efficacy and survival outcomes for different types of tumors. Other advances include insights into clinical and dosimetric factors that predict the risk and severity of RIL, which can be starting points for lymphopenia mitigation strategies. Examples of RIL mitigation strategies that can be discussed include, hypofractionation, applying dose constraints to lymphoid-rich organs, or the reduction of the total irradiated volume by proton therapy, FLASH, PULSAR, or adaptive radiotherapy.
Specific themes to be addressed include:
- Influence of radiation-induced lymphopenia (RIL) on immunotherapy efficacy and survival outcomes.
- Influence of lymphocyte subsets (e.g. CD4, CD8, reg T-cells, B-cells) in RIL on oncologic outcomes.
- Clinical and dosimetric predictors of RIL (e.g. conventional or deep-learning-based prediction models).
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.
Radiation-induced lymphopenia (RIL) is a long-known and frequent toxicity of radiotherapy and is the direct consequence of cell death of lymphocytes crossing the radiation field during treatment. In recent years, interest and evidence have been growing for the negative influence of RIL on treatment outcomes and survival of patients with solid tumors. Especially since the rise of immunotherapy, which is largely reliant on vital lymphocytes. Insight into clinical and dosimetric risk factors can help identify patients with an increased risk of RIL and possible management. Methods to mitigate RIL aim to reduce unintentional exposure of the circulating blood pool and secondary lymphoid organs to radiotherapy, with the ultimate goal of improving survival.
The purpose of this Research Topic is to provide an overview of the new insights into the clinical relevance of radiation-induced lymphopenia (RIL) and discuss possibilities to mitigate RIL. Recent advances that can be discussed in this Research Topic include studies on the relationship of RIL with immunotherapy efficacy and survival outcomes for different types of tumors. Other advances include insights into clinical and dosimetric factors that predict the risk and severity of RIL, which can be starting points for lymphopenia mitigation strategies. Examples of RIL mitigation strategies that can be discussed include, hypofractionation, applying dose constraints to lymphoid-rich organs, or the reduction of the total irradiated volume by proton therapy, FLASH, PULSAR, or adaptive radiotherapy.
Specific themes to be addressed include:
- Influence of radiation-induced lymphopenia (RIL) on immunotherapy efficacy and survival outcomes.
- Influence of lymphocyte subsets (e.g. CD4, CD8, reg T-cells, B-cells) in RIL on oncologic outcomes.
- Clinical and dosimetric predictors of RIL (e.g. conventional or deep-learning-based prediction models).
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.
