BACKGROUND: Radiation-induced lung toxicity (RILT) is an important dose-limiting toxicity during thoracic radiotherapy. Early prediction of radiation lung toxicity will allow physicians to determine a customized treatment regimen for each patient and deliver a radiation dose tailored to that individual's normal tissue sensitivity profile rather than to the average tolerance of the whole population. METHODS: This review focuses on blood biomarkers in predicting radiation-induced lung toxicity. We searched the literature for data associated with cytokines, and we review the updates of proteomic and genetic polymorphisms in radiation lung toxicity. RESULTS: Studies from single institutions have demonstrated the significant values of cytokines such as TGF-beta1, IL-6, KL-6, surfactant proteins, and IL-1ra on predicting RILT. The majority of studies focus on the values prior to and at the end of radiation therapy. There is limited data from proteomics and specific genomic single nucleotide polymorphism studies that target individualized radiation therapy for patients with lung cancer. CONCLUSIONS: Biomarkers or models that can accurately predict radiation-induced lung damage at an early stage, before completion of chemoradiation, would allow physicians to monitor and customize remaining treatment for each patient.
BACKGROUND: Radiation-induced lung toxicity (RILT) is an important dose-limiting toxicity during thoracic radiotherapy. Early prediction of radiation lung toxicity will allow physicians to determine a customized treatment regimen for each patient and deliver a radiation dose tailored to that individual's normal tissue sensitivity profile rather than to the average tolerance of the whole population. METHODS: This review focuses on blood biomarkers in predicting radiation-induced lung toxicity. We searched the literature for data associated with cytokines, and we review the updates of proteomic and genetic polymorphisms in radiation lung toxicity. RESULTS: Studies from single institutions have demonstrated the significant values of cytokines such as TGF-beta1, IL-6, KL-6, surfactant proteins, and IL-1ra on predicting RILT. The majority of studies focus on the values prior to and at the end of radiation therapy. There is limited data from proteomics and specific genomic single nucleotide polymorphism studies that target individualized radiation therapy for patients with lung cancer. CONCLUSIONS: Biomarkers or models that can accurately predict radiation-induced lung damage at an early stage, before completion of chemoradiation, would allow physicians to monitor and customize remaining treatment for each patient.
Authors: Xiaoxiang Guan; Erich M Sturgis; Dapeng Lei; Zhensheng Liu; Kristina R Dahlstrom; Qingyi Wei; Guojun Li Journal: Clin Cancer Res Date: 2010-02-23 Impact factor: 12.531
Authors: Dirk De Ruysscher; Jianyue Jin; Tim Lautenschlaeger; Jin-Xiong She; Zhongxing Liao; Feng-Ming Spring Kong Journal: Transl Lung Cancer Res Date: 2017-12