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Article: The use of blood biomarkers to predict radiation lung toxicity: A potential strategy to individualize thoracic radiation therapy

TitleThe use of blood biomarkers to predict radiation lung toxicity: A potential strategy to individualize thoracic radiation therapy
Authors
Issue Date2008
Citation
Cancer Control, 2008, v. 15, n. 2, p. 140-150 How to Cite?
AbstractBackground: 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-β1, 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.
Persistent Identifierhttp://hdl.handle.net/10722/266885
ISSN
2023 Impact Factor: 2.5
2023 SCImago Journal Rankings: 0.698

 

DC FieldValueLanguage
dc.contributor.authorKong, Feng Ming-
dc.contributor.authorAo, Xiaoping-
dc.contributor.authorWang, Li-
dc.contributor.authorLawrence, Theodore S.-
dc.date.accessioned2019-01-31T07:19:53Z-
dc.date.available2019-01-31T07:19:53Z-
dc.date.issued2008-
dc.identifier.citationCancer Control, 2008, v. 15, n. 2, p. 140-150-
dc.identifier.issn1073-2748-
dc.identifier.urihttp://hdl.handle.net/10722/266885-
dc.description.abstractBackground: 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-β1, 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.-
dc.languageeng-
dc.relation.ispartofCancer Control-
dc.titleThe use of blood biomarkers to predict radiation lung toxicity: A potential strategy to individualize thoracic radiation therapy-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1177/107327480801500206-
dc.identifier.pmid18376381-
dc.identifier.scopuseid_2-s2.0-49649100905-
dc.identifier.volume15-
dc.identifier.issue2-
dc.identifier.spage140-
dc.identifier.epage150-
dc.identifier.eissn1526-2359-
dc.identifier.issnl1073-2748-

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