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Plasma metabolite biomarkers predictive of radiation induced cardiotoxicity.

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Citation: Radiotherapy & Oncology. 2020 Apr 20PMID: 32360032Institution: MedStar Heart & Vascular InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: IN PROCESS -- NOT YET INDEXEDYear: 2020 ISSN:

0167-8140

Name of journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and OncologyAbstract: CONCLUSION: Herein, we report the feasibility of developing a metabolomics-based biomarker panel that is associated with adverse outcomes of cardiac function in patients who received RT for the treatment of esophageal cancer. Copyright (c) 2020 Elsevier B.V. All rights reserved.METHODS: We analyzed plasma and left ventricle heart tissue samples collected from a cohort of male Sprague Dawley (SD) rats that were either sham irradiated or received fractionated doses (9 Gy per day x 5 days) of targeted X-ray radiation to the heart. Metabolomic and lipidomic analyses were utilized as a correlative approach for delineation of novel biomarkers associated with radiation-induced cardiac toxicity. Additionally, we used high-resolution mass spectrometry to examine the metabolomic profiles of plasma samples obtained from patients receiving high dose thoracic RT for esophageal cancer.PURPOSE: Although advancements in cancer treatments using radiation therapy (RT) have led to improved outcomes, radiation-induced heart disease (RIHD) remains a significant source of morbidity and mortality in survivors of cancers in the chest. Currently, there are no diagnostic tests in clinical use due to a lack of understanding of the natural history and mechanisms of RIHD development. Few studies have examined the utility of using metabolomics to prospectively identify cancer survivors who are at risk of developing cardiotoxicity.RESULTS: Metabolic alterations in the rat model and patient plasma profiles, showed commonalities of radiation response that included steroid hormone biosynthesis and vitamin E metabolism. Alterations in patient plasma profiles were used to develop classification algorithms predictive of patients at risk of developing RIHD.All authors: Ballew EA, Barac A, Boerma M, Cheema AK, Girgis M, Jayatilake M, Li Y, Srichai MB, Sridharan V, Unger K, Yeh CFiscal year: FY2020Digital Object Identifier:

https://dx.doi.org/10.1016/j.radonc.2020.04.018

Date added to catalog: 2020-07-09

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Title notes ( 5 )

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Journal Article	MedStar Authors Catalog	Article	32360032	Available		32360032

CONCLUSION: Herein, we report the feasibility of developing a metabolomics-based biomarker panel that is associated with adverse outcomes of cardiac function in patients who received RT for the treatment of esophageal cancer. Copyright (c) 2020 Elsevier B.V. All rights reserved.

METHODS: We analyzed plasma and left ventricle heart tissue samples collected from a cohort of male Sprague Dawley (SD) rats that were either sham irradiated or received fractionated doses (9 Gy per day x 5 days) of targeted X-ray radiation to the heart. Metabolomic and lipidomic analyses were utilized as a correlative approach for delineation of novel biomarkers associated with radiation-induced cardiac toxicity. Additionally, we used high-resolution mass spectrometry to examine the metabolomic profiles of plasma samples obtained from patients receiving high dose thoracic RT for esophageal cancer.

PURPOSE: Although advancements in cancer treatments using radiation therapy (RT) have led to improved outcomes, radiation-induced heart disease (RIHD) remains a significant source of morbidity and mortality in survivors of cancers in the chest. Currently, there are no diagnostic tests in clinical use due to a lack of understanding of the natural history and mechanisms of RIHD development. Few studies have examined the utility of using metabolomics to prospectively identify cancer survivors who are at risk of developing cardiotoxicity.

RESULTS: Metabolic alterations in the rat model and patient plasma profiles, showed commonalities of radiation response that included steroid hormone biosynthesis and vitamin E metabolism. Alterations in patient plasma profiles were used to develop classification algorithms predictive of patients at risk of developing RIHD.

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