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Gene expression signature in mouse thyroid tissue after (131)I and (211)At exposure

BACKGROUND: (131)I and (211)At are used in nuclear medicine and accumulate in the thyroid gland and may impact normal thyroid function. The aim of this study was to determine transcriptional profile variations, assess the impact on cellular activity, and identify genes with biomarker properties in t...

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Detalles Bibliográficos
Autores principales: Rudqvist, Nils, Spetz, Johan, Schüler, Emil, Langen, Britta, Parris, Toshima Z., Helou, Khalil, Forssell-Aronsson, Eva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615992/
https://www.ncbi.nlm.nih.gov/pubmed/26492889
http://dx.doi.org/10.1186/s13550-015-0137-8
Descripción
Sumario:BACKGROUND: (131)I and (211)At are used in nuclear medicine and accumulate in the thyroid gland and may impact normal thyroid function. The aim of this study was to determine transcriptional profile variations, assess the impact on cellular activity, and identify genes with biomarker properties in thyroid tissue after (131)I and (211)At administration in mice. METHODS: To further investigate thyroid tissue transcriptional responses to (131)I and (211)At administration, we generated a new transcriptional dataset that includes re-evaluated raw intensity values from our previous (131)I and (211)At studies. Differential transcriptional profiles were identified by comparing treated and mock-treated samples using Nexus Expression 3.0 software. Further data analysis was performed using R/Bioconductor and IPA. RESULTS: A total of 1144 genes were regulated. Hierarchical clustering subdivided the groups into two clusters containing the lowest and highest absorbed dose levels, respectively, and revealed similar transcriptional regulation patterns for many kallikrein-related genes. Twenty-seven of the 1144 genes were recurrently regulated after (131)I and (211)At exposure and divided into six clusters. Several signalling pathways were affected, including calcium, integrin-linked kinase, and thyroid cancer signalling, and the peroxisomal proliferator-activated receptor network. CONCLUSIONS: Substantial changes in transcriptional regulation were shown in (131)I and (211)At-treated samples, and 27 genes were identified as potential biomarkers for (131)I and (211)At exposure. Clustering revealed distinct differences between transcriptional profiles of both similar and different exposures, demonstrating the necessity for better understanding of radiation-induced effects on cellular activity. Additionally, ionizing radiation-induced changes in kallikrein gene expression and identified canonical pathways should be further assessed.