Cell type-dependent gene transcription profile in a three-dimensional human skin tissue model exposed to low doses of ionizing radiation: Implications for medical exposures
Claere von Neubeck
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorHarish Shankaran
Department of Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorNorman J. Karin
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorPaula M. Kauer
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorWilliam B. Chrisler
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorXihai Wang
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorR. Joe Robinson
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorKatrina M. Waters
Department of Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorSusan C. Tilton
Department of Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorCorresponding Author
Marianne B. Sowa
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Pacific Northwest National Laboratory, P.O. Box 999, MS J4-02, Richland, WA 99352, USASearch for more papers by this authorClaere von Neubeck
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorHarish Shankaran
Department of Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorNorman J. Karin
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorPaula M. Kauer
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorWilliam B. Chrisler
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorXihai Wang
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorR. Joe Robinson
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorKatrina M. Waters
Department of Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorSusan C. Tilton
Department of Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington
Search for more papers by this authorCorresponding Author
Marianne B. Sowa
Department of Systems Toxicology, Pacific Northwest National Laboratory, Richland, Washington
Pacific Northwest National Laboratory, P.O. Box 999, MS J4-02, Richland, WA 99352, USASearch for more papers by this authorAbstract
The concern over possible health risks from exposures to low doses of ionizing radiation has been driven largely by the increase in medical exposures, the routine implementation of X-ray backscatter devices for airport security screening, and, most recently, the nuclear incident in Japan. Because of a paucity of direct epidemiological data at very low doses, cancer risk must be estimated from high dose exposure scenarios. However, there is increasing evidence that low and high dose exposures result in different signaling events and may have different response mechanisms than higher doses. We have examined the radiation-induced temporal response after exposure to 10 cGy of an in vitro three dimensional (3D) human skin tissue model using microarray-based transcriptional profiling. Cell type-specific analysis showed significant changes in gene expression with the levels of >1,400 genes altered in the dermis and >400 genes regulated in the epidermis. The two cell layers rarely exhibited overlapping responses at the mRNA level. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) measurements validated the microarray data in both regulation direction and value. Key pathways identified relate to cell cycle regulation, immune responses, hypoxia, reactive oxygen signaling, and DNA damage repair. The proliferation status as well as the expression of PCNA was examined in histological samples. We discuss in particular the role of proliferation, emphasizing how the disregulation of cellular signaling in normal tissue may impact progression toward radiation-induced secondary diseases. Environ. Mol. Mutagen. 2012. © 2012 Wiley Periodicals, Inc.
Supporting Information
Additional Supporting Information may be found in the online version of this article.
Filename | Description |
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EM_21682_sm_SuppFile1.xlsx9 MB | Supporting Information |
EM_21682_sm_SuppFile2.xlsx2.5 MB | Supporting Information |
EM_21682_sm_SuppTab1.doc71.5 KB | Supporting Information Table 1. Enrichment of annotation terms in up- and down-regulated probes in the dermis. Functional enrichment analysis was performed using DAVID as detailed in Methods. aTotal number of statistically significant probes in the up/down regulated lists at the indicated time point. bActual annotation term from DAVID or a representative term for an annotation cluster with geometric mean (GM) p value ≤ 0.01. The latter are highlighted using an asterisk (*) next to the term. cThe minimum p value is presented for annotation clusters with GM p value ≤ 0.01. The actual p value is presented for all other individual terms (terms with p ≤ 0.01 that belong to clusters with GM p value > 0.01, or orphan terms that are not part of any of the annotation clusters). |
EM_21682_sm_SuppTab2.doc50 KB | Supporting Information Table 2. Enrichment of annotation terms in up- and down-regulated probes in the epidermis. Functional enrichment analysis was performed using DAVID as detailed in Methods. See Sup. Table 1 for description of terminology. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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