Identification of stable housekeeping genes in response to ionizing radiation in cancer research

Housekeeping genes (HKGs) are essential for basic maintenance of a variety of cellular processes. They ideally maintain uniform expression independent of experimental conditions. However, the effects of ionizing radiation (IR) on HKG expression is unclear. Statistical algorithms, geNorm and Normfind...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Scientific reports 2017-03, Vol.7 (1), p.43763-43763, Article 43763
Hauptverfasser: Iyer, Gopal, Wang, Albert R., Brennan, Sean R., Bourgeois, Shay, Armstrong, Eric, Shah, Pari, Harari, Paul M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Housekeeping genes (HKGs) are essential for basic maintenance of a variety of cellular processes. They ideally maintain uniform expression independent of experimental conditions. However, the effects of ionizing radiation (IR) on HKG expression is unclear. Statistical algorithms, geNorm and Normfinder were used for estimating the stability of HKGs as raw quantification cycle (Cq) values were not a reliable factor for normalization. Head and neck, non-small lung and pancreas cells were exposed to 2, 4 and 6 Gy IR doses and expression of fourteen HKGs was measured at 5 min to 48 h post-irradiation within a given tissue. Paired and single cell line analyses under these experimental conditions identified TATA-Box Binding Protein (TBP) and Importin 8 (IPO8) to be stable in non-small cell lung cancer. In addition to these two genes, Ubiquitin C (UBC) in head and neck cancer and Transferrin receptor (TFRC) and β-Glucuronidase (GUSB) in pancreatic cancer were identified to be stable as well. In summary we present a resource for top ranked five stable HKGs and their transcriptional behavior in commonly used cancer model cell lines and suggest the use of multiple HKGs under radiation treatment conditions is a reliable metric for quantifying gene expression.
ISSN:2045-2322
2045-2322
DOI:10.1038/srep43763