By the same authors

From the same journal

From the same journal

Differential transcription factor expression by human epithelial cells of buccal and urothelial derivation

Research output: Contribution to journalArticlepeer-review

Full text download(s)

Published copy (DOI)



Publication details

JournalExperimental cell research
DateAccepted/In press - 25 May 2018
DateE-pub ahead of print - 26 May 2018
DatePublished (current) - 15 Aug 2018
Issue number2
Number of pages11
Pages (from-to)284-294
Early online date26/05/18
Original languageEnglish


Identification of transcription factors expressed by differentiated cells is informative not only of tissue-specific pathways, but to help identify master regulators for cellular reprogramming. If applied, such an approach could generate healthy autologous tissue-specific cells for clinical use where cells from the homologous tissue are unavailable due to disease. Normal human epithelial cells of buccal and urothelial derivation maintained in identical culture conditions that lacked significant instructive or permissive signalling cues were found to display inherent similarities and differences of phenotype. Investigation of transcription factors implicated in driving urothelial-type differentiation revealed buccal epithelial cells to have minimal or absent expression of PPARG, GATA3 and FOXA1 genes. Retroviral overexpression of GATA3 or PPARG1 coding sequences in buccal epithelial cells resulted in nuclear immunolocalisation of the respective proteins, with both transductions also inducing expression of the urothelial differentiation-associated claudin 3 tight junction protein. PPARγ1 overexpression alone entrained expression of nuclear FOXA1 and GATA3 proteins, providing objective evidence of its upstream positioning in a transcription factor network and identifying it as a candidate factor for urothelial-type transdifferentiation or reprogramming.

Bibliographical note

© 2018 The Authors. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations