U227443.pdf (33.8 MB)
Download file

Experimental models of stem cell commitment and human disease

Download (33.8 MB)
thesis
posted on 15.12.2014, 10:33 by Lea-Anne Harrison
The aim of this thesis was to test the hypothesis that stem cells and their progenitors are important in metaplasia in the gastrointestinal (GI) tract across species. Immunohistochemistry (IHC) was employed to identify and analyse potential stem cell markers in human tissue. Putative stem cell location was mapped using a thymidine analogue to label slow cycling cells in human tissue. Zebrafish were investigated to examine deoxycholic acid (DCA), as a model for bile acid stimulation on stem cell fate, and whole animal histology was evaluated. Finally, the liver fatty acid binding protein (L-FABP) promoter was used to direct placental cadherin (P-cadherin) expression in the GI tract in a transgenic murine model. IHC analysis showed P-cadherin was expressed in the putative stem cell compartment in human oesophageal and Barrett's mucosa. Iododeoxyuridine (IUdR) labelling identified the stem cell compartment in human tissue. Double labelling, using IUdR with Ki-67 further identified a small stem cell side population in the basal compartments. The zebrafish model showed a mucin cell phenotype in the DCA stimulated animals, which was absent from controls. In the transgenic mouse model, although neoexpression of P-cadherin was demonstrated in the small bowel by RT-PCR, there was no obvious phenotype observed. However, there was an increase in stem cell division in the small bowel. In conclusion, the data generated in this thesis support the hypothesis that stem cells play a pivotal role in human disease. It would appear that the previously undefined stem cell compartment can now be elucidated and the P-cadherin upregulation is a feature of this location.

History

Date of award

01/01/2007

Author affiliation

Cancer Studies and Molecular Medicine

Awarding institution

University of Leicester

Qualification level

Doctoral

Qualification name

PhD

Language

en

Usage metrics

Categories

Keywords

Exports