Clinical puzzle: Barrett's oesophagus

Dis Model Mech. 2008 Jul-Aug;1(1):26-31. doi: 10.1242/dmm.000273.

Abstract

The incidence of oesophageal adenocarcinoma has increased dramatically in the Western world over the past two decades. Owing to its dismal 5-year prognosis in advanced stages, early diagnosis is required in order to improve survival rates. Barrett's oesophagus (Barrett's) has been recognised as a pre-cancerous condition generally associated with chronic and severe gastro-oesophageal reflux disease (GORD). Barrett's is defined as the substitution of the normal stratified squamous epithelium of the oesophagus with a columnar cell lining with intestinal-type differentiation; a phenomenon commonly referred to as intestinal metaplasia. Clinical challenges include finding cost-effective ways to identify patients with Barrett's, stratifying them according to their cancer risk and improving the diagnostic potential of endoscopic sampling. Research has generally focused on identifying tissue biomarkers to predict cancer risk in these patients. The oesophagus is easily accessible, making it possible to work with human samples, but most studies have been retrospective and underpowered. Endoscopic surveillance programmes are problematic due to sampling bias and the subjective grading of dysplasia. The lack of an animal model has hampered studies to elucidate markers of the transition from Barrett's to cancer and to test potential therapeutics. However, a number of in vitro model systems are ripe for further development into more physiologically complete systems.

MeSH terms

  • Adenocarcinoma / diagnosis
  • Adenocarcinoma / pathology*
  • Animals
  • Barrett Esophagus / diagnosis
  • Barrett Esophagus / genetics
  • Barrett Esophagus / pathology*
  • Biomarkers / analysis
  • Cell Transformation, Neoplastic
  • Disease Progression
  • Early Diagnosis
  • Esophageal Neoplasms / diagnosis
  • Esophageal Neoplasms / pathology*
  • Genetic Predisposition to Disease
  • Humans
  • Models, Biological

Substances

  • Biomarkers