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2006 Abstracts: Towards the Molecular Characterization of Disease: Comparison of Molecular and Histological Analysis of Esophageal Epithelia
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Towards the Molecular Characterization of Disease: Comparison of Molecular and Histological Analysis of Esophageal Epithelia
Daniel Vallbohmer1, Paul Marjoram2, Hidekazu Kuramochi3, Daisuke Shimizu3, Hsuan Jung2, Steve R. DeMeester1, Daniel Oh1, Parakrama T. Chandrasoma4, Kathleen D. Danenberg5, Tom R. DeMeester1, Peter V. Danenberg3, Jeffrey H. Peters6; 1Department of Surgery, University of Southern California, Los Angeles, CA; 2Department of Preventive Medicine, University of Southern California, Los Angeles, CA; 3Department of Biochemistry and Molecular Biology, University of Southern California, Los Angeles, CA; 4Department of Pathology, University of Southern California, Los Angeles, CA; 5Response Genetics, Inc., Los Angeles, CA; 6Department of Surgery, University of Rochester, Rochester, NY

Background: Reliable quantification of gene expression offers the possibility of more accurate and prognostically relevant characterization of tissues than potentially subjective interpretations of histopathologists. The aim of this study was to evaluate the feasibility of molecular characterization of normal and pathologic esophageal epithelia. Therefore we measured the expression of 18 selected genes and compared them to histological features in a spectrum of esophageal disease. Methods: Esophageal tissue biopsies from patients with foregut symptoms were laser-capture microdissected and the expression levels of 18 selected genes were measured by QRT-PCR (Taqman®). Linear discriminant analysis, which uses combinations of genes to distinguish between histological groups, was performed to compare gene expression and the following 5 histological groups: 1) normal squamous epithelium, (n=32); 2) reflux-esophagitis, (n=13); 3) non-dysplastic Barrett’s, (n=17); 4) dysplastic Barrett’s, (n=10); 5) adenocarcinoma, (n=22). Results: A panel of 7 genes had 90-94% predictive power to distinguish non-dysplastic and dysplastic Barrett’s esophagus. Clustering analysis revealed structure in gene expression values even in the absence of histology. Expression levels in 17 genes differed significantly across histological groups. Classification based on gene expression agreed with histopathological assessment in the following percentage of cases: normal squamous epithelium =53%, reflux-esophagitis =31%, non-dysplastic Barrett’s =76%, dysplastic Barrett’s=40% and adenocarcinoma =59%. Interestingly, predictive power improved markedly when inflammatory and dysplastic tissues were removed (77%-94%) [Table]. Conclusion: Gene expression classification agrees well with histopathological examination. When differences occur, it is unclear whether this effect is due to intra-observer variability in pathological diagnosis or to a genuine difference between gene expression and histopathology.
Linear discriminant analysis for the three histological groups normal squamous epithelium, non-dysplastic Barrett’s and esophageal adenocarcinoma using the full panel of genes

 

Genetic Prediction Group

 

 

 

Squamous Epithelium

Non-dysplastic Barrett’s

Adenocarcinoma

Predictive Power [%]

Actual histologic group

Squamous Epithelium

30

1

1

94

 

Non-dysplastic Barrett’s

0

15

2

88

 

Adenocarcinoma

2

3

17

77


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