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Published in: Journal of Cancer Research and Clinical Oncology 5/2003

01-05-2003 | Original Paper

Classification of Dukes' B and C colorectal cancers using expression arrays

Authors: Casper Møller Frederiksen, Steen Knudsen, Søren Laurberg, Torben F. Ørntoft

Published in: Journal of Cancer Research and Clinical Oncology | Issue 5/2003

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Abstract

Purpose

Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene expression microarrays could be used to classify colorectal tumors.

Methods

We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each of the Dukes' stages A, B, C, and D. Expression data were filtered based on either covariance or a selection of the most significantly varying genes between tumor stages.

Results

A nearest neighbor classifier was used to classify normal, and Dukes' B and C samples with less than 20% error, whereas Dukes' A and D could not be classified correctly. A number of interesting gene clusters showed a discriminating difference between Dukes' B and C samples. These included mitochondrial genes, stromal remodeling genes, and genes related to cell adhesion.

Conclusion

Molecular classification based on gene expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays.
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Metadata
Title
Classification of Dukes' B and C colorectal cancers using expression arrays
Authors
Casper Møller Frederiksen
Steen Knudsen
Søren Laurberg
Torben F. Ørntoft
Publication date
01-05-2003
Publisher
Springer-Verlag
Published in
Journal of Cancer Research and Clinical Oncology / Issue 5/2003
Print ISSN: 0171-5216
Electronic ISSN: 1432-1335
DOI
https://doi.org/10.1007/s00432-003-0434-x

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