Volume 2 Supplement 1

Second International Symposium on the Molecular Biology of Breast Cancer

Open Access

Studying breast cancer on a genomic scale using DNA microarrays

  • D Botstein1 and
  • PO Brown1
Breast Cancer Research20002(Suppl 1):S.36

https://doi.org/10.1186/bcr196

Published: 12 March 2000

Full text

Genome-wide studies of human gene expression have become possible in recent years because of the availability of most of the sequences of protein-encoding genes. Technology has been developed in our group to obtain and analyze patterns of expression of many thousands of genes at once. We have begun to apply cDNA microarray technology to the study of cancer, focusing on breast cancer. We characterized the variation in patterns of gene expression in a set of 62 surgical specimens of human breast tumors from 40 different patients, using cDNA microarrays representing 8102 different human genes. The observed gene expression patterns provided a remarkably distinctive molecular portrait of each tumor. Twenty of the tumors had been sampled twice, both before and after a 16-week course of doxorubicin chemotherapy, and two tumors were paired with a lymph node metastasis from the same patient. The gene expression patterns observed in the serial samples from the same tumor, and the tumor/metastasis pairs, were almost always more similar to each other than either was to any other samples. Clusters of co-expressed genes were identified, for which variation in mRNA levels could be related to specific features of physiological variation, or to variation in the cellular constituents of the tumors. The tumors could be classified into subtypes that were distinguished by pervasive differences in their gene expression patterns. Such classifications were robust, and reflected changes in gene expression in the epithelial cells as well as differences in expression derived from the populations of non-epithelial cells in the tumors. These results suggest that gene expression patterns can provide distinctive and recognizable molecular portraits of individual tumors, and perhaps a basis for a new molecular classification of cancers.

Authors’ Affiliations

(1)
Stanford University School of Medicine

Copyright

© Current Science Ltd 2000

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