Molecular classification of breast cancer patients by gene expression profiling

• Published in: The Journal of pathology Vol. 195; no. 3; pp. 312 - 320
• Main Authors: Ahr, André, Holtrich, Uwe, Solbach, Christine, Scharl, Anton, Strebhardt, Klaus, Karn, Thomas, Kaufmann, Manfred
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.10.2001; Wiley
• Subjects: Biological and medical sciences; breast cancer; Breast Neoplasms - classification; Breast Neoplasms - genetics; Breast Neoplasms - pathology; Cluster Analysis; diagnosis; differentially expressed genes; DNA array; DNA Primers - genetics; DNA Probes - genetics; Female; Gene Expression Profiling; Genetic Markers; Gynecology. Andrology. Obstetrics; Humans; Lymphatic Metastasis; Mammary gland diseases; Medical sciences; Oligonucleotide Array Sequence Analysis; Polymerase Chain Reaction - methods; Tumors; tumour classification; Human; Hybridization; Malignant tumor; Gene expression; Real time; Polymerase chain reaction; Pathology; Mammary gland diseases; Histopathology; Classification; Epithelial cell; Female; Diagnosis; Mammary gland; Molecular biology; Comparative study
• ISSN: 0022-3417; 1096-9896
• DOI: 10.1002/path.955

For many tumuors, pathological subclasses exist which have to be further defined by genetic markers to improve therapy and follow‐up strategies. In this study, cDNA array analyses of breast cancers have been performed to classify tumuors into categories based on expression patterns. Comparing purified normal ductal epithelial cells and corresponding tumour tissues, the expression of only a small fraction of genes was found to be significantly changed. A subset of genes repeatedly found to be differentially expressed in breast cancers was subsequently employed to perform a classification of 82 normal and malignant breast specimens by cluster analysis. This analysis identifies a subgroup of transcriptionally related tumours, designated class A, which can be further subdivided into A1 and A2. Correlation with classical clinicopathological parameters revealed that subgroup A1 was characterized by a high number of node‐positive tumours (14 of 16). In this subgroup there was a disproportionate number of patients who had already developed distant metastases at the time of diagnosis (25% in this subgroup, compared with 5% among the rest of the samples). Taken together, the use of these differentially expressed marker genes in conjunction with sample clustering algorithms provides a novel molecular classification of breast cancer specimens, which facilitates the identification of patients with a higher risk of recurrence. Copyright © 2001 John Wiley & Sons, Ltd.