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Breast Cancer Research
Published in: Breast Cancer Research 3/2006

Open Access 01-06-2006 | Research article

The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis

Authors: Susan J Cleator, Trevor J Powles, Tim Dexter, Laura Fulford, Alan Mackay, Ian E Smith, Haukur Valgeirsson, Alan Ashworth, Mitch Dowsett

Published in: Breast Cancer Research | Issue 3/2006

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Abstract

Introduction

The aim of this study was to examine the effect of the cellular composition of biopsies on the error rates of multigene predictors of response of breast tumours to neoadjuvant adriamycin and cyclophosphamide (AC) chemotherapy.

Materials and methods

Core biopsies were taken from primary breast tumours of 43 patients prior to AC, and subsequent clinical response was recorded. Post-chemotherapy (day 21) samples were available for 16 of these samples. Frozen sections of each core were used to estimate the proportion of invasive cancer and other tissue components at three levels. Transcriptional profiling was performed using a cDNA array containing 4,600 elements.

Results

Twenty-three (53%) patients demonstrated a 'good' and 20 (47%) a 'poor' clinical response. The percentage invasive tumour in core biopsies collected from these patients varied markedly. Despite this, agglomerative clustering of sample expression profiles showed that almost all biopsies from the same tumour aggregated as nearest neighbours. SAM (significance analysis of microarrays) regression analysis identified 144 genes which distinguished high- and low-percentage invasive tumour biopsies at a false discovery rate of not more than 5%. The misclassification error of prediction of clinical response using microarray data from pre-treatment biopsies (on leave-one-out cross-validation) was 28%. When prediction was performed on subsets of samples which were more homogeneous in their proportions of malignant and stromal cells, the misclassification error was considerably lower (8%–13%, p < 0.05 on permutation).

Conclusion

The non-tumour content of breast cancer samples has a significant effect on gene expression profiles. Consideration of this factor improves accuracy of response prediction by expression array profiling. Future gene expression array prediction studies should be planned taking this into account.
Appendix
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Metadata
Title
The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis
Authors
Susan J Cleator
Trevor J Powles
Tim Dexter
Laura Fulford
Alan Mackay
Ian E Smith
Haukur Valgeirsson
Alan Ashworth
Mitch Dowsett
Publication date
01-06-2006
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 3/2006
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/bcr1506

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