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The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis
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 primar...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1557729/ https://www.ncbi.nlm.nih.gov/pubmed/16790077 http://dx.doi.org/10.1186/bcr1506 |
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author | Cleator, Susan J Powles, Trevor J Dexter, Tim Fulford, Laura Mackay, Alan Smith, Ian E Valgeirsson, Haukur Ashworth, Alan Dowsett, Mitch |
author_facet | Cleator, Susan J Powles, Trevor J Dexter, Tim Fulford, Laura Mackay, Alan Smith, Ian E Valgeirsson, Haukur Ashworth, Alan Dowsett, Mitch |
author_sort | Cleator, Susan J |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-1557729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-15577292006-09-01 The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis Cleator, Susan J Powles, Trevor J Dexter, Tim Fulford, Laura Mackay, Alan Smith, Ian E Valgeirsson, Haukur Ashworth, Alan Dowsett, Mitch Breast Cancer Res Research Article 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. BioMed Central 2006 2006-06-21 /pmc/articles/PMC1557729/ /pubmed/16790077 http://dx.doi.org/10.1186/bcr1506 Text en Copyright © 2006 Cleator et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Cleator, Susan J Powles, Trevor J Dexter, Tim Fulford, Laura Mackay, Alan Smith, Ian E Valgeirsson, Haukur Ashworth, Alan Dowsett, Mitch The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
title | The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
title_full | The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
title_fullStr | The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
title_full_unstemmed | The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
title_short | The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
title_sort | effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1557729/ https://www.ncbi.nlm.nih.gov/pubmed/16790077 http://dx.doi.org/10.1186/bcr1506 |
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