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Breast Cancer Research and Treatment
Published in: Breast Cancer Research and Treatment 3/2008

01-08-2008 | Epidemiology

Drug metabolism-related genes as potential biomarkers: analysis of expression in normal and tumour breast tissue

Authors: Vanesa Martinez, Susan Kennedy, Padraig Doolan, Patrick Gammell, Helena Joyce, Elaine Kenny, Jai Prakash Mehta, Eoin Ryan, Robert O’Connor, John Crown, Martin Clynes, Lorraine O’Driscoll

Published in: Breast Cancer Research and Treatment | Issue 3/2008

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Abstract

The complex role of drug metabolism-related enzymes and their possible influence in cancer development, treatment and outcome has not yet been completely elucidated. There is evidence that these enzymes can activate certain environmental procarcinogens to more toxic derivatives and thus a role has been proposed for them in carcinogenesis. The fact that they can also inactivate a number of chemotherapeutic drugs has raised the possibility of these enzymes influencing the sensitivity of tumour cells to anticancer agents. In this report, we analyse the expression of drug metabolism-related genes within a whole genome microarray study of 104 breast cancer and 17 normal breast specimens. Kaplan–Meier survival curves, Chi-squared, and Cox Regression analyses were used to identify associations between expression of gene transcripts and patients’ clinicopathological and survival data. Our results show that several of these genes are significantly expressed in both normal and tumour tissue; in many cases, expression is altered in the tumour specimens as compared to normal breast tissue. Moreover, expression of ARNT2 and GST A1 was correlated with prognosis. Kaplan–Meier analysis showed expression of ARNT2 mRNA to correlate significantly with favourable disease outcome for patients, in terms of both their disease-free survival (P = 0.0094) and overall survival (P = 0.0018) times from diagnosis, while detection of GST A1 mRNA correlated with shortened disease-free survival (P = 0.0131) and overall survival (P = 0.0028). Multivariate analysis indicated GST A1 expression to be an independent prognostic factor for overall survival (P = 0.045). Our results suggest a possible use of ARNT2 and GST A1 as prognostic breast cancer biomarkers.
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Metadata
Title
Drug metabolism-related genes as potential biomarkers: analysis of expression in normal and tumour breast tissue
Authors
Vanesa Martinez
Susan Kennedy
Padraig Doolan
Patrick Gammell
Helena Joyce
Elaine Kenny
Jai Prakash Mehta
Eoin Ryan
Robert O’Connor
John Crown
Martin Clynes
Lorraine O’Driscoll
Publication date
01-08-2008
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 3/2008
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-007-9739-9

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