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Title of Journal: Breast Cancer Res Treat

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Abbravation: Breast Cancer Research and Treatment

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Springer US

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DOI

10.1016/0042-207x(68)90823-3

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ISSN

1573-7217

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Interaction between smoking history and gene expre

Authors: Sarah A Andres Katie E Bickett Mohammad A Alatoum Theodore S Kalbfleisch Guy N Brock James L Wittliff
Publish Date: 2015/07/23
Volume: 152, Issue: 3, Pages: 545-556
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Abstract

In contrast to studies focused on cigarette smoking and risk of breast cancer occurrence this study explored the influence of smoking on breast cancer recurrence and progression The goal was to evaluate the interaction between smoking history and gene expression levels on recurrence and overall survival of breast cancer patients Multivariable Cox proportional hazards models were fitted for 48 cigarette smokers 50 nonsmokers and the total population separately to determine which gene expressions and gene expression/cigarette usage interaction terms were significant in predicting overall and diseasefree survival in breast cancer patients Using methods similar to Andres et al BMC Cancer 13326 2013a Horm Cancer 4208–221 2013b multivariable analyses revealed CENPN CETN1 CYP1A1 IRF2 LECT2 and NCOA1 to be important predictors for both breast carcinoma recurrence and mortality among smokers Additionally COMT was important for recurrence and NAT1 and RIPK1 were important for mortality In contrast only IRF2 CETN1 and CYP1A1 were significant for disease recurrence and mortality among nonsmokers with NAT2 additionally significant for survival Analysis of interaction between smoking status and gene expression values using the combined samples revealed significant interactions between smoking status and CYP1A1 LECT2 and CETN1 Signatures consisting of 7–8 genes were highly predictive for breast cancer recurrence and overall survival among smokers with median Cindex values of 08 and 073 for overall survival and recurrence respectively In contrast median Cindex values for nonsmokers was only 059 Hence significant interactions between gene expression and smoking status can play a key role in predicting breast cancer patient outcomesWe would like to thank Irina A Smolenkova for her technical assistance This project was supported in part by a grant from the Phi Beta Psi Charity Trust TSK JLW and a Research on Women ROW grant to JLW from the EVP for Research and Innovation University of Louisville

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