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吸烟史与基因表达水平之间的相互作用会影响乳腺癌患者的生存率。

Interaction between smoking history and gene expression levels impacts survival of breast cancer patients.

作者信息

Andres Sarah A, Bickett Katie E, Alatoum Mohammad A, Kalbfleisch Theodore S, Brock Guy N, Wittliff James L

机构信息

Department of Biochemistry & Molecular Biology, University of Louisville, Louisville, KY, 40202, USA.

出版信息

Breast Cancer Res Treat. 2015 Aug;152(3):545-56. doi: 10.1007/s10549-015-3507-z. Epub 2015 Jul 23.

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 non-smokers, and the total population separately to determine which gene expressions and gene expression/cigarette usage interaction terms were significant in predicting overall and disease-free survival in breast cancer patients. Using methods similar to Andres et al. (BMC Cancer 13:326, 2013a; Horm Cancer 4:208-221, 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 non-smokers, 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 C-index values of 0.8 and 0.73 for overall survival and recurrence, respectively. In contrast, median C-index values for non-smokers was only 0.59. Hence, significant interactions between gene expression and smoking status can play a key role in predicting breast cancer patient outcomes.

摘要

与聚焦于吸烟与乳腺癌发生风险的研究不同,本研究探讨了吸烟对乳腺癌复发和进展的影响。目标是评估吸烟史与基因表达水平对乳腺癌患者复发和总生存的相互作用。分别对48名吸烟者、50名不吸烟者以及总人群拟合多变量Cox比例风险模型,以确定哪些基因表达以及基因表达/吸烟情况交互项在预测乳腺癌患者的总生存和无病生存方面具有显著性。使用与安德烈斯等人(《BMC癌症》13:326,2013年a;《激素癌症》4:208 - 221,2013年b)相似的方法,多变量分析显示,CENPN、CETN1、CYP1A1、IRF2、LECT2和NCOA1是吸烟者中乳腺癌复发和死亡的重要预测因素。此外,COMT对复发很重要,NAT1和RIPK1对死亡很重要。相比之下,在不吸烟者中,只有IRF2、CETN1和CYP1A1对疾病复发和死亡具有显著性,NAT2对生存也具有显著性。使用合并样本分析吸烟状态与基因表达值之间的相互作用,发现吸烟状态与CYP1A1、LECT2和CETN1之间存在显著的相互作用。由7 - 8个基因组成的特征对吸烟者的乳腺癌复发和总生存具有高度预测性,总生存和复发的C指数中位数分别为0.8和0.73。相比之下,不吸烟者的C指数中位数仅为0.59。因此,基因表达与吸烟状态之间的显著相互作用在预测乳腺癌患者的预后方面可能起关键作用。

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