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.
Adipokines are important for regulation body metabolism and immune response. Many studies have shown that variants in adipokines genes play a role in age-associated diseases. In this study, we investigated the contribution of rs266729 (-11377G/C), rs2241766 (+45T/G), and rs1501299 (+276 G/T) SNPs of adiponectin gene (ADIPQO) and rs7799039 (-2548C/A) SNP of leptin (LEP) gene to human longevity phenotype in Jordanian population. Polymorphisms were genotyped in 110 randomly selected elderly subjects (>85 years old) with mean age of 90.2 years, and 120 young control subjects (range from 20 to 50 years) with mean age of 32.0 years. No significant differences were detected in the genotype and allele frequencies of examined gene variants between the two groups (p > 0.05). However, when gender was considered, genotypes and alleles frequencies of rs1501299 SNP in ADIPOQ gene and rs7799039 in LEP gene were significantly associated with longevity in men (p < 0.02) but not in women (p > 0.05). Thus, ADIPOQ and LEP genes polymorphisms might play a gender-specific role in the pathway to men's longevity.
Our investigations explore the association of cigarette smoking on breast cancer risk of recurrence and progression, in contrast to studies that focused on tobacco use and risk of breast cancer occurrence. The goal was to decipher the interaction between smoking history and expression levels of 22 gene candidates selected from microarray data obtained from laser capture microdissected carcinoma cells from 247 de-identified patient tissue biopsies on disease recurrence and overall patient survival of breast cancer patients. qRT-PCR was used to determine expression levels for NAT1, NAT2, COMT, SOD1, SOD2, BRCA1, BRCA2, APOC1, ARID1B, CTNNBL1, MSX1, UBE2F, IRF2, NCOA1, LECT2, THAP4, RIPK1, AGPAT1, C7orf23, CENPN, CETN1 and YTHDC2 selected from a previous study for 50 breast cancer patients with a history of cigarette smoking and 51 patients who had never smoked. For smokers and non-smokers separately, L1-penalized multivariable Cox regression models were fit to predict patient disease-free and overall survival, with 1000 splits of the data into training (70%) and test (30%) sets to determine predictive accuracy based on the C-index. The LASSO penalty was used to perform variable selection in each of the training sets, and a permutation procedure was used to determine a significance threshold for the number of times a variable was kept in the model. Multivariable analyses using the LASSO revealed CENPN, CETN1, CYP1A1, IRF2, LECT2, and NCOA1 to be significant predictors for both disease recurrence and mortality among smokers. Additionally, COMT was highly associated with recurrence, and NAT1 and RIPK1 were associated with mortality. In contrast, only IRF2, CETN1, and CYP1A1 were significant for disease recurrence and mortality among non-smokers, with NAT2 additionally significant for survival. Median, 25th percentile, and 75th percentile for the C-indexes based on the gene expression models are given in Table 1. Table 1. C-indexes for the Four Gene Expression Models Based on 1000 Test Data SetsPatient GroupOutcome25th PercentileMedian75th PercentileCurrent SmokersOverall Survival0.730.800.86Current SmokersRecurrence-free Survival0.670.730.78Never SmokedOverall Survival0.530.590.66Never SmokedRecurrence-free Survival0.510.590.66 Analysis of interaction between smoking status and gene expression values using the combined samples revealed significant interactions between smoking status and CYP1A1, LECT2, CETN1. Molecular 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, the median C-index values for non-smokers was only 0.59. Hence, significant interactions between expression of crucial genes and cigarette smoking status appear to play a key role in predicting clinical outcomes of breast carcinoma patients. Supported in part by a grant from the Phi Beta Psi Charity Trust (TSK & JLW) and a Research of Women (ROW) grant to JLW from the EVP for Research and Innovation, University of Louisville. Citation Format: James L Wittliff, Sarah A Andres, Mohammad A Alatoum, Katie E Bickett, Theodore S Kalbfleisch, Guy N Brock. Interaction between smoking history and gene expression levels impacts survival of breast carcinoma patients [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-03-11.
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