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Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (1)
Molecular carcinogenesis (1)
Etzel, Carol J. (2)
Cortes, Andrea C. (1)
El-Zein, Randa (1)
El-Zein, Randa A. (1)
Fenech, Michael (1)
Lopez, Mirtha (1)
Lopez, Mirtha S. (1)
Monroy, Claudia M. (1)
Rourke, Elizabeth (1)
Spitz, Margaret R. (1)
Strom, Sara S. (1)
Younes, Anas (1)
Year of Publication
Hodgkin Lymphoma Risk: Role of Genetic Polymorphisms and Gene-Gene Interactions in DNA repair pathways
Monroy, Claudia M.
Cortes, Andrea C.
Etzel, Carol J.
Strom, Sara S.
DNA repair variants may play a potentially important role in an individual’s susceptibility to developing cancer. Numerous studies have reported the association between genetic single nucleotide polymorphisms (SNPs) in DNA repair genes and different types of hematologic cancers. However, to date, the effects of such SNPs on modulating Hodgkin Lymphoma (HL) risk have not yet been investigated. We hypothesized that gene-gene interaction between candidate genes in Direct Reversal, Nucleotide excision repair (NER), Base excision repair (BER) and Double strand break (DSB) pathways may contribute to susceptibility to HL. To test this hypothesis, we conducted a study on 200 HL cases and 220 controls to assess associations between HL risk and 21 functional SNPs in DNA repair genes. We evaluated potential gene-gene interactions and the association of multiple polymorphisms in a chromosome region using a multi-analytic strategy combining logistic regression, multi-factor dimensionality reduction and classification and regression tree approaches. We observed that, in combination, allelic variants in the XPC Ala499Val, NBN Glu185Gln, XRCC3 Thr241Me, XRCC1 Arg194Trp and XRCC1 399Gln polymorphisms modify the risk for developing HL. Moreover, the cumulative genetic risk score revealed a significant trend where the risk for developing HL increases as the number of adverse alleles in BER and DSB genes increase. These findings suggest that DNA repair variants in BER and DSB pathways may play an important role in the development of HL.
Cytokinesis-Blocked Micronucleus Cytome Assay Biomarkers Identify Lung Cancer Cases Amongst Smokers
El-Zein, Randa A.
Spitz, Margaret R.
Etzel, Carol J.
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
The multi-endpoint cytokinesis-blocked micronucleus assay is used for assessing chromosome aberrations. We have recently reported that this assay is extremely sensitive to genetic damage caused by the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyr-idyl)-1-butanone (NNK) and that the binucleated cells with micronuclei, nucleoplasmic bridges, and nuclear buds in lymphocytes (chromosome damage endpoints measured by the assay) are strong predictors of lung cancer risk. In the current study, we refined our analysis to include toxicity endpoints (micronuclei in mononucleated cells, apoptosis, necrosis, and nuclear division index) to investigate the benefit of including these variables on improving the predictive value of the assay. Baseline and NNK-induced micronuclei in mononucleated cells were significantly higher in patients (n = 139) than controls (n = 130; P < 0.001). Baseline apoptosis was higher among cases; however, the controls showed a significant higher fold increase in NNK-induced apoptosis compared with baseline (P < 0.001). Principal components analysis was used to derive a summary measure for all endpoints and calculate the positive predictive value (PPV) and negative predictive value (NPV) for disease status. First principal component for NNK-induced chromosome damage endpoints (binucleated cells with micronuclei, nucleoplasmic bridges, and nuclear buds) had an area under the curve = 97.9 (95% confidence interval, 95.9-99.0), PPV = 94.8, and NPV = 92.6. The discriminatory power improved when micronuclei in mononucleated cells were included: area under the curve = 99.1 (95% confidence interval, 97.9- 100.0), PPV = 98.7 and NPV = 95.6. The simplicity, rapidity, and sensitivity of the assay together with potential for automation make it a valuable tool for screening and prioritizing potential cases for intensive screening.
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