The Experts below are selected from a list of 159471168 Experts worldwide ranked by ideXlab platform
Timothy R Rebbeck - One of the best experts on this subject based on the ideXlab platform.
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Abstract 2740: Decision tree-based modeling of androgen pathway genes and prostate cancer risk
Cancer Research, 2011Co-Authors: Jill S. Barnholtz-sloan, Charnita Zeigler-johnson, Neal J. Meropol, Xiaowei Guan, Timothy R RebbeckAbstract:Background: Inherited variability in genes that influence androgen metabolism has been implicated in the etiology of prostate cancer. However, joint effects of these genes have not been fully defined in terms of risk. Objective: The objective of this analysis was to evaluate gene-gene and gene-environment interactions for prostate cancer risk using classification and regression tree (CART) models (i.e. decision trees), and to evaluate whether these interactive effects add information about prostate cancer risk prediction beyond that of “traditional” risk factors. Methods: We compared CART models to traditional logistic regression models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional logistic regression (LR) to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: In European Americans, single SNP or haplotype associations were found with CYP3A5 (OR=2.11 (1.13, 3.97)); increasing number of CAG repeats in the AR gene (OR=0.90 (0.83, 0.98)); and the CYP3A4/CYP3A5 AG haplotype (OR=2.86 (1.15, 7.12)). No significant single SNP or haplotype associations were found in African Americans. The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of BPH, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, individual proportion of European ancestry, number of GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC while for African Americans, the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment interactions specific for European Americans and African Americans discovered using CART as compared to standard LR techniques. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2740. doi:10.1158/1538-7445.AM2011-2740
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Decision Tree-Based Modeling of Androgen Pathway Genes and Prostate Cancer Risk
Cancer Epidemiology Biomarkers & Prevention, 2011Co-Authors: Jill S. Barnholtz-sloan, Charnita Zeigler-johnson, Neal J. Meropol, Xiaowei Guan, Timothy R RebbeckAbstract:Background: Inherited variability in genes that influence androgen metabolism has been associated with prostate cancer risk. The objective of this analysis was to evaluate interactions for prostate cancer risk using classification and regression trees (CART) and to evaluate whether these interactive effects add information about risk prediction beyond that of "traditional" risk factors. Methods: We compared CART models to traditional logistic regression (LR) models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional LR to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of benign prostate hypertrophy, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, European ancestry proportion, GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC, while for African Americans the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment racial/ethnic specific interactions that would not have been found using traditional LR approaches. Impact: These results provide new insight into underlying prostate cancer biology for European Americans and African Americans.
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Joint effects of inflammation and androgen metabolism on prostate cancer severity.
International Journal of Cancer, 2008Co-Authors: Timothy R Rebbeck, Hanna Rennert, Teo V. Tran, Kyle Walker, Margerie Patacsil-coomes, Sachdeva R, Amy H Walker, Saarene Panossian, Elaine Spangler, Alan J. WeinAbstract:Multiple pathways of prostate carcinogenesis have been proposed, including those involving androgen metabolism and inflammation. These pathways are not independent, and may act together in prostate cancer etiology: androgens promote both inflammatory processes and serve as mitogens in prostate tumor growth. To explore the possible joint effects of these pathways in prostate cancer severity, we studied 1,090 Caucasian prostate cancer cases to evaluate whether tumor severity is influenced by a history of benign prostatic hyperplasia (BPH) interacting with genotypes involved in inflammation or androgen metabolism including MSR1, RNASEL, AR, CYP3A4, CYP3A43, CYP3A5 and SRD5A2. We observed a statistically significant interaction between a number of genotypes and BPH. After considering the potential for false positive associations, the only remaining significant associations involved CYP3A43 P340A genotypes and history of BPH on both Gleason grade (interaction p-value = 0.026) and tumor stage (interaction p-value = 0.017). These results suggest that androgen metabolism may act in concert with inflammatory phenotypes such as BPH in determining prostate cancer severity.
Charnita Zeigler-johnson - One of the best experts on this subject based on the ideXlab platform.
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Abstract 2740: Decision tree-based modeling of androgen pathway genes and prostate cancer risk
Cancer Research, 2011Co-Authors: Jill S. Barnholtz-sloan, Charnita Zeigler-johnson, Neal J. Meropol, Xiaowei Guan, Timothy R RebbeckAbstract:Background: Inherited variability in genes that influence androgen metabolism has been implicated in the etiology of prostate cancer. However, joint effects of these genes have not been fully defined in terms of risk. Objective: The objective of this analysis was to evaluate gene-gene and gene-environment interactions for prostate cancer risk using classification and regression tree (CART) models (i.e. decision trees), and to evaluate whether these interactive effects add information about prostate cancer risk prediction beyond that of “traditional” risk factors. Methods: We compared CART models to traditional logistic regression models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional logistic regression (LR) to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: In European Americans, single SNP or haplotype associations were found with CYP3A5 (OR=2.11 (1.13, 3.97)); increasing number of CAG repeats in the AR gene (OR=0.90 (0.83, 0.98)); and the CYP3A4/CYP3A5 AG haplotype (OR=2.86 (1.15, 7.12)). No significant single SNP or haplotype associations were found in African Americans. The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of BPH, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, individual proportion of European ancestry, number of GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC while for African Americans, the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment interactions specific for European Americans and African Americans discovered using CART as compared to standard LR techniques. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2740. doi:10.1158/1538-7445.AM2011-2740
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Decision Tree-Based Modeling of Androgen Pathway Genes and Prostate Cancer Risk
Cancer Epidemiology Biomarkers & Prevention, 2011Co-Authors: Jill S. Barnholtz-sloan, Charnita Zeigler-johnson, Neal J. Meropol, Xiaowei Guan, Timothy R RebbeckAbstract:Background: Inherited variability in genes that influence androgen metabolism has been associated with prostate cancer risk. The objective of this analysis was to evaluate interactions for prostate cancer risk using classification and regression trees (CART) and to evaluate whether these interactive effects add information about risk prediction beyond that of "traditional" risk factors. Methods: We compared CART models to traditional logistic regression (LR) models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional LR to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of benign prostate hypertrophy, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, European ancestry proportion, GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC, while for African Americans the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment racial/ethnic specific interactions that would not have been found using traditional LR approaches. Impact: These results provide new insight into underlying prostate cancer biology for European Americans and African Americans.
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CYP3A4, CYP3A5, and CYP3A43 Genotypes and Haplotypes in the Etiology and Severity of Prostate Cancer
Cancer research, 2004Co-Authors: Charnita Zeigler-johnson, Amy H Walker, Saarene Panossian, Elaine Spangler, Alan J. Wein, Tara M. Friebel, Yiting Wang, Margerie Patacsil, Richard Aplenc, S. Bruce MalkowiczAbstract:The CYP3A genes reside on chromosome 7q21 in a multigene cluster. The enzyme products of CYP3A4 and CYP3A43 are involved in testosterone metabolism. CYP3A4 and CYP3A5 have been associated previously with prostate cancer occurrence and severity. To comprehensively examine the effects of these genes on prostate cancer occurrence and severity, we studied 622 incident prostate cancer cases and 396 controls. Substantial and race-specific linkage disequilibrium was observed between CYP3A4 and CYP3A5 in both races but not between other pairs of loci. We found no association of CYP3A5 genotypes with prostate cancer or disease severity. CYP3A43*3 was associated with family history-positive prostate cancer (age- and race-adjusted odds ratio = 5.86, 95% confidence interval, 1.10-31.16). CYP3A4*1B was associated inversely with the probability of having prostate cancer in Caucasians (age-adjusted odds ratio = 0.54, 95% confidence interval, 0.32-0.94). We also observed significant interactions among these loci associated with prostate cancer occurrence and severity. There were statistically significant differences in haplotype frequencies involving these three genes in high-stage cases (P < 0.05) compared with controls. The observation that CYP3A4 and CYP3A43 were associated with prostate cancer, are not in linkage equilibrium, and are both involved in testosterone metabolism, suggest that both CYP3A4*1B and CYP3A43*3 may influence the probability of having prostate cancer and disease severity.
Jill S. Barnholtz-sloan - One of the best experts on this subject based on the ideXlab platform.
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Abstract 2740: Decision tree-based modeling of androgen pathway genes and prostate cancer risk
Cancer Research, 2011Co-Authors: Jill S. Barnholtz-sloan, Charnita Zeigler-johnson, Neal J. Meropol, Xiaowei Guan, Timothy R RebbeckAbstract:Background: Inherited variability in genes that influence androgen metabolism has been implicated in the etiology of prostate cancer. However, joint effects of these genes have not been fully defined in terms of risk. Objective: The objective of this analysis was to evaluate gene-gene and gene-environment interactions for prostate cancer risk using classification and regression tree (CART) models (i.e. decision trees), and to evaluate whether these interactive effects add information about prostate cancer risk prediction beyond that of “traditional” risk factors. Methods: We compared CART models to traditional logistic regression models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional logistic regression (LR) to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: In European Americans, single SNP or haplotype associations were found with CYP3A5 (OR=2.11 (1.13, 3.97)); increasing number of CAG repeats in the AR gene (OR=0.90 (0.83, 0.98)); and the CYP3A4/CYP3A5 AG haplotype (OR=2.86 (1.15, 7.12)). No significant single SNP or haplotype associations were found in African Americans. The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of BPH, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, individual proportion of European ancestry, number of GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC while for African Americans, the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment interactions specific for European Americans and African Americans discovered using CART as compared to standard LR techniques. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2740. doi:10.1158/1538-7445.AM2011-2740
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Decision Tree-Based Modeling of Androgen Pathway Genes and Prostate Cancer Risk
Cancer Epidemiology Biomarkers & Prevention, 2011Co-Authors: Jill S. Barnholtz-sloan, Charnita Zeigler-johnson, Neal J. Meropol, Xiaowei Guan, Timothy R RebbeckAbstract:Background: Inherited variability in genes that influence androgen metabolism has been associated with prostate cancer risk. The objective of this analysis was to evaluate interactions for prostate cancer risk using classification and regression trees (CART) and to evaluate whether these interactive effects add information about risk prediction beyond that of "traditional" risk factors. Methods: We compared CART models to traditional logistic regression (LR) models for associations of factors with prostate cancer risk using 1084 prostate cancer cases and 941 controls. All analyses were stratified by race. We used unconditional LR to complement and compare to the race-stratified CART results using the area under curve (AUC) for the receiver operating characteristic (ROC) curves. Results: The CART modeling of prostate cancer risk showed different interaction profiles by race. For European Americans, interactions among CYP3A43 genotype, history of benign prostate hypertrophy, family history of prostate cancer and age at consent revealed a distinct hierarchy of gene-environment and gene-gene interactions. While for African Americans, interactions among family history of prostate cancer, European ancestry proportion, GGC AR repeats and CYP3A4/CYP3A5 haplotype revealed distinct interaction effects from those found in European Americans. For European Americans the CART model had the highest AUC, while for African Americans the LR model with the CART discovered factors had the largest AUC. Conclusion: These results show novel gene-gene and gene-environment racial/ethnic specific interactions that would not have been found using traditional LR approaches. Impact: These results provide new insight into underlying prostate cancer biology for European Americans and African Americans.
Alan J. Wein - One of the best experts on this subject based on the ideXlab platform.
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Joint effects of inflammation and androgen metabolism on prostate cancer severity.
International Journal of Cancer, 2008Co-Authors: Timothy R Rebbeck, Hanna Rennert, Teo V. Tran, Kyle Walker, Margerie Patacsil-coomes, Sachdeva R, Amy H Walker, Saarene Panossian, Elaine Spangler, Alan J. WeinAbstract:Multiple pathways of prostate carcinogenesis have been proposed, including those involving androgen metabolism and inflammation. These pathways are not independent, and may act together in prostate cancer etiology: androgens promote both inflammatory processes and serve as mitogens in prostate tumor growth. To explore the possible joint effects of these pathways in prostate cancer severity, we studied 1,090 Caucasian prostate cancer cases to evaluate whether tumor severity is influenced by a history of benign prostatic hyperplasia (BPH) interacting with genotypes involved in inflammation or androgen metabolism including MSR1, RNASEL, AR, CYP3A4, CYP3A43, CYP3A5 and SRD5A2. We observed a statistically significant interaction between a number of genotypes and BPH. After considering the potential for false positive associations, the only remaining significant associations involved CYP3A43 P340A genotypes and history of BPH on both Gleason grade (interaction p-value = 0.026) and tumor stage (interaction p-value = 0.017). These results suggest that androgen metabolism may act in concert with inflammatory phenotypes such as BPH in determining prostate cancer severity.
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CYP3A4, CYP3A5, and CYP3A43 Genotypes and Haplotypes in the Etiology and Severity of Prostate Cancer
Cancer research, 2004Co-Authors: Charnita Zeigler-johnson, Amy H Walker, Saarene Panossian, Elaine Spangler, Alan J. Wein, Tara M. Friebel, Yiting Wang, Margerie Patacsil, Richard Aplenc, S. Bruce MalkowiczAbstract:The CYP3A genes reside on chromosome 7q21 in a multigene cluster. The enzyme products of CYP3A4 and CYP3A43 are involved in testosterone metabolism. CYP3A4 and CYP3A5 have been associated previously with prostate cancer occurrence and severity. To comprehensively examine the effects of these genes on prostate cancer occurrence and severity, we studied 622 incident prostate cancer cases and 396 controls. Substantial and race-specific linkage disequilibrium was observed between CYP3A4 and CYP3A5 in both races but not between other pairs of loci. We found no association of CYP3A5 genotypes with prostate cancer or disease severity. CYP3A43*3 was associated with family history-positive prostate cancer (age- and race-adjusted odds ratio = 5.86, 95% confidence interval, 1.10-31.16). CYP3A4*1B was associated inversely with the probability of having prostate cancer in Caucasians (age-adjusted odds ratio = 0.54, 95% confidence interval, 0.32-0.94). We also observed significant interactions among these loci associated with prostate cancer occurrence and severity. There were statistically significant differences in haplotype frequencies involving these three genes in high-stage cases (P < 0.05) compared with controls. The observation that CYP3A4 and CYP3A43 were associated with prostate cancer, are not in linkage equilibrium, and are both involved in testosterone metabolism, suggest that both CYP3A4*1B and CYP3A43*3 may influence the probability of having prostate cancer and disease severity.
Naoto Senda - One of the best experts on this subject based on the ideXlab platform.
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Modification of single-nucleotide polymorphism in a fully humanized CYP3A mouse by genome editing technology.
Scientific Reports, 2017Co-Authors: Kaoru Kobayashi, Shoko Takehara, Kazuomi Nakamura, Azusa Okada, Yasuko Tsukazaki, Kanako Kazuki, Tetsushi Sakuma, Naoto SendaAbstract:Cytochrome P450, family 3, subfamily A (CYP3A) enzymes metabolize approximately 50% of commercially available drugs. Recently, we developed fully humanized transchromosomic (Tc) CYP3A mice with the CYP3A cluster including CYP3A4, CYP3A5, CYP3A7, and CYP3A43. Our humanized CYP3A mice have the CYP3A5*3 (g.6986G) allele, resulting in the almost absence of CYP3A5 protein expression in the liver and intestine. To produce model mice for predicting CYP3A5′s contribution to pharmacokinetics, we performed a single-nucleotide polymorphism (SNP) modification of CYP3A5 (g.6986G to A, *3 to *1) on the CYP3A cluster using genome editing in both mouse ES cells and fertilized eggs, and produced humanized CYP3A5*1 mice recapitulating the CYP3A5*1 carrier phenotype in humans. The humanized CYP3A mouse with CYP3A5*1 is the first Tc mouse for predicting the SNP effect on pharmacokinetics in humans. The combination of Tc technology and genome editing enables the production of useful humanized models that reflect humans with different SNPs.
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Trans-chromosomic mice containing a human CYP3A cluster for prediction of xenobiotic metabolism in humans
Human Molecular Genetics, 2012Co-Authors: Yasuhiro Kazuki, Yasuko Tsukazaki, Naoto Senda, Sasitorn Aueviriyavit, Hiroki Kawakami, Takeshi Oshima, Yoshimi Kuroiwa, Kaoru Kobayashi, Sumio OhtsukiAbstract:Human CYP3A is the most abundant P450 isozyme present in the human liver and small intestine, and metabolizes around 50% of medical drugs on the market. The human CYP3A subfamily comprises four members (CYP3A4, CYP3A5, CYP3A7, CYP3A43) encoded on human chromosome 7. However, transgenic mouse lines carrying the entire human CYP3A cluster have not been constructed because of limitations in conventional cloning techniques. Here, we show that the introduction of a human artificial chromosome (HAC) containing the entire genomic human CYP3A locus recapitulates tissue- and stage-specific expression of human CYP3A genes and xenobiotic metabolism in mice. About 700 kb of the entire CYP3A genomic segment was cloned into a HAC (CYP3A-HAC), and trans-chromosomic (Tc) mice carrying a single copy of germline-transmittable CYP3A-HAC were generated via a chromosome-engineering technique. The tissue- and stage-specific expression profiles of CYP3A genes were consistent with those seen in humans. We further generated mice carrying the CYP3A-HAC in the background homozygous for targeted deletion of most endogenous Cyp3a genes. In this mouse strain with ‘fully humanized’ CYP3A genes, the kinetics of triazolam metabolism, CYP3A-mediated mechanism-based inactivation effects and formation of fetal-specific metabolites of dehydroepiandrosterone observed in humans were well reproduced. Thus, these mice are likely to be valuable in evaluating novel drugs metabolized by CYP3A enzymes and in studying the regulation of human CYP3A gene expression. Furthermore, this system can also be used for generating Tc mice carrying other human metabolic genes.
