Estimation of exposure to two potent heterocyclic aromatic amines in various human populations and their role in colorectal cancer

Thesis (Ph. D.)--Massachusetts Institute of Technology, Division of Toxicology, 1997.Includes bibliographical references.by La Creis R. Kidd.Ph.D

Automating biomedical data science through tree-based pipeline optimization

Over the past decade, data science and machine learning has grown from a mysterious art form to a staple tool across a variety of fields in academia, business, and government. In this paper, we introduce the concept of tree-based pipeline optimization for automating one of the most tedious parts of machine learning---pipeline design. We implement a Tree-based Pipeline Optimization Tool (TPOT) and demonstrate its effectiveness on a series of simulated and real-world genetic data sets. In particular, we show that TPOT can build machine learning pipelines that achieve competitive classification accuracy and discover novel pipeline operators---such as synthetic feature constructors---that significantly improve classification accuracy on these data sets. We also highlight the current challenges to pipeline optimization, such as the tendency to produce pipelines that overfit the data, and suggest future research paths to overcome these challenges. As such, this work represents an early step toward fully automating machine learning pipeline design.Comment: 16 pages, 5 figures, to appear in EvoBIO 2016 proceeding

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among Men of African Descent: A case-control study

<p>Abstract</p> <p>Background</p> <p>Polymorphisms in <it>glutathione S-transferase </it>(GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected <it>GST </it>genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic <it>GSTs </it>(<it>M1</it>, <it>T1</it>, and <it>P1</it>) alone and combined with cigarette smoking on PCA susceptibility.</p> <p>Methods</p> <p>In order to evaluate the effects of <it>GST </it>polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of <it>GSTM1 </it>and <it>GSTT1 </it>gene deletions, <it>GSTP1 </it>105 Val and cigarette smoking on PCA risk.</p> <p>Results</p> <p>We observed a moderately significant association between risk among men possessing at least one variant <it>GSTP1 </it>105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among <it>GSTM1 </it>(OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and <it>GSTT1 </it>(OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the <it>GSTM1</it>-<it>GSTP1 </it>pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the <it>GSTP1 </it>Val marker. Notably, the <it>GSTM1</it>-<it>GSTP1 </it>axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the <it>GST </it>SNPs and PCA.</p> <p>Conclusion</p> <p>A moderately significant association was observed between PCA risk and men possessing at least one variant <it>GSTP1 </it>105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the <it>GSTP1 </it>(Val/Val) and <it>GSTM1 </it>(*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting <it>GSTP1 </it>105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility.</p

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer

<p>Abstract</p> <p>Background</p> <p>Molecular and epidemiological evidence demonstrate that altered gene expression and single nucleotide polymorphisms in the apoptotic pathway are linked to many cancers. Yet, few studies emphasize the interaction of variant apoptotic genes and their joint modifying effects on prostate cancer (PCA) outcomes. An exhaustive assessment of all the possible two-, three- and four-way gene-gene interactions is computationally burdensome. This statistical conundrum stems from the prohibitive amount of data needed to account for multiple hypothesis testing.</p> <p>Methods</p> <p>To address this issue, we systematically prioritized and evaluated individual effects and complex interactions among 172 apoptotic SNPs in relation to PCA risk and aggressive disease (i.e., Gleason score ≥ 7 and tumor stages III/IV). Single and joint modifying effects on PCA outcomes among European-American men were analyzed using statistical epistasis networks coupled with multi-factor dimensionality reduction (SEN-guided MDR). The case-control study design included 1,175 incident PCA cases and 1,111 controls from the prostate, lung, colo-rectal, and ovarian (PLCO) cancer screening trial. Moreover, a subset analysis of PCA cases consisted of 688 aggressive and 488 non-aggressive PCA cases. SNP profiles were obtained using the NCI Cancer Genetic Markers of Susceptibility (CGEMS) data portal. Main effects were assessed using logistic regression (LR) models. Prior to modeling interactions, SEN was used to pre-process our genetic data. SEN used network science to reduce our analysis from > 36 million to < 13,000 SNP interactions. Interactions were visualized, evaluated, and validated using entropy-based MDR. All parametric and non-parametric models were adjusted for age, family history of PCA, and multiple hypothesis testing.</p> <p>Results</p> <p>Following LR modeling, eleven and thirteen sequence variants were associated with PCA risk and aggressive disease, respectively. However, none of these markers remained significant after we adjusted for multiple comparisons. Nevertheless, we detected a modest synergistic interaction between <it>AKT3 rs2125230-PRKCQ rs571715 </it>and disease aggressiveness using SEN-guided MDR (p = 0.011).</p> <p>Conclusions</p> <p>In summary, entropy-based SEN-guided MDR facilitated the logical prioritization and evaluation of apoptotic SNPs in relation to aggressive PCA. The suggestive interaction between <it>AKT3-PRKCQ </it>and aggressive PCA requires further validation using independent observational studies.</p

Evaluation of Oxidative Stress Response Related Genetic Variants, Pro-oxidants, Antioxidants and Prostate Cancer

Background: Oxidative stress and detoxification mechanisms have been commonly studied in Prostate Cancer (PCa) due to their function in the detoxification of potentially damaging reactive oxygen species (ROS) and carcinogens. However, findings have been either inconsistent or inconclusive. These mixed findings may, in part, relate to failure to consider interactions among oxidative stress response related genetic variants along with pro- and antioxidant factors. Methods: We examined the effects of 33 genetic and 26 environmental oxidative stress and defense factors on PCa risk and disease aggressiveness among 2,286 men from the Cancer Genetic Markers of Susceptibility project (1,175 cases, 1,111 controls). Single and joint effects were analyzed using a comprehensive statistical approach involving logistic regression, multi-dimensionality reduction, and entropy graphs. Results: Inheritance of one CYP2C8 rs7909236 T or two SOD2 rs2758331 A alleles was linked to a 1.3- and 1.4-fold increase in risk of developing PCa, respectively (p-value = 0.006-0.013). Carriers of CYP1B1 rs1800440GG, CYP2C8 rs1058932TC and, NAT2 (rs1208GG, rs1390358CC, rs7832071TT) genotypes were associated with a 1.3 to 2.2-fold increase in aggressive PCa [p-value = 0.04-0.001, FDR 0.088-0.939]. We observed a 23% reduction in aggressive disease linked to inheritance of one or more NAT2 rs4646247 A alleles (p = 0.04, FDR = 0.405). Only three NAT2 sequence variants remained significant after adjusting for multiple hypotheses testing, namely NAT2 rs1208, rs1390358, and rs7832071. Lastly, there were no significant gene-environment or gene-gene interactions associated with PCa outcomes. Conclusions: Variations in genes involved in oxidative stress and defense pathways may modify PCa. Our findings do not firmly support the role of oxidative stress genetic variants combined with lifestyle/environmental factors as modifiers of PCa and disease progression. However, additional multi-center studies poised to pool genetic and environmental data are needed to make strong conclusions

No Association between Variant -acetyltransferase Genes, Cigarette Smoking and Prostate Cancer Susceptibility Among Men of African Descent

Objective We evaluated the individual and combination effects of NAT1, NAT2 and tobacco smoking in a case-control study of 219 incident prostate cancer (PCa) cases and 555 disease-free men. Methods Allelic discriminations for 15 NAT1 and NAT2 loci were detected in germ-line DNA samples using Taqman polymerase chain reaction (PCR) assays. Single gene, gene-gene and gene-smoking interactions were analyzed using logistic regression models and multi-factor dimensionality reduction (MDR) adjusted for age and subpopulation stratification. MDR involves a rigorous algorithm that has ample statistical power to assess and visualize gene-gene and gene-environment interactions using relatively small samples sizes (i.e., 200 cases and 200 controls). Results Despite the relatively high prevalence of NAT1*10/*10 (40.1%), NAT2 slow (30.6%), and NAT2 very slow acetylator genotypes (10.1%) among our study participants, these putative risk factors did not individually or jointly increase PCa risk among all subjects or a subset analysis restricted to tobacco smokers. Conclusion Our data do not support the use of N -acetyltransferase genetic susceptibilities as PCa risk factors among men of African descent; however, subsequent studies in larger sample populations are needed to confirm this finding

Multi-institutional prostate cancer study of genetic susceptibility in populations of African descent.

International audienceProstate cancer disparities have been reported in men of African descent who show the highest incidence, mortality, compared with other ethnic groups. Few studies have explored the genetic and environmental factors for prostate cancer in men of African ancestry. The glutathione-S-transferases family conjugates carcinogens before their excretion and is expressed in prostate tissue. This study addressed the role of GSTM1 and GSTT1 deletions on prostate cancer risk in populations of African descent. This multi-institutional case-control study gathered data from the Genetic Susceptibility to Environmental Carcinogens (GSEC) database, the African-Caribbean Cancer Consortium (AC3) and Men of African Descent and Carcinoma of the Prostate Consortium (MADCaP). The analysis included 10 studies (1715 cases and 2363 controls), five in African-Americans, three in African-Caribbean and two in African men. Both the GSTM1 and the GSTT1 deletions showed significant inverse associations with prostate cancer [odds ratio (OR): 0.90, 95% confidence interval (CI) 0.83-0.97 and OR 0.88, 95% CI: 0.82-0.96, respectively]. The association was restricted to Caribbean and African populations. A significant positive association was observed between GSTM1 deletion and prostate cancer in smokers in African-American studies (OR: 1.28, 95% CI: 1.01-1.56), whereas a reduced risk was observed in never-smokers (OR: 0.66, 95% CI: 0.46-0.95). The risk of prostate cancer increased across quartiles of pack-years among subjects carrying the deletion of GSTM1 but not among subjects carrying a functional GSTM1. Gene-environment interaction between smoking and GSTM1 may be involved in the etiology of prostate cancer in populations of African descent