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Articles by E. A Houseman
Total Records ( 2 ) for E. A Houseman
  E. A Houseman , B. C Christensen , M. R Karagas , M. R Wrensch , H. H Nelson , J. L Wiemels , S Zheng , J. K Wiencke , K. T Kelsey and C. J. Marsit
 

Motivation: Integration of various genome-scale measures of molecular alterations is of great interest to researchers aiming to better define disease processes or identify novel targets with clinical utility. Particularly important in cancer are measures of gene copy number DNA methylation. However, copy number variation may bias the measurement of DNA methylation. To investigate possible bias, we analyzed integrated data obtained from 19 head and neck squamous cell carcinoma (HNSCC) tumors and 23 mesothelioma tumors.

Results: Statistical analysis of observational data produced results consistent with those anticipated from theoretical mathematical properties. Average beta value reported by Illumina GoldenGate (a bead-array platform) was significantly smaller than a similar measure constructed from the ratio of average dye intensities. Among CpGs that had only small variations in measured methylation across tumors (filtering out clearly biological methylation signatures), there were no systematic copy number effects on methylation for three and more than four copies; however, one copy led to small systematic negative effects, and no copies led to substantial significant negative effects.

Conclusions: Since mathematical considerations suggest little bias in methylation assayed using bead-arrays, the consistency of observational data with anticipated properties suggests little bias. However, further analysis of systematic copy number effects across CpGs suggest that though there may be little bias when there are copy number gains, small biases may result when one allele is lost, and substantial biases when both alleles are lost. These results suggest that further integration of these measures can be useful for characterizing the biological relationships between these somatic events.

  C. S Wilhelm Benartzi , D. C Koestler , E. A Houseman , B. C Christensen , J. K Wiencke , A. R Schned , M. R Karagas , K. T Kelsey and C. J. Marsit
 

DNA methylation profiles can be used to define molecular cancer subtypes that may better inform disease etiology and clinical decision-making. This investigation aimed to create DNA methylation profiles of bladder cancer based on CpG methylation from almost 800 cancer-related genes and to then examine the relationship of those profiles with exposures related to risk and clinical characteristics. DNA, derived from formalin-fixed paraffin-embedded tumor samples obtained from incident cases involved in a population-based case-control study of bladder cancer in New Hampshire, was used for methylation profiling on the Illumina GoldenGate Methylation Bead Array. Unsupervised clustering of those loci with the greatest change in methylation between tumor and non-diseased tissue was performed to defined molecular subgroups of disease, and univariate tests of association followed by multinomial logistic regression was used to examine the association between these classes, bladder cancer risk factors and clinical phenotypes. Membership in the two most methylated classes was significantly associated with invasive disease (P < 0.001 for both class 3 and 4). Male gender (P = 0.04) and age >70 years (P = 0.05) was associated with membership in one of the most methylated classes. Finally, average water arsenic levels in the highest percentile predicted membership in an intermediately methylated class of tumors (P = 0.02 for both classes). Exposures and demographic associated with increased risk of bladder cancer specifically associate with particular subgroups of tumors defined by DNA methylation profiling and these subgroups may define more aggressive disease.

 
 
 
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