Explore the vast range of titles available.

DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed. Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data. Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a \"hypermethylator state.\" High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA. We identified a methylation signature for a \"hypermethylator phenotype\" in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers.

Eosinophilic esophagitis (EoE) is a chronic, food-driven allergic disease resulting in eosinophilic esophageal inflammation. We recently found that EoE susceptibility is associated with genetic variants in the promoter of CAPN14, a gene with reported esophagus-specific expression. CAPN14 is dynamically up-regulated as a function of EoE disease activity and after exposure of epithelial cells to interleukin-13 (IL-13). Herein, we aimed to explore molecular modulation of CAPN14 expression. We identified three putative binding sites for the IL-13-activated transcription factor STAT6 in the promoter and first intron of CAPN14. Luciferase reporter assays revealed that the two most distal STAT6 elements were required for the ∼10-fold increase in promoter activity subsequent to stimulation with IL-13 or IL-4, and also for the genotype-dependent reduction in IL-13-induced promoter activity. One of the STAT6 elements in the promoter was necessary for IL-13-mediated induction of CAPN14 promoter activity while the other STAT6 promoter element was necessary for full induction. Chromatin immunoprecipitation in IL-13 stimulated esophageal epithelial cells was used to further support STAT6 binding to the promoter of CAPN14 at these STAT6 binding sites. The highest CAPN14 and calpain-14 expression occurred with IL-13 or IL-4 stimulation of esophageal epithelial cells under culture conditions that allow the cells to differentiate into a stratified epithelium. This work corroborates a candidate molecular mechanism for EoE disease etiology in which the risk variant at 2p23 dampens CAPN14 expression in differentiated esophageal epithelial cells following IL-13/STAT6 induction of CAPN14 promoter activity.

Background DNA methylation is an important epigenetic mark and dysregulation of DNA methylation is associated with many diseases including cancer. Advances in next-generation sequencing now allow unbiased methylome profiling of entire patient cohorts, greatly facilitating biomarker discovery and presenting new opportunities to understand the biological mechanisms by which changes in methylation contribute to disease. Enrichment-based sequencing assays such as MethylCap-seq are a cost effective solution for genome-wide determination of methylation status, but the technical reliability of methylation reconstruction from raw sequencing data has not been well characterized. Methods We analyze three MethylCap-seq data sets and perform two different analyses to assess data quality. First, we investigate how data quality is affected by excluding samples that do not meet quality control cutoff requirements. Second, we consider the effect of additional reads on enrichment score, saturation, and coverage. Lastly, we verify a method for the determination of the global amount of methylation from MethylCap-seq data by comparing to a spiked-in control DNA of known methylation status. Results We show that rejection of samples based on our quality control parameters leads to a significant improvement of methylation calling. Additional reads beyond ~13 million unique aligned reads improved coverage, modestly improved saturation, and did not impact enrichment score. Lastly, we find that a global methylation indicator calculated from MethylCap-seq data correlates well with the global methylation level of a sample as obtained from a spike-in DNA of known methylation level. Conclusions We show that with appropriate quality control MethylCap-seq is a reliable tool, suitable for cohorts of hundreds of patients, that provides reproducible methylation information on a feature by feature basis as well as information about the global level of methylation.

DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed. Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data. Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a \"hypermethylator state.\" High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA. We identified a methylation signature for a \"hypermethylator phenotype\" in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers.

DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed. Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data. Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a \"hypermethylator state.\" High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA. We identified a methylation signature for a \"hypermethylator phenotype\" in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers.

Introduction: DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation marks are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens. Widespread accumulation of methylation in regulatory elements in some cancers (termed the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA that are not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses have been performed for a limited number of cancer specimens. Yet methods for analyzing these large datasets and integrating findings from different studies have not been fully developed. An approach was developed to profile CIMP by combining the strengths of two different methylome profiling techniques. Methods: Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing (MethylCap-seq). Publically available data from The Cancer Genome Atlas (TCGA) for 203 endometrial cancers, analyzed using the Infinium HumanMethylation 450 beadchip, were compared to the MethylCap-seq data. A MethylCap-seq quality control module was developed to exclude sequencing samples with poor-quality methylation data from analysis. Additional MethylCap-seq datasets were also used to develop and validate the quality control module. Results: Analysis of total methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. I developed a 13-region methylation signature associated with a “hypermethylator state” using a training set of five highly methylated and eight lowly methylated tumors. The signature was validated using data from TCGA. High signature methylation score was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in TCGA test set. In addition, the methylation signature distinguished >90% of endometrioid endometrial tumors from normal controls in the test set. Furthermore, classification of tumors by signature methylation score proved highly robust, showing good agreement with previously published methylation clusters for the test set as well as consistent ranking of tumors across alternative signatures. Conclusion: I identified a methylation signature for a “hypermethylator phenotype” in endometrial cancer and developed methods that could prove useful for identifying extreme methylation phenotypes in other cancers.

Eosinophilic esophagitis (EoE) is a chronic, food-driven allergic disease resulting in eosinophilic esophageal inflammation. We recently found that EoE susceptibility is associated with genetic variants in the promoter of CAPN14, a gene with reported esophagus-specific expression. CAPN14 is dynamically up-regulated as a function of EoE disease activity and after exposure of epithelial cells to interleukin-13 (IL-13). Herein, we aimed to explore molecular modulation of CAPN14 expression. We identified three putative binding sites for the IL-13-activated transcription factor STAT6 in the promoter and first intron of CAPN14. Luciferase reporter assays revealed that the two most distal STAT6 elements were required for the ~10-fold increase in promoter activity subsequent to stimulation with IL-13 or IL-4, and also for the genotype-dependent reduction in IL-13-induced promoter activity. One of the STAT6 elements in the promoter was necessary for IL-13-mediated induction of CAPN14 promoter activity while the other STAT6 promoter element was necessary for full induction. Chromatin immunoprecipitation in IL-13 stimulated esophageal epithelial cells was used to further support STAT6 binding to the promoter of CAPN14 at these STAT6 binding sites. The highest CAPN14 and calpain-14 expression occurred with IL-13 or IL-4 stimulation of esophageal epithelial cells under culture conditions that allow the cells to differentiate into a stratified epithelium. This work corroborates a candidate molecular mechanism for EoE disease etiology in which the risk variant at 2p23 dampens mediated CAPN14 expression in differentiated esophageal epithelial cells following IL-13/STAT6 induction of CAPN14 promoter activity.

Improving the heat tolerance of cotton is a major concern for breeding programs. To address this need, a fast and effect way of quantifying thermotolerant phenotypes is required. Triphenyl tetrazolium chloride (TTC) based enzyme viability testing following high-temperature stress can be used as a vegetative heat tolerance phenotype. This is because when live cells encounter a TTC solution, TTC undergoes a chemical reduction producing a visible, insoluble red product called triphenyl formazan, that can be quantified spectrophotometrically. However, existing TTC based cell viability assays cannot easily be deployed at the scale required in a crop improvement program. In this study, a heat stress assay (HSA) based on the use of TTC enzyme viability testing has been refined and improved for efficiency, reliability, and ease of use through four experiments. Sampling factors that may influence assay results, such as leaf age, plant water status, and short-term cold storage, were also investigated. Experiments conducted in this study have successfully downscaled the assay and identified an optimal sampling regime, enabling measurement of large segregating populations for application in breeding programs. The improved HSA methodology is important as it is proposed that long-term improvements in cotton thermotolerance can be achieved through the concurrent selection of superior phenotypes based on the HSA and yield performance in hot environments. Additionally, a new way of interpreting both heat tolerance and heat resistance was developed, differentiating genotypes that perform well at the time of a heat stress event and those that maintain a similar performance level to a non-stressed control.