Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments.

Glioblastoma multiforme (GBM) is the most deadly brain tumor, and currently lacks effective treatment options. Brain tumor-initiating cells (BTICs) and orthotopic xenografts are widely used in investigating GBM biology and new therapies for this aggressive disease. However, the genomic characteristics and molecular resemblance of these models to GBM tumors remain undetermined. We used massively parallel sequencing technology to decode the genomes and transcriptomes of BTICs and xenografts and their matched tumors in order to delineate the potential impacts of the distinct growth environments. Using data generated from whole-genome sequencing of 201 samples and RNA sequencing of 118 samples, we show that BTICs and xenografts resemble their parental tumor at the genomic level but differ at the mRNA expression and epigenomic levels, likely due to the different growth environment for each sample type. These findings suggest that a comprehensive genomic understanding of in vitro and in vivo GBM model systems is crucial for interpreting data from drug screens, and can help control for biases introduced by cell-culture conditions and the microenvironment in mouse models. We also found that lack of MGMT expression in pretreated GBM is linked to hypermutation, which in turn contributes to increased genomic heterogeneity and requires new strategies for GBM treatment.

Integration of DNA methylation patterns and genetic variation in human pediatric tissues help inform EWAS design and interpretation.

BACKGROUND: The widespread use of accessible peripheral tissues for epigenetic analyses has prompted increasing interest in the study of tissue-specific DNA methylation (DNAm) variation in human populations. To date, characterizations of inter-individual DNAm variability and DNAm concordance across tissues have been largely performed in adult tissues and therefore are limited in their relevance to DNAm profiles from pediatric samples. Given that DNAm patterns in early life undergo rapid changes and have been linked to a wide range of health outcomes and environmental exposures, direct investigations of tissue-specific DNAm variation in pediatric samples may help inform the design and interpretation of DNAm analyses from early life cohorts. In this study, we present a systematic comparison of genome-wide DNAm patterns between matched pediatric buccal epithelial cells (BECs) and peripheral blood mononuclear cells (PBMCs), two of the most widely used peripheral tissues in human epigenetic studies. Specifically, we assessed DNAm variability, cross-tissue DNAm concordance and genetic determinants of DNAm across two independent early life cohorts encompassing different ages. RESULTS: BECs had greater inter-individual DNAm variability compared to PBMCs and highly the variable CpGs are more likely to be positively correlated between the matched tissues compared to less variable CpGs. These sites were enriched for CpGs under genetic influence, suggesting that a substantial proportion of DNAm covariation between tissues can be attributed to genetic variation. Finally, we demonstrated the relevance of our findings to human epigenetic studies by categorizing CpGs from published DNAm association studies of pediatric BECs and peripheral blood. CONCLUSIONS: Taken together, our results highlight a number of important considerations and practical implications in the design and interpretation of EWAS analyses performed in pediatric peripheral tissues.

Epigenetic analysis of human postmortem brain tissue.

Epigenomic profiles have been mapped across a broad range of brain regions and developmental contexts in postmortem human brain tissues, illuminating our understanding of epigenetic regulation in neural function and plasticity across the life course. Importantly, disease-associated epigenetic alterations in postmortem brain have provided compelling insights into the gene-regulatory architecture underlying neurobiologic disease susceptibility and pathogenesis. However, the use of postmortem brain tissues for molecular analyses warrants careful consideration of key technical and biologic factors that may confound epigenetic analyses. In this chapter, we describe the predominant forms of epigenetic regulation (DNA modifications, chromatin structure, and noncoding RNA expression) and discuss the various methodologies used to assess each epigenetic mark. In addition, we provide an overview of existing epigenetic studies using human brain tissues as well as highlight the various challenges and considerations for epigenomic profiling in human postmortem brain samples.

DNA methylation signatures of chronic alcohol dependence in purified CD3+ T-cells of patients undergoing alcohol treatment.

Several studies have shown an association of alcohol dependence with DNA methylation (DNAm), suggesting that environmentally-induced changes on epigenomic variation may play an important role in alcohol dependence. In the present study, we analysed genome-wide DNAm profiles of purified CD3+ T-cells from pre- and post-treatment alcohol dependent patients, as well as closely matched healthy controls. We identified 59 differentially methylated CpG sites comparing patients prior to treatment with healthy controls and were able to confirm 8 of those sites in additional analyses for differentially methylated regions. Comparing patients before and after a 3-week alcohol treatment program we revealed another unique set of 48 differentially methylated CpG sites. Additionally, we found that the mean global DNAm was significantly lower in patients prior to treatment compared to controls, but reverted back to levels similar to controls after treatment. We validated top-ranked hits derived from the epigenome-wide analysis by pyrosequencing and further replicated two of them in an independent cohort and confirmed differential DNAm of HECW2 and SRPK3 in whole blood. This study is the first to show widespread DNAm variation in a disease-relevant blood cell type and implicates HECW2 and SRPK3 DNAm as promising blood-based candidates to follow up in future studies.

Adjusting for Cell Type Composition in DNA Methylation Data Using a Regression-Based Approach.

Analysis of DNA methylation in a population context has the potential to uncover novel gene and environment interactions as well as markers of health and disease. In order to find such associations it is important to control for factors which may mask or alter DNA methylation signatures. Since tissue of origin and coinciding cell type composition are major contributors to DNA methylation patterns, and can easily confound important findings, it is vital to adjust DNA methylation data for such differences across individuals. Here we describe the use of a regression method to adjust for cell type composition in DNA methylation data. We specifically discuss what information is required to adjust for cell type composition and then provide detailed instructions on how to perform cell type adjustment on high dimensional DNA methylation data. This method has been applied mainly to Illumina 450K data, but can also be adapted to pyrosequencing or genome-wide bisulfite sequencing data.

DNA methylation profiling in human Huntington's disease brain.

Despite extensive progress in Huntington's disease (HD) research, very little is known about the association of epigenetic variation and HD pathogenesis in human brain tissues. Moreover, its contribution to the tissue-specific transcriptional regulation of the huntingtin gene (HTT), in which HTT expression levels are highest in brain and testes, is currently unknown. To investigate the role of DNA methylation in HD pathogenesis and tissue-specific expression of HTT, we utilized the Illumina HumanMethylation450K BeadChip array to measure DNA methylation in a cohort of age-matched HD and control human cortex and liver tissues. In cortex samples, we found minimal evidence of HD-associated DNA methylation at probed sites after correction for cell heterogeneity but did observe an association with the age of disease onset. In contrast, comparison of matched cortex and liver samples revealed tissue-specific DNA methylation of the HTT gene region at 38 sites (FDR < 0.05). Importantly, we identified a novel differentially methylated binding site in the HTT proximal promoter for the transcription factor CTCF. This CTCF site displayed increased occupancy in cortex, where HTT expression is higher, compared with the liver. Additionally, CTCF silencing reduced the activity of an HTT promoter-reporter construct, suggesting that CTCF plays a role in regulating HTT promoter function. Overall, although we were unable to detect HD-associated DNA methylation alterations at queried sites, we found that DNA methylation may be correlated to the age of disease onset in cortex tissues. Moreover, our data suggest that DNA methylation may, in part, contribute to tissue-specific HTT transcription through differential CTCF occupancy.