Abstract B1-32: Genome-wide integrative analysis correlating locus-specific DNA methylation and hydroxymethylation to gene expression in normal prostate cells
Bibliographic record
Abstract
Abstract Aberrant epigenetic modification in the form of regional hypermethylation and global hypomethylation has been implicated in the dysregulation of gene expression in various cancers, including prostate cancer (PCa). Recently discovered 5-hydroxymethylated marks (5hmC), considered to be key intermediates in the process of DNA demethylation, have also been shown to exhibit significant global loss in solid tumors as compared to normal tissue. Similar to cytosine base methylation (5mC), 5hmC may also play a key role in the regulation of gene expression and, consequently, gene function in PCa. We hypothesize that dynamic interplay between 5mC and 5hmC enrichment in promoter, CpG island, and intragenic regions shows specific association patterns with gene expression. A systematic investigation of these methylation marks may provide novel insights into epigenomic architecture by elucidating novel pathways and candidate genes in prostate tumorigenesis. Using Next Generation Sequencing (NGS), we characterized genome-wide 5mC and 5hmC marks and RNA expression data in a normal prostate tissue-derived representative cell line (RWPE-1). We have completed NGS following methyl-binding protein capture (MBD-seq) and hydroxymethyl-selective chemical labeling (hMe-Seal), and have performed integrative analysis correlating enriched genes stratified by region (intergenic regions proximal to DNase I hypersensitivity sites, as well as promoter, CpG island, and intragenic regions) to expression data obtained from RNA-seq and also validated using publicly available microarray expression data (GEO Accession Number: GSM375783) We divided expression data into equal tiers representing genes with no expression, low expression, and high expression, and have performed pathway-based analysis on genes significantly enriched for either 5mC or 5hmC marks for each tier stratified by gene region. We found gene expression to exhibit a strong positive correlation with core promoter and CpG island hydroxymethylation, with a corresponding negative correlation to methylation of these regions. In contrast, gene expression was found to be positively correlated with both methylation and hydroxymethylation in both intragenic regions and intergenic regions proximal to ENCODE DNase I hypersensitivity sites (GEO Accession Number: GSM1008595), which are associated with open chromatin and may play a role in downstream gene regulation. Interestingly, pathway-based analysis of these stratified tiers, grouped via the Molecular Complex Detection algorithm (MCODE) to identify pathway clusters with high biological significance, showed 5hmC and 5mC enrichment of the same pathways in each expression tier, suggesting a possible co-operative role for intragenic co-expression of these marks in regulating biological pathways. Clustered pathways co-enriched in intragenic 5mC and 5hmC showed strong enrichment in Gene Ontology terms related to core cellular functions within each expression tier, such as ion channel and transport regulation, primary metabolic processes, and protein and RNA binding. Currently, we are investigating these pathways to identify key candidate genes regulated by 5hmC and 5mC marks in normal prostate. This is the first study to correlate locus-specific global 5hmC enrichment to expression in normal prostate cells. Our preliminary analysis has shown correlation between 5hmC and 5mC enrichment in genic, promoter, CpG island, and upstream DNase I hypersensitivity site-proximal regions and expression in RWPE-1 cells. Insights from this model will subsequently be explored via whole-genome differential analysis between normal prostate and PCa to determine the effect of epigenetic alterations in cancer on gene expression. Subsequently, our characterization of key cellular pathways exhibiting dynamic enrichment patterns for 5hmC or 5mC marks will potentially allow us to identify differentially epigenetically modified target genes implicated in prostate cancer tumorigenesis. Citation Format: Shivani N. Kamdar, Linh T. Ho, Ruth Isserlin, Ken J. Kron, Theodorus van der Kwast, Alexandre R. Zlotta, Neil E. Fleshner, Gary Bader, Bharati Bapat. Genome-wide integrative analysis correlating locus-specific DNA methylation and hydroxymethylation to gene expression in normal prostate cells. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-32.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".