Abstract 5325: 5-hydroxymethylcytosine profiling identifies differential targeting in <i>IDH1</i> mutant versus <i>IDH1</i> wild-type high-grade gliomas
Bibliographic record
Abstract
Abstract Glioblastoma demonstrates significant epigenetic dysregulation with subgroup differences highlighted by the Glioma CpG-Island Methylator Phenotype (G-CIMP) seen in IDH1 mutant tumors. 5-hydroxymethylcytosine (5hmC) has been implicated in IDH1 wild-type gliomas, however its role in IDH1 mutant tumors remains incompletely understood. We examined 5hmC profiles in high grade (WHO III/IV) IDH1 mutant (n = 12) and IDH1 wild-type (n = 9) tumors through parallel processing of samples using bisulfite (BS) and oxidative bisulfite (OxBS) conversion, with subsequent analysis on the Illumina MethylationEPIC Beadchip platform. Hydroxymethylation profiles were correlated with gene expression measured using the Affymetrix Human Gene 2.0 ST array platform. Cumulative density plots for mean 5hmC β-value across IDH1 mutant and wild-type tumors demonstrated 5hmC accumulation predominantly within the top 10th percentile of probes. No significant difference in global 5hmC levels between IDH1 mutant versus wild-type tumors was evident. Mean 5hmC β-values were 4.6%% and 3.8% for IDH1 mutant and wild-type tumors across all probes, respectively. To focus on regions with greatest 5hmC abundance, we assessed probes among the top 1% mean 5hmC β-values. In addition to probes with high 5hmC abundance, differentially hydroxymethylated (DHMR) regions were identified using the R package ChAMP, comparing IDH1 mutant to wild-type tumors. At the probe level, top 1% and DHMR probes demonstrated a relative increase in 5hmC among IDH1 mutant tumors versus IDH1 wild-type. Top 1% and DHMR probes were enriched for enhancer and super-enhancer regions in both IDH1 mutant and IDH1 wild-type tumors, however enhancer and super-enhancers targeted only partially overlapped. Pathway enrichment analysis for top 1% probe gene targets and DHMR-associated genes identified pathways implicated in glioma pathogenesis. Among genes characteristically ‘hypermethylated' in G-CIMP + tumors, 28/50 were methylated while 22/50 were hypermethylated in our IDH1 mutant cohort, suggesting that 5hmC contributes to overall methylation of G-CIMP target genes. 5hmC marked the most highly expressed genes in our tumor cohort, with increased expression associated with gene body hydroxymethylation. Among 1367 genes differentially expressed between IDH1 mutant and wild-type tumors, 48 demonstrated a positive significant Spearman correlation between probe 5hmC β-value and gene expression (r ≥ 0.5, p < 0.05), including genes implicated in gliomagenesis as well as novel candidates. This correlation was most evident for genes upregulated in the IDH1 mutant cohort. Citation Format: Wioletta Glowacka, Harshika Jain, Makiko Okura, Abulizi Maimaitiming, Romina Nejad, Mamatjan Yasin, Hamza Farooq, Kenneth Aldape, Paul Kongkham. 5-hydroxymethylcytosine profiling identifies differential targeting in IDH1 mutant versus IDH1 wild-type high-grade gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5325.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".