Abstract 1428: A CpG island methylator phenotype defines a clinically aggressive subgroup of posterior fossa ependymoma
Bibliographic record
Abstract
Abstract Ependymoma is the third most common pediatric brain tumor and remains incurable in 45% of patients. It arises in the spinal cord, supratentorial brain, and most commonly in children, the posterior fossa (PF). We recently reported the identification of two molecularly and clinically distinct subgroups of PF ependymoma, which we named Group A and B. While patients with Group B tumors harbor a large number of gross chromosomal gains and losses (approx. 17 arm events per tumor) and have favorable prognoses (5 year PFS = 92%), patients with Group A tumors have balanced genomic profiles (approx. 1 arm event per tumor) with poor clinical outcomes (5 year PFS = 24%). We hypothesized that aberrant DNA methylation could be a mechanism driving the tumorigenesis of Group A PF ependymoma. To this end, we isolated methylated DNA in 92 ependymomas by Methyl Binding Domain 2 protein assisted recovery, and hybridized enriched DNA to promoter tiling arrays (Nimblegen). Using unsupervised hierarchical clustering we determined that the DNA methylation profiles of ependymoma were regionally specified, dividing tumors into subgroups according to their anatomical origin. Using both gene expression and DNA methylation platforms, we identified a subset of PF ependymoma, which clustered with spinal tumors, supporting the vast molecular differences between Group A and B PF ependymoma. We next compared the number of methylated genes identified in Group A versus B, and observed that Group A tumors exhibited a greater number of methylated genes at specific CpG islands, a feature described as a CpG island methylator phenotype (CIMP) in glioma, colon cancer, and breast cancer. We validated these findings in a non-overlapping cohort of 48 PF ependymomas, analyzed using a different array technology (Illumina Infinium 450K). Using various unsupervised clustering methods (HCL, K-MEANS, NMF, and SOM), we verified that Group A and B exhibited highly distinct DNA methylation profiles. Further, we confirmed that Group A tumours were defined by a greater overall number of methylated genes (A: 855, B: 233; Wilcoxon-Rank Sum Test), and a greater number of methylated genes per tumour (A: 511, B: 425; Wilcoxon-Rank Sum Test). We performed Gene Set Enrichment analysis and observed that many genes methylated in Group A exhibited a significant overlap with genes marked by the polycomb repressor (PRC2) complex in embryonic stem cells (p<0.0001, FDR<0.1%), a phenomenon seen in other cancer CIMPs. We propose two diverse mechanisms leading to tumourigenesis in Group A and B ependymoma. The greater number of chromosomal alterations in Group B suggests a Chromosomal Instability (CIN) phenotype, while the greater number of methylated CpG islands in Group A suggests a CpG island Methylator (CIMP) phenotype. Understanding these underlying mechanisms driving Group A and B pathogenesis may yield new leads for subgroup-specific treatments of PF ependymoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1428. doi:1538-7445.AM2012-1428
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".