PATH-48. THE DNA METHYLATION LANDSCAPE OF CORE AND PERIPHERAL DIFFUSE GLIOMA REGIONS SHOWS LITTLE SPATIAL SUBTYPE HETEROGENEITY AFTER CONSIDERING TUMOR PURITY
Bibliographic record
Abstract
Abstract While diffuse gliomas are notorious for their histopathological, genetic and transcriptional spatial heterogeneity, little is known about their epigenetic spatial heterogeneity. The result of spatial (epi)genetic analysis is strongly influenced by the proportion of cancer cells in a sample, so called tumor purity. However, a gold standard for assessment of tumor purity is lacking. We set out to analyze tumor purity using different measurement modalities and explore tumor purity-corrected DNA methylation spatial heterogeneity in glioma. DNA methylation(-derived), quantitative histological and radiological measurements of tumor purity, as well as DNA methylation profiles, were analyzed in 133 image-guided multi-sector stereotactic biopsy samples of 16 patients with newly diagnosed glioma. These biopsies were acquired in regions with and without abnormalities on MRI. Data was validated in two independent populations of respectively 102 multi-region samples in 24 glioma patients and 64 single-region samples from patients without glioma. DNA methylation profiles from The Cancer Genome Atlas and the patients without glioma was used to predict DNA methylation and transcriptional subtype. Consensus measurement of tumor purity estimates (CPE) ranged from 0 to 91% and was most correlated with the DNA methylation measurement of tumor purity. Neuropathological qualitative assessment of tumor presence generally corresponded well with CPE, but occasionally samples reported as ‘histologically normal’ demonstrated tumor purities up to 53%. After filtering specimens with tumor purity less than 50%, DNA methylation subtype showed little spatial heterogeneity, this in contrast to transcriptional subtype. Samples from core and peripheral regions showed similar DNA methylation profiles. Non-purity related intratumoral heterogeneity for promotor methylation of epigenetically regulated genes was minimal, but higher in IDH-wildtype than in IDH-mutant gliomas. In conclusion, after considering DNA methylation-based measurement of tumor purity DNA methylation in diffuse gliomas shows little spatial heterogeneity; incorporating such tumor purity information can further increase the reliability of methylation-profiling-based tumor classification.
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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".