F.1 DNA methylome profiling identifies stability of IDH mutations throughout glioma evolution
Bibliographic record
Abstract
Background: Isocitrate dehydrogenase (IDH) mutation status is a key diagnostic and prognostic feature of gliomas. There are conflicting reports regarding the stability of IDH mutations throughout glioma evolution and treatment. Here, we provide an institutional experience of patients with conflicting IDH mutation status longitudinally in order to determine if IDH mutation status changes over time. Methods: We retrospectively identified patients from 2009-2018 with immunohistochemistry (IHC)-recorded IDH mutation status discrepancies longitudinally. Archived frozen tissue samples were analyzed using methylation profiling, Sanger sequencing, and droplet digital PCR (ddPCR). Results were compared to the IHC-reported IDH mutation status. Results: We reviewed 1491 archived glioma samples including 91 patients with multiple tumour samples collected longitudinally. In all instances of IDH mutation discrepancy, we found reasonable explanations through multi-platform profiling that resolved the discrepancies. This included the presence of non-canonical IDH2 mutations identified through Sanger sequencing and perilesional tumour samples or reactive brain tissue identified through methylation profiling. Conclusions: Our findings support the hypothesis that IDH mutations occur early in gliomagenesis and are stable throughout glioma treatment and evolution. Our study highlights the importance of accurate surgical sampling and the role of DNA methylome profiling in diagnostically uncertain cases for integrated pathological and molecular diagnosis.
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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 | 0.002 |
| 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) | 0.001 | 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".