Differences in methylation profiles between long-term survivors and short-term survivors of IDH-wild-type glioblastoma
Bibliographic record
Abstract
Abstract Background Patients with glioblastoma (GBM) have a median overall survival (OS) of approximately 16 months. However, approximately 5% of patients survive >5 years. This study examines the differences in methylation profiles between long-term survivors (>5 years, LTS) and short-term survivors (<1 year, STS) with isocitrate dehydrogenase (IDH)-wild-type GBMs. Methods In a multicenter retrospective analysis, we identified 25 LTS with a histologically confirmed GBM. They were age- and sex-matched to an STS. The methylation profiles of all 50 samples were analyzed with EPIC 850k, classified according to the DKFZ methylation classifier, and the methylation profiles of LTS versus STS were compared. Results After methylation profiling, 16/25 LTS and 23/25 STS were confirmed to be IDH-wild-type GBMs, all with +7/–10 signature. LTS had significantly increased O6-methylguanine methyltransferase (MGMT) promoter methylation and higher prevalence of FGFR3-TACC3 fusion (P = .03). STS were more likely to exhibit CDKN2A/B loss (P = .01) and higher frequency of NF1 (P = .02) mutation. There were no significant CpGs identified between LTS versus STS at an adjusted P-value of .05. Unadjusted analyses identified key pathways involved in both LTS and STS. The most common pathways were the Hippo signaling pathway and the Wnt pathway in LTS, and GPCR ligand binding and cell–cell signaling in STS. Conclusions A small group of patients with IDH-wild-type GBM survive more than 5 years. While there are few differences in the global methylation profiles of LTS compared to STS, our study highlights potential pathways involved in GBMs with a good or poor prognosis.
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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) | 0.001 | 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".