BIOM-84. MGMT METHYLATION STATUS REMAINS LARGELY UNCHANGED IN RECURRENT GLIOMA AND INFLUENCES RE-TREATMENT WITH TEMOZOLOMIDE
Bibliographic record
Abstract
Abstract BACKGROUND MGMT promoter methylation is a critical biomarker in glioma, predicting response to temozolomide (TMZ) and overall survival. In this study we investigated changes in MGMT methylation status between two sequential glioma samples and explored their clinical implications on clinical decision making. METHODS Data from 533 patients with recurrent glioma in the Caris database were analyzed; 426 had MGMT status available for two sequential tumor samples and were classified as hypermethylated or unmethylated (including equivocal cases). A retrospective chart review was also performed for 28 patients from two institutions, including 10 overlapping with the Caris cohort. RESULTS Among the 426 patients, 84% (358) retained the same MGMT status—52% unmethylated and 32% hypermethylated. Notably, 16% (68) changed status: 11% from hypermethylated to unmethylated and 5% vice versa. Patients who lost hypermethylation had lower initial methylation levels than those who remained hypermethylated (mean difference 13.5 points, p<0.001). Similarly, patients gaining hypermethylation had lower methylation at recurrence compared to consistently hypermethylated cases (mean difference 16.3 points, p<0.001). Time between surgeries was shorter in patients who remained unmethylated (p=0.001) or lost methylation (p=0.006) compared to those consistently hypermethylated. In the clinical cohort (n=28), 86% showed no methylation status change (46% unmethylated, 39% hypermethylated). Four patients (14%) changed status equally in both directions. All but two patients received TMZ after initial resection. At recurrence, 55% of those who remained hypermethylated were re-treated with TMZ, while the rest received investigational therapy or supportive care. CONCLUSION MGMT methylation status remains unchanged in the majority of recurrent gliomas, with change notable in 16% of cases. Clinically, TMZ is frequently used at diagnosis regardless of methylation, but its use appears to be more selective to hypermethylated cases at recurrence. Larger studies are needed to clarify the survival impact of TMZ re-challenge based on methylation changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".