The DNA methylome of DDR genes and benefit from RT or TMZ in IDH mutant low-grade glioma treated in EORTC 22033
Bibliographic record
Abstract
The optimal treatment for patients with low-grade glioma (LGG) WHO grade II remains controversial. Overall survival ranges from 2 to over 15 years depending on molecular and clinical factors. Hence, risk-adjusted treatments are required for optimizing outcome and quality of life. We aim at identifying mechanisms and associated molecular markers predictive for benefit from radiotherapy (RT) or temozolomide (TMZ) in LGG patients treated in the randomized phase III trial EORTC 22033. As candidate biomarkers for these genotoxic treatments, we considered the DNA methylome of 410 DNA damage response (DDR) genes. We first identified 62 functionally relevant CpG sites located in the promoters of 24 DDR genes, using the LGG data from The Cancer Genome Atlas. Then we tested their association with outcome [progression-free survival (PFS)] depending on treatment in 120 LGG patients of EORTC 22033, whose tumors were mutant for isocitrate dehydrogenase 1 or 2 (IDHmt), the molecular hallmark of LGG. The results suggested that seven CpGs of four DDR genes may be predictive for longer PFS in one of the treatment arms that comprised MGMT, MLH3, RAD21, and SMC4. Most interestingly, the two CpGs identified for MGMT are the same, previously selected for the MGMT-STP27 score that is used to determine the methylation status of the MGMT gene. This score was higher in the LGG with 1p/19q codeletion, in this and other independent LGG datasets. It was predictive for PFS in the TMZ, but not in the RT arm of EORTC 22033. The results support the hypothesis that a high score predicts benefit from TMZ treatment for patients with IDHmt LGG, regardless of the 1p/19q status. This MGMT methylation score may identify patients who benefit from first-line treatment with TMZ, to defer RT for long-term preservation of cognitive function and quality of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".