Tissue 2-Hydroxyglutarate as a Biomarker for <i>Isocitrate Dehydrogenase</i> Mutations in Gliomas
Bibliographic record
Abstract
Abstract Purpose: Isocitrate dehydrogenase (IDH) mutations are common in low-grade gliomas and the IDH mutation status is now integrated into the WHO classification of gliomas. IDH mutations lead to preferential accumulation of the R- relative to the S-enantiomer of 2-hydroxyglutarate (2-HG). We investigated the utility of tissue total 2-HG, R-2-HG, and the R-2-HG/S-2-HG ratio (rRS) as diagnostic and prognostic biomarkers for IDH mutations in gliomas. Experimental Design: Glioma tissue and blood samples from 87 patients were analyzed with HPLC-MS/MS coupled with a CHIROBIOTIC column to quantify both enantiomers of 2-HG. ROC analysis was conducted to evaluate the sensitivity and specificity of 2-HG, R-2-HG, and rRS. The feasibility of real-time determination of IDH status was evaluated in 11 patients intraoperatively. The prognostic value of rRS was evaluated using the Kaplan–Meier method. Results: The rRS in glioma tissues clearly distinguished patients with IDH-mutant versus wild-type tumors (P < 0.001). Sensitivity and specificity using an rRS cut-off value of 32.26 were 97% and 100%, respectively. None of total 2-HG, R-2-HG, or rRS was elevated in serum samples. Among patients with IDH-mutant tumors, tissue rRS stratifies overall survival. The duration of tissue analysis is approximately 60 minutes. Conclusions: Our study demonstrates that rRS is a reliable biomarker of IDH mutation status. This technique can be used to determine IDH mutation status intraoperatively, and to guide treatment decisions based on IDH mutation status in real time. Finally, rRS values may provide additional prognostic information and further validation is required.
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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 | 0.001 | 0.001 |
| 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".