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Comparison of 2-hydroxyglutarate (2HG) levels in tissue and serum of isocitrate dehydrogenase (IDH)-mutated (MUT) versus wild-type (WT) gliomas.

2017· article· en· W2684146816 on OpenAlexaffabout
Hao‐Wen Sim, Romina Nejad, Wenjiang Zhang, Warren Mason, Mark Bernstein, Ken Aldape, Gelareh Zadeh, Eric Xueyu Chen

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsToronto Western HospitalPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsIsocitrate dehydrogenaseGliomaMedicineIDH1GastroenterologyInternal medicinePathologyMolecular biologyCancer researchBiologyMutantGeneticsBiochemistryGene

Abstract

fetched live from OpenAlex

2037 Background: IDH mutations are common in low-grade gliomas and confer significantly improved prognosis. IDH catalyzes the oxidative decarboxylation of isocitrate to α-ketoglutarate, and subsequently to the oncometabolite 2HG. Mutant IDH leads to preferential accumulation of the R relative to the S enantiomer of 2HG. We analyzed the ratio of R to S enantiomers (rRS) in glioma tissues and matched serum samples, and correlated findings with IDH status, 1p19q codeletion status and survival. Methods: Fresh frozen glioma tissues and matched serum samples were obtained from the University of Toronto Brain Tumor Bank. IDH status was determined by immunohistochemistry and confirmed by 450K methylation profile or direct sequencing. 1p19q codeletion status was determined by loss-of-heterozygosity PCR analysis. R-2HG and S-2HG levels were quantified using HPLC tandem mass spectrometry coupled with a CHIROBIOTIC column. Results: Glioma tissues from 70 patients were analyzed – 52 with IDH MUT and 18 WT. 30 had matched serum samples. Using glioma tissues, rRS clearly distinguished MUT vs WT (median 574 vs 1.3, p < 1x10-9) with only three outliers. In contrast, rRS was not elevated in serum samples (median 1.5 vs 1.2, p = 0.13). Overall survival (OS) was significantly longer for MUT vs WT (median 178 vs 33 months, p < 1×10-7). Stratifying MUT by tissue rRS, median OS was 197, 178, 178 and 122 months for lowest to highest quartiles of rRS respectively. 1p19q codeletion status and tumor latency did not explain this trend, given rRS was similar in codeleted vs non-codeleted MUT, and similar in MUT operated < 3 vs ≥3 months from diagnosis. Progression-free survival results corresponded to OS. Conclusions: rRS from glioma tissues effectively differentiated MUT vs WT, whereas serum samples were unreliable. Unlike current methods, tissue rRS enables real-time determination of IDH status, and thus may guide clinical practice such as extent of surgical resection intraoperatively and upfront selection of adjuvant therapy. rRS potentially stratifies survival within MUT patients, providing detailed correlative information.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.269
GPT teacher head0.544
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes2
Has abstractyes

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