Detection of IDH1/IDH2 Mutations Using Multiplex PCR/Single-base Extension in Formalin-Fixed, Paraffin-Embedded Glioma Tissues
Bibliographic record
Abstract
Isocitrate dehydrogenase (IDH) has an important role in a key step of the citric acid cycle. Recently, it has been found that mutants of either of the 2 IDH genes could be found in several cancers, including astrocytic and oligodendroglial neoplasms, and that the mutations result in the generation of a dominant-negative inhibitor of IDH dimer activity. These mutations are typically found in codon 132 in exon 4 of IDH1 and 172 in exon 4 of IDH2. Of the mutations in IDH1, 90% are of a single variant (R132H). IDH mutation detection has a prognostic role in gliomas. We developed a simple, PCR-based assay to detect IDH1/2 mutations in gliomas. This protocol combines a single, multiplexed PCR reaction, using gene specific primers, with a single, multiplexed, SNaPshot (Applied Biosystems, Carlsbad CA) reaction. The products are then resolved by capillary electrophoresis. Multiplex PCR products serve as template for SNaPshot reactions using gene-specific, single-base extension primers. As controls to demonstrate the ability of our test to visualize common IDH1 and IDH2 mutants, we also cloned known IDH1/2 mutations into plasmids using oligonucleotide-based, site-directed mutagenesis. In a blinded validation survey, we evaluated 30 glioma specimens that had been previously tested by PCR DNA sequencing. Concordance was 100%. The common R132H IDH1 mutation and a single R132S IDH1 mutation were identified in our validation samples. Our assay yields several improvements over genomic PCR sequencing. Data were faster and easier to interpret than from sequencing. Test results could be obtained in 1 day, from DNA extraction to analysis. Equivalent results were observed when comparing DNA extracted from formalin-fixed, paraffin-embedded tissue to those extracted from frozen tissue samples. In addition, the simplicity of this test allows for the adaptation of this assay to automation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 0.001 |
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".