Detection of JAK2 V617F mutation in patients with myeloproliferative disorders using real-time PCR
Bibliographic record
Abstract
A41 Our molecular diagnostic laboratory is using real-time PCR and conventional PCR to identify 25 translocations and mutations associated with sarcomas, leukemias, and lymphomas. Recently, a somatic point mutation in the Janus kinase 2 (JAK2) gene has been identified in patients with BCR/ABL-negative myeloproliferative disorders (MPD) in most cases of polycythemia vera and in a subset of patients with essential thrombocythemia. To detect the JAK2 V617F mutation in MPD patients, we have developed a fast real-time PCR assay that does not require subsequent sequencing. DNA is purified from whole blood and/or bone marrow, PCR is performed on a LightCycler instrument using hybridization probes, and genotype is identified from the melting curve analysis. In addition to being highly specific, melting curve analysis using hybridization probes allows to semi-quantify JAK2 V617F and wild-type alleles. In our cohort of MPD patients, we have identified 26% homozygous and 40% heterozygous for the JAK2 V167F mutation. The proportion of mutant allele varies from 10% to 70% in heterozygous. Although JAK2 V617F mutation has been associated mostly with BCR/ABL-negative MPD, we have identified a patient carrying both the JAK2 V617F mutation (60% of mutant allele) and the BCR-ABL b3;2a translocation associated with chronic myelogenous leukemia (ratio BCR/ABL over G6PDH of 9%). BCR/ABL-negative MPD patients can undergo complete remission after bone marrow transplantation; future work will then study if reappearance of JAK2 V617F mutation in some patients correlate with disease relapse and how JAK2 V617F allele proportion correlate with disease progression. In conclusion, we demonstrated that the JAK2 V617F mutation can be detected by a fast, specific, and semi-quantitative assay based on real-time PCR. This assay simplifies the diagnostic of MDP, especially of polycythemia vera, and could potentially be used to monitor response to therapy.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".