Molecular pathogenesis of the myeloproliferative neoplasms
Bibliographic record
Abstract
The Philadelphia negative myeloproliferative neoplasms (MPN) compromise a heterogeneous group of clonal myeloid stem cell disorders comprising polycythaemia vera, essential thrombocythaemia and primary myelofibrosis. Despite distinct clinical entities, these disorders are linked by morphological similarities and propensity to thrombotic complications and leukaemic transformation. Current therapeutic options are limited in disease-modifying activity with a focus on the prevention of thrombus formation. Constitutive activation of the JAK/STAT signalling pathway is a hallmark of pathogenesis across the disease spectrum with driving mutations in JAK2, CALR and MPL identified in the majority of patients. Co-occurring somatic mutations in genes associated with epigenetic regulation, transcriptional control and splicing of RNA are variably but recurrently identified across the MPN disease spectrum, whilst epigenetic contributors to disease are increasingly recognised. The prognostic implications of one MPN diagnosis may significantly limit life expectancy, whilst another may have limited impact depending on the disease phenotype, genotype and other external factors. The genetic and clinical similarities and differences in these disorders have provided a unique opportunity to understand the relative contributions to MPN, myeloid and cancer biology generally from specific genetic and epigenetic changes. This review provides a comprehensive overview of the molecular pathophysiology of MPN exploring the role of driver mutations, co-occurring mutations, dysregulation of intrinsic cell signalling, epigenetic regulation and genetic predisposing factors highlighting important areas for future consideration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".