The Transcriptional Profile of PV Displays Limited Similarity to EPO Stimulated Progenitor Cells: Evidence That JAK2 V617F Confers a Novel Program to Malignant Hematopoietic Stem Cells.
Bibliographic record
Abstract
Abstract Polycythemia vera (PV) is a myeloproliferative disorder characterized by accumulation of mature red cells (RBC). Recent evidence indicates that a mutation of JAK2, V617F, is found in virtually all patients with PV. This allele encodes a constitutively active form of JAK2 and represents a likely pathogenic lesion. JAK2 is required for normal RBC development and is activated by erythropoietin (EPO) during erythroid maturation. Hence the JAK2 mutation may phenocopy EPO stimulation of hematopoietic progenitor cells (HPC). This hypothesis predicts that gene expression profiles of EPO-stimulated normal human CD34+ cells should closely correlate with gene expression found in malignant PV progenitors. We tested this idea using our dataset of human HPC from 8 normals and 9 PV patients and a recently published data set (Ebert et al., Blood 2005) of normal human HPC treated with EPO. In addition, we examined our other data sets to obtain the murine transcriptional program of EPO stimulation, including BaF3-EPO-R cells, HCD-57 cells, fetal liver cells, and phenylhydrazine-primed splenic erythroblasts all treated with EPO. Using low sensitivity direct sequencing we detected the JAK2 V617F mutation in one third of our PV patients and are now using high sensitivity allele-specific PCR to document the mutation in all patients. Further, the gene expression profiles across all of our PV specimens is uniform; hence the PV progenitors in this study are likely representative of JAK2 mutant cells. The human and mouse experiments, pre- and post-EPO treatment, were queried to produce a transcriptional profile of EPO stimulation, i.e. genes that significantly (p≤0.05) changed at least 2x between no drug and EPO treatment after multiple testing correction. A support vector machine selected 31 of 47 EPO- regulated human genes which correctly identified 16 of 17 samples as PV or normal upon leave-one-out cross-validation. This shows similarities exist between normal EPO/JAK2 signaling and PV. However the gene expression signature of EPO stimulated progenitors had very little overlap with the expression profile of PV specimens. Only 3 genes were present in both sets, KLF4, RGC32, SKIP1. Even when the restrictions were eased to a 1.5x change between PV and normal, only 5 genes were common to the PV and EPO sets (KLF4, MCL1, RGC32, SUI1, SKIP1), representing 2.6% of the total. Interestingly, these five genes alone are sufficient to predict EPO treatment in humans and PV status. Analysis of the murine data set yielded an even smaller overlap with PV, 1.1% (2 genes of 177). 38 EPO-regulated murine genes, distinct from the human set, predicted all PV samples correctly and performed with 60% accuracy on cross-validation. We conclude that expression of 5 genes may represent the common action of mutant and wild-type JAK2. The divergence in gene expression pattern between EPO treated cells and PV indicates that the JAK2 mutation in PV progenitors also affects genes distinct from the usual EPO targets during normal hematopoiesis. Genes affected by mutant JAK2 in PV may represent novel therapeutic targets in this disease. We are further testing this hypothesis by expression profiling of normal CD34+ cells expressing the mutant JAK2.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".