DUSP6 Mediates Resistance to JAK2 Inhibition and Drives Myeloproliferative Neoplasm Disease Progression
Bibliographic record
Abstract
Abstract Myeloproliferative neoplasms (MPNs) are clonally derived from hematopoietic stem/progenitor cells (HSPCs) and typically harbor somatic mutations in one of three genes (JAK2, CALR, MPL) leading to aberrant activation of JAK-STAT signaling. While small molecule inhibitors of JAK2 provide symptomatic benefit for MPN patients, they do not eradicate the underlying malignant clone, nor do they prevent disease progression. Chronic MPNs exhibit a propensity for transformation to secondary acute myeloid leukemia (sAML), for which the underlying mechanisms remain poorly understood, resulting in limited treatment options and dismal clinical outcomes. To understand alterations to the transcriptional landscape underlying MPN disease progression, we performed bulk transcriptome profiling on myelofibrosis (MF) and sAML patient CD34+ HSPCs. Differential gene expression analysis revealed upregulation of dual-specificity phosphatase 6 (DUSP6), which encodes a MAPK phosphatase that regulates ERK signaling, in sAML CD34+ cells. Elevated DUSP6 protein expression accompanying disease progression was confirmed via MPN patient bone marrow immunofluorescence and imaging mass cytometry analysis. We performed further single cell RNA sequencing (scRNA-seq) in conjunction with TotalSeq surface protein marker detection on more than 50,000 sorted CD34+ cells of serial samples from three patients at chronic MPN and sAML stages, and two healthy controls, which revealed DUSP6 among the top 21 genes elevated in all three paired samples across disease progression. Subsequent differentiation trajectory pseudotime analysis demonstrated concomitant elevation of DUSP6 across state trajectories and disease progression. Genetic and pharmacologic targeting of DUSP6 followed by biochemical and mass cytometry analysis identified signaling inhibition through S6 and JAK/STAT, establishing them as novel, non-canonical effectors of DUSP6. DUSP6 inhibition also led to potent suppression of cell proliferation, induction of apoptosis and cell cycle arrest, and reduction of inflammatory cytokine production in primary MPN samples. Furthermore, ectopic DUSP6 expression augmented proliferation and mediated JAK2 inhibitor resistance, while DUSP6 inhibition reduced colony-forming potential of JAK2 inhibitor-persistent patient cells. Mechanistically, DUSP6 suppression dampened S6 signaling via inhibition of RSK1 (RPS6KA1), which we identified as a second indispensable candidate associated with poor clinical outcome via Kaplan-Meier overall survival (Log-rank p = 0.0005) and multivariate (RPS6KA1 expression hazard ratio = 1.60, 95% confidence interval: 1.10, 2.34) analyses of the TCGA LAML cohort. Strong correlation was observed (r = 0.68; p = 0.0009) between RPS6KA1 and DUSP6 expression in CD34+ HSPCs, and pharmacologic inhibition of RSK1 with BI-D1870 suppressed proliferation and colony formation across AML cell lines and primary samples. DUSP6 inhibition in vivo via small molecule inhibitor BCI resolved pathologically elevated hematocrit and white blood cell counts and reduced splenomegaly in Jak2 V617F knock-in mice. In the MPL W515L retroviral transplant model, BCI suppressed leukocytosis while reducing reticulin fibrosis and prolonging survival. In patient-derived xenograft (PDX) model of NSGS mice engrafted with sAML patient CD34+ cells, BCI treatment or DUSP6 knockdown reduced peripheral blood hCD45+ engraftment. Importantly, BCI treatment did not pathologically cause cytopenias or decrease spleen weights in wild-type mice, nor did it reduce hCD45+ engraftment in NSGS PDX mice engrafted with healthy donor CD34+ cells. Lastly, NSGS PDX mice engrafted with MF patient CD34+ cells ectopically expressing DUSP6 demonstrated marked leukocytosis, splenomegaly, and early lethality. These findings underscore DUSP6 in driving MPN disease progression and therapeutic resistance, and highlight the DUSP6-RSK1 axis as a novel, druggable pathway in myeloid malignancies. Figure 1 Figure 1. Disclosures Oh: Abbvie: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Membership on an entity's Board of Directors or advisory committees; Celgene Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Constellation: Membership on an entity's Board of Directors or advisory committees; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees; Disc Medicine: Membership on an entity's Board of Directors or advisory committees; Geron: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees; Kartos Therapeutics: Membership on an entity's Board of Directors or advisory committees; PharamaEssentia: Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Membership on an entity's Board of Directors or advisory committees.
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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 | 0.000 | 0.000 |
| 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".