The myeloproliferative neoplasms (MPN) frequently progress to blast phase disease, an aggressive form of acute myeloid leukemia. To identify genes that suppress disease progression, we performed a focused CRISPR/Cas9 screen and discovered that depletion of LKB1/Stk11 led to enhanced in vitro self-renewal of murine MPN cells. Deletion of Stk11 in a mouse MPN model caused rapid lethality with enhanced fibrosis, osteosclerosis, and an accumulation of immature cells in the bone marrow, as well as enhanced engraftment of primary human MPN cells in vivo. LKB1 loss was associated with increased mitochondrial reactive oxygen species and stabilization of HIF1α, and downregulation of LKB1 and increased levels of HIF1α were observed in human blast phase MPN specimens. Of note, we observed strong concordance of pathways that were enriched in murine MPN cells with LKB1 loss with those enriched in blast phase MPN patient specimens, supporting the conclusion that STK11 is a tumor suppressor in the MPNs.

Significance:

Progression of the myeloproliferative neoplasms to acute myeloid leukemia occurs in a substantial number of cases, but the genetic basis has been unclear. We discovered that loss of LKB1/STK11 leads to stabilization of HIF1a and promotes disease progression. This observation provides a potential therapeutic avenue for targeting progression.

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Philadelphia-negative myeloproliferative neoplasms (MPN) are a group of blood stem cell disorders affecting the myeloid lineage that include polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). Each MPN phenotype is characterized by increased proliferation of differentiated myeloid lineages including red blood cells, megakaryocytes, and granulocytes and is caused by driver mutations in JAK2, MPL, and CALR that constitutively activate the JAK/STAT pathway. Patients with MPN transform to acute leukemia with rates of 10% to 20%, 2% to 5%, and 1% to 4% in PMF, PV, and ET, respectively (1–4). Post-MPN acute myeloid leukemia (AML), also known as blast phase MPN (MPN-BP), is an aggressive malignancy with a median survival of three to five months (5–7). Although several studies involving sequencing of MPN and MPN-BP samples identified mutations or variants in several genes related to myeloid malignancies such as ASXL1, EZH2, SRSF2, LNK, TET2, and TP53 (3, 8) and recurring deletions of JARID2 (9), the mechanisms of transformation remain largely unclear.

MPN-BP is characterized by the presence of 20% or more peripheral blood or bone marrow blasts, suggesting the emergence of a malignant myeloid clone with impaired differentiation and increased self-renewing capacity consistent with the transformation to AML. To better understand the genetic alterations that cause a switch from the chronic phase to MPN-BP, we performed a focused CRISPR/Cas9 screen to identify tumor suppressor genes whose deletion enhanced self-renewal of hematopoietic stem and progenitor cells (HSPC) harboring MPN driver mutations in a serial replating assay. We identified liver-inducible kinase (LKB1)/serine threonine kinase 11 (STK11) as a driver of leukemic transformation in MPN and reveal that its downregulation is accompanied by an increase in mitochondrial reactive oxygen species (ROS) and stabilization of hypoxia-inducible factor 1 alpha (HIF1α). These results are surprising because, although LKB1 is widely known as a tumor suppressor in solid cancer, its loss leads to depletion of HSPCs and bone marrow failure rather than expansion (10–12). Our results suggest that enhanced JAK/STAT signaling is required for the survival and subsequent transformation of hematopoietic cells lacking LKB1.

A Focused CRISPR/Cas9 Screen Reveals Stk11 Loss as a Driver of HSPC Self-Renewal

To investigate tumor suppressor genes that drive leukemic transformation in cells with activated JAK/STAT signaling, we performed a positive CRISPR/Cas9 screen by transducing two curated lentiviral single-guide RNA (sgRNA) libraries, each containing four sgRNAs targeting ∼100 unique annotated tumor suppressors and several MPN-associated genes as well as 50 nontargeting control sgRNAs (Supplementary Table S1), in Jak2V617F/Vav-Cre c-Kit+ HSPCs with a Lox-STOP-Lox allele of Cas9 (Cas9lsl) and assessed their serial replating capacity in methylcellulose media (Fig. 1A). Trp53 was intentionally omitted from both libraries due to previous reports already identifying it as a transformation factor (8) for JAK2-mutant MPNs. Transduction of either library 1 or 2 in Vav-Cre/Cas9lsl lin HSPCs did not result in enhanced replating (Supplementary Fig. S1A), whereas CRISPR editing of Trp53 in Jak2V617F/Vav-Cre/Cas9lsl c-Kit+ HSPCs as a positive control resulted in enhanced serial replating as expected (Supplementary Fig. S1B and S1C). By contrast, transduction of library 2 led to robust serial replating of JAK2V617F cells over five generations, whereas transduction of library 1 or a control empty vector failed to induce this phenotype (Fig. 1B). Next-generation sequencing (NGS) of DNA obtained from cells at plating 1 as a baseline versus plating 3 showed enrichment of all four guides present in the library that target serine/threonine kinase 11 (Stk11), which encodes LKB1 (Fig. 1C), whereas two sgRNAs targeting Stk11 were significantly enriched at plating 5 (Supplementary Table S2). Although there were nine other genes that had significant guide enrichment in platings 3 and/or 5 none of these genes showed enrichment of more than one guide (Supplementary Table S2). Of note, out of 50 nontargeting sgRNAs in library 2, only one was significantly enriched at plating 3, but was not enriched at plating 5. To confirm the Stk11 result of the screen, we electroporated ribonucleotide complexes (RNP) containing Cas9 and two independent sgRNAs targeting Stk11 in Jak2V617F/Vav-Cre c-Kit+ HSPCs and performed a serial replating assay. Cells electroporated with either Stk11 sgRNA induced a strong serial replating over six generations, whereas cells electroporated with the control sgRNA failed to replate (Fig. 1D). To evaluate the efficiency of sgRNA targeting, we sequenced a region of Stk11 flanking the Cas9 cut site and performed Inference of CRISPR Edits (ICE) analysis (13) on the resulting chromatograms from Sanger sequencing. The percentage of productive insertions/deletions increased from plating 1 to plating 5, indicating progressive enrichment of Stk11 knockout cells during replating (Fig. 1E). Finally, we performed Western blot analysis for LKB1 levels in cells at different stages and observed strong downregulation of LKB1 expression (Fig. 1F). Together, these results show that loss of the tumor suppressor Stk11 is a driver of in vitro self-renewal in Jak2V617F MPN cells.

Figure 1.

CRISPR/Cas9 screening reveals loss of LKB1 is a driver of serial replating of Jak2V617F hematopoietic cells. A, Schematic of the experimental workflow. MOI, multiplicity of infection. B, Number of hematopoietic colonies formed at each generation of plating for Jak2V617/Cas9/Vav-Cre cells infected with library 1 or 2. The average of two biological replicates ± SD is shown. C, sgRNA enrichment of plating 1 versus 3 or 5 as determined by DNAsequencing. sgRNAs targeting Stk11 are highlighted in red. The P value represents significance by Fisher exact test. D, Number of hematopoietic colonies formed over six generations for Jak2V617F/Vav-Cre cells targeted with two independent sgRNA targeting Stk11. The average ± SEM are shown; n = 3.E, ICE analysis of the extent of Stk11 targeting in cells from B. F, Western blot for LKB1 levels at the various stages of replating of Jak2V617F/Vav-Cre cells electroporated with RNPs against Stk11. GRB2 is displayed as the loading control. G, Schematic of the experimental workflow for the MPLW515L studies. H, Number of hematopoietic colonies formed for up to six generations for murine Stk11-floxed HSPCs expressing various combinations of MPLW515L and Cre. The average ± SD are shown, n = 6. CFU, colony-forming units. I, MDS plot of RNA-sequencing (RNA-seq) data comparing MPLW515L/Stk11-null to MPLW515L/Stk11+/+ cells after one, three, and six rounds of plating. J, Unsupervised clustering analysis comparing RNA-seq data from cells collected after the first round of plating for control and MPLW515L/Stk11+/+ and at first, third, and sixth plating for MPLW515L/Stk11-null cells. K, Mean average (MA) plot of the comparison MPLW515L/Stk11-null versus MPLW515L/Stk11+/+ at plating one showing differentially expressed genes. CPM, counts per million. L and M, Pathways that are correlated with the MPLW515L/Stk11-null phenotype (L) or correlated with the MPLW515L phenotype (M) by GSEA.

Figure 1.

CRISPR/Cas9 screening reveals loss of LKB1 is a driver of serial replating of Jak2V617F hematopoietic cells. A, Schematic of the experimental workflow. MOI, multiplicity of infection. B, Number of hematopoietic colonies formed at each generation of plating for Jak2V617/Cas9/Vav-Cre cells infected with library 1 or 2. The average of two biological replicates ± SD is shown. C, sgRNA enrichment of plating 1 versus 3 or 5 as determined by DNAsequencing. sgRNAs targeting Stk11 are highlighted in red. The P value represents significance by Fisher exact test. D, Number of hematopoietic colonies formed over six generations for Jak2V617F/Vav-Cre cells targeted with two independent sgRNA targeting Stk11. The average ± SEM are shown; n = 3.E, ICE analysis of the extent of Stk11 targeting in cells from B. F, Western blot for LKB1 levels at the various stages of replating of Jak2V617F/Vav-Cre cells electroporated with RNPs against Stk11. GRB2 is displayed as the loading control. G, Schematic of the experimental workflow for the MPLW515L studies. H, Number of hematopoietic colonies formed for up to six generations for murine Stk11-floxed HSPCs expressing various combinations of MPLW515L and Cre. The average ± SD are shown, n = 6. CFU, colony-forming units. I, MDS plot of RNA-sequencing (RNA-seq) data comparing MPLW515L/Stk11-null to MPLW515L/Stk11+/+ cells after one, three, and six rounds of plating. J, Unsupervised clustering analysis comparing RNA-seq data from cells collected after the first round of plating for control and MPLW515L/Stk11+/+ and at first, third, and sixth plating for MPLW515L/Stk11-null cells. K, Mean average (MA) plot of the comparison MPLW515L/Stk11-null versus MPLW515L/Stk11+/+ at plating one showing differentially expressed genes. CPM, counts per million. L and M, Pathways that are correlated with the MPLW515L/Stk11-null phenotype (L) or correlated with the MPLW515L phenotype (M) by GSEA.

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LKB1 Loss in MPN Cells Induces Transcriptional Changes Related to Hypoxia, Oxidative Phosphorylation, and the Stem Cell Program

Hematopoietic-specific depletion of Stk11 in mice leads to bone marrow failure due to an initial burst of proliferation of Stk11-deficient hematopoietic stem cells (HSC) followed by their depletion (10–12). To confirm the phenotype induced by Stk11 loss with a different MPN driver mutation, we obtained Stk11fl/fl mice (12). We cotransduced Stk11fl/fl c-Kit+ HSPCs with a retroviral vector encoding the MPN driver mutation MPLW515L and an mCherry reporter (Migr1-MPLW515L-mcherry) along with a retroviral vector encoding CRE recombinase and a GFP reporter (Migr1-CRE-GFP) to induce Stk11 deletion, sorted mCherry-GFP double-positive cells, and cultured them in methylcellulose media (Fig. 1G). As with the Jak2V617F genotype, hematopoietic progenitor cells expressing MPLW515L alone failed to serially replate (Fig. 1H). By contrast, homozygous deletion of Stk11 in combination with MPLW515L (MPLW515L/Stk11Δ/Δ) led to a robust replating phenotype similar to the Jak2V617F/Stk11 targeted cells, whereas those with empty vector control (CTRL), Stk11 deletion alone, or MPLW515L overexpression alone failed to replate (Fig. 1H). Of note, MPLW515LStk11Δ/Δ cells also grew in cytokine-free methylcellulose media and in liquid culture in a cytokine-independent fashion with an immature morphology when transferred from cytokine-free methylcellulose to liquid culture (Supplementary Fig. S2A–S2C).

To investigate the transcriptional changes that characterize the replating phenotype, we performed RNA sequencing (RNA-seq) on CTRL and MPLW515L cells at plating 1 along with MPLW515L/Stk11Δ/Δ cells at platings 1, 3, and 6. Multidimensional scaling (MDS) plot showed a distinct clustering of MPLW515L/Stk11Δ/Δ from CTRL and MPLW515L cells (Fig. 1I). Differential expression analysis across all the conditions resulted in 5,463 differentially expressed genes, and unsupervised hierarchical clustering of these genes highlighted a transcriptional signature separated from CTRL and MPLW515L cells (Fig. 1J). To identify genes specifically associated with deletion of Stk11 in the context of JAK/STAT activation, we performed differential expression analysis on MPLW515LStk11Δ/Δ cells versus MPLW515L cells at plating 1. Stk11 deletion had a profound effect on the transcriptome of MPLW515L cells and resulted in 1,527 genes being differentially expressed (Fig. 1K; Supplementary Table S3). Gene set enrichment analysis (GSEA) revealed enrichment of pathways related to hypoxia, embryonic stem cells, and regulation of oxidative phosphorylation (OXPHOS) in the MPLW515L/Stk11Δ/Δ phenotype, whereas pathways related to myeloid differentiation, maturation of hematopoietic cells, and IL6 production were enriched in the MPLW515L MPN cells (Fig. 1L and M; Supplementary Fig. S3A and S3B). Full GSEA pathway analysis is available in Supplementary Table S4. Together, these data demonstrate that loss of Stk11 results in the same self-renewal phenotype in both JAK2 and MPL-mutant settings and induces profound transcriptional changes that separate immature MPLW515LStk11Δ/Δ cells from the differentiated state of MPLW515L MPN cells.

Enhanced Self-Renewal of Stk11-Deficient Cells with Activated JAK/STAT Signaling Is Associated with HIF1α Stabilization

We then investigated the mechanism by which loss of LKB1 contributes to enhanced self-renewal. First, we collected cells from the first-generation methylcellulose cultures of murine HSPCs of four different genotypes: wild-type (WT), MPLW515L, Stk11Δ/Δ, and MPLW515L/Stk11Δ/Δ. Whole-cell lysates were then assessed for levels of LKB1 and its well-studied downstream substrate AMPK (Fig. 2A). Previous studies have shown that loss of LKB1 did not induce HSC failure through AMPK (10–12); therefore, we were not surprised to see that levels of total AMPK and phospho-AMPK (pAMPK) at threonine 172 were not substantially depleted by loss of Stk11. Of note, overexpression of MPLW515L also did not result in changes in AMPK levels, nor did the combination of Stk11 loss and MPLW515L expression.

Figure 2.

Stabilization of HIF1α promotes colony formation in cells with MPLW515L that are deficient for Stk11. A, Western blot analysis of protein levels in hematopoietic cells after the first plating. GRB2 is shown as the loading control. n = 2. B, Western blot analysis of HIF1α hydroxylation andPHD2 after the first plating. Densitometry is shown relative to WT. GRB2 is displayed as the loading control. n = 2. C, Colony-forming units (CFU) over sixgenerations in WT cells transduced with MPLW515L, HIF1α WT, HIF1α PP/AA-mutant and the various combinations. The average ± SEM are shown; n = 2.D, Comparison of mitoROS in cells at platings 1, 3, and 6. Representative flow and the average ± SEM are shown. MFI, mean fluorescence intensity. E, Left, Western blot analysis of protein levels in MPLW515L/Stk11-null cells after treatment with various small molecules known to target HIF1α stabilization. Actin is shown as a loading control. Right, effect of small molecules on colony formation capacity of MPLW515L/Stk11-null cells. The average ± SD are shown. P values by Dunnet multiple comparisons test against DMSO control. F, Effect of N-acetylcysteine (NAC) on the colony replating phenotype. No significant differences were observed. The average ± SEM are shown; n = 3.

Figure 2.

Stabilization of HIF1α promotes colony formation in cells with MPLW515L that are deficient for Stk11. A, Western blot analysis of protein levels in hematopoietic cells after the first plating. GRB2 is shown as the loading control. n = 2. B, Western blot analysis of HIF1α hydroxylation andPHD2 after the first plating. Densitometry is shown relative to WT. GRB2 is displayed as the loading control. n = 2. C, Colony-forming units (CFU) over sixgenerations in WT cells transduced with MPLW515L, HIF1α WT, HIF1α PP/AA-mutant and the various combinations. The average ± SEM are shown; n = 2.D, Comparison of mitoROS in cells at platings 1, 3, and 6. Representative flow and the average ± SEM are shown. MFI, mean fluorescence intensity. E, Left, Western blot analysis of protein levels in MPLW515L/Stk11-null cells after treatment with various small molecules known to target HIF1α stabilization. Actin is shown as a loading control. Right, effect of small molecules on colony formation capacity of MPLW515L/Stk11-null cells. The average ± SD are shown. P values by Dunnet multiple comparisons test against DMSO control. F, Effect of N-acetylcysteine (NAC) on the colony replating phenotype. No significant differences were observed. The average ± SEM are shown; n = 3.

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Given the gene-expression data that revealed that there was enrichment of the hypoxia gene set by GSEA and substantial upregulation of hexokinase II (HKII), we assessed the expression of these factors in cells of the various genotypes. Consistent with the RNA-seq data, we saw that HKII was markedly upregulated by deletion of Stk11 and expression of MPLW515L (Fig. 2A). In accordance with GSEA, we also observed that HIF1α, the key transcriptional regulator of HKII, was also substantially elevated in the LKB1-deficient cells that expressed MPLW515L. Moreover, stabilization of HIF1α persisted even in cells expanded in liquid culture (Supplementary Fig. S4). These results strongly suggest that activation of JAK/STAT signaling in combination with Stk11 deletion leads to stabilization of HIF1α under normoxic conditions and increases its downstream target gene expression. To investigate how HIF1α is stabilized in MPLW515L/Stk11Δ/Δ cells, we assayed for levels of prolyl hydroxylase 2 (PHD2) and hydroxylated HIF1α. In the mutant cells, hydroxylation of HIF1α was reduced compared with controls, whereas PHD2 was largely unchanged, suggesting an impairment of PHD activity in these cells (Fig. 2B).

Next, to determine whether stabilization of HIF1α is sufficient to promote enhanced self-renewal, we transduced WT murine bone marrow cells with combinations of MPLW515L, WT HIF1α, and an allele of HIF1α (HIF1αPP/AA) that cannot be hydroxylated and targeted for VHL-mediated ubiquitination (14). Consistent with a key role for HIF1α in the replating phenotype of cells with activated JAK/STAT signaling, we found that HIF1α stabilization was sufficient to confer serial replating of MPLW515L cells with WT STK11 expression (Fig. 2C). Together, these data confirm that HIF1α stabilization is sufficient for enhanced self-renewal of cells expressing MPLW515L. Prior studies have indicated that mitochondrial function through OXPHOS and production of mitochondrial reactive oxygen species (mitoROS) has been linked to the stabilization of HIF1α (15–17). Consistent with our prediction that HIF1α is stabilized through increased mitoROS, we also observed that the levels of mitoROS were elevated in Jak2V617F/Stk11Δ/Δ cells (Fig. 2D).

Finally, we assayed whether the replating of MPLW515L/Stk11Δ/Δ cells was sensitive to drugs known to target HIF1α through various mechanisms: disruption of HIF1α DNA binding (echinomycin), inhibition of mTOR (rapamycin), and reduction of mitoROS (mitotempo and S3QEL2). We observed that colony formation was inhibited by all four compounds, with the most significant decrease caused by mitotempo (Fig. 2E). Furthermore, targeting mitochondrial superoxide with mitotempo resulted in both strong inhibition of colony formation and HIF1α destabilization, whereas suppression of complex III–derived superoxide without alteration of OXPHOS with S3QEL2 (18) was still sufficient to inhibit colony formation and HIF1α protein stabilization (Fig. 2E). By contrast, sequestration of cellular ROS by N-acetylcysteine failed to impede replating (Fig. 2F). Taken together, our data are consistent with the model that loss of LKB1 leads to increased mitochondrial ROS signaling, which increases stabilization of HIF1α and enhances self-renewal.

Loss of Stk11 Transforms MPLW515L-Induced MPN to Spent Phase with Immature Blasts In Vivo

Serial replating is often used as an in vitro surrogate for leukemic transformation, but there are examples that show that these are not always inexorably linked. To study whether the potent replating phenotype seen with deletion of Stk11 is associated with in vivo transformation, we modeled heterozygous and homozygous loss in animal models of MPNs. First, to assess the effect of haploinsufficiency, we bred Jak2V617F inducible mice with Vav-Cre and the Stk11-floxed strains. As expected, Jak2V617F/Vav-Cre animals developed an MPN characterized by polycythemia and succumbed to disease by 220 days, with 50% lethality seen at 150 days (Supplementary Fig. S5A and S5B). Heterozygous loss of Stk11 in the presence of JAK2V617F did not appreciably alter the peripheral blood counts, but significantly impaired survival, with all mice succumbing to disease by 120 days with 50% lethality seen at day 75. Of note, heterozygous loss of Stk11 by itself had no phenotype, consistent with prior reports (10–12). Furthermore, activation of JAK/STAT signaling in vivo led to an increase in the LinSca+c-Kit+ HSC fraction and a modest decrease in LinSca+ progenitors, with no change in the proportion of myeloid progenitors; simultaneous deletion of one allele of Stk11 did not alter these phenotypes (Supplementary Fig. S5C–S5E).

Next, to assess the effect of complete LKB1 loss after MPN development, we collected HSPCs from Mx1-Cre/Stk11fl/fl or Stk11fl/fl control animals without Cre, transduced with MPLW515L-eGFP, and transplanted the cells to irradiated congenic animals (Fig. 3A). After three weeks, when the animals displayed features of an MPN, we confirmed that the presence of two floxed Stk11 alleles did not alter the engraftment efficiency (Supplementary Fig. S6A). We then treated the mice with three doses of pIpC to induce Stk11 deletion and observed that loss of Stk11 led to rapid lethality, reduced body and spleen weights, and pancytopenia (Fig. 3BD). Histologic analysis of the MPLW515L/Stk11Δ/Δ mice at the time of sacrifice revealed that loss of Stk11 was associated with much more intense fibrosis and osteosclerosis of the bone marrow compared with those mice that retained Stk11 (Fig. 3E and F). Furthermore, in contrast to the MPLW515L group, in which six of seven mice developed MPN, the majority of the MPLW515L/Stk11 mice (8 of 13) developed a malignancy characterized by a variably hypocellular bone marrow containing multiple foci of blasts comprising >20% of the mononuclear cells (Fig. 3G and H). This disease was also accompanied by minimal to no residual normal bone marrow hematopoiesis and splenic infiltration (Supplementary Fig. S6B). By contrast to the heterozygous deletion, complete absence of Stk11, confirmed by Western blot (Supplementary Fig. S6C), altered the HSPC populations, with a prominent decrease of LK and LSK compartments (Fig. 3I). This change was accompanied by an overall decrease in GFP+ hematopoietic cells in the bone marrow of MPLW515L/Stk11Δ/Δ mice (Supplementary Fig. S6D). Finally, we saw increased mitochondrial ROS in the whole bone marrow of MPLW515L/Stk11Δ/Δ mice (Fig. 3J). Although these data are somewhat reminiscent of the Stk11 knockout bone marrow aplasia phenotype, in the context of mutant JAK2 or MPL, loss of Stk11 recapitulates MPN disease progression in patients.

Figure 3.

Deletion of Stk11 drives progression of MPN in vivo. A, Schematic of experimental workflow. B, Survival curve of animals transplanted with Stk11fl/fl/MX1-Cre/MPLW515L or Stk11fl/fl/MPLW515L bone marrow cells. Yellow box indicates timing of pIpC treatment. P value (log-rank test) represents the difference in survival between the two groups of mice. C, Body and spleen weights of the two groups of mice. The average ± SD is shown, n = 7. D, White blood cell, platelet counts and hematocrit of mice in the two groups. P values were derived by Student t test with Benjamini and Yekutieli correction for multiple hypothesis testing. The average ± SEM is shown; n = 5. E and F, Representative hematoxylin and eosin– and reticulin-stained sections of the bone marrow recipient animals. Original magnification, ×100 (C, D). G, Higher power magnification of the bone marrow of two MPLW515L/Stk11Δ/Δ mice highlighting the accumulation of immature blasts. Original magnification, ×500. H, Comparison of the malignant phenotypes of MPLW515L versus MPLW515L/Stk11Δ/Δ mice. MPN, animals with a hypercellular bone marrow with mature cells; disease progression, animals with >20% blasts in an otherwise hypocellular bone marrow; bone marrow failure, animals with a hypocellular marrow and no blasts. Differences in the proportions of the phenotypes in the two groups were evaluated by Fisher exact test. I, Flow cytometry data for hematopoietic progenitor cells. The average ± SD is shown. P values by Student t test. J, Measurement of mitochondrial ROS in whole bone marrow cells from the mice as determined by intracellular flow cytometry. Representative plot (left) and individual data (right) are shown. The average ± SEM is shown. P value determined by Student t test.

Figure 3.

Deletion of Stk11 drives progression of MPN in vivo. A, Schematic of experimental workflow. B, Survival curve of animals transplanted with Stk11fl/fl/MX1-Cre/MPLW515L or Stk11fl/fl/MPLW515L bone marrow cells. Yellow box indicates timing of pIpC treatment. P value (log-rank test) represents the difference in survival between the two groups of mice. C, Body and spleen weights of the two groups of mice. The average ± SD is shown, n = 7. D, White blood cell, platelet counts and hematocrit of mice in the two groups. P values were derived by Student t test with Benjamini and Yekutieli correction for multiple hypothesis testing. The average ± SEM is shown; n = 5. E and F, Representative hematoxylin and eosin– and reticulin-stained sections of the bone marrow recipient animals. Original magnification, ×100 (C, D). G, Higher power magnification of the bone marrow of two MPLW515L/Stk11Δ/Δ mice highlighting the accumulation of immature blasts. Original magnification, ×500. H, Comparison of the malignant phenotypes of MPLW515L versus MPLW515L/Stk11Δ/Δ mice. MPN, animals with a hypercellular bone marrow with mature cells; disease progression, animals with >20% blasts in an otherwise hypocellular bone marrow; bone marrow failure, animals with a hypocellular marrow and no blasts. Differences in the proportions of the phenotypes in the two groups were evaluated by Fisher exact test. I, Flow cytometry data for hematopoietic progenitor cells. The average ± SD is shown. P values by Student t test. J, Measurement of mitochondrial ROS in whole bone marrow cells from the mice as determined by intracellular flow cytometry. Representative plot (left) and individual data (right) are shown. The average ± SEM is shown. P value determined by Student t test.

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Deletion of STK11 Enhances Engraftment of Human MPN Primary Cells

We next assayed the consequences of STK11 depletion of the growth of primary human MPN cells in vivo. We collected peripheral blood CD34+ from patients diagnosed with an MPN, introduced sgRNA targeting STK11 by nucleofection of RNP particles with Cas9, and then transplanted these cells to NOD scid gamma Il3/GM/SF (NSGS) animals (Supplementary Fig. S7A). After 12 weeks, we analyzed engraftment and evaluated the degree of editing of the human cells. Remarkably, we observed a consistent increase in engraftment of cells that showed successful STK11 gene editing (Supplementary Fig. S7B and S7C). This was reflected by an increase of human cells in peripheral blood for two of three patient samples, an increase of human CD45+ cells in the bone marrow, and an increase of total bone marrow cells (Supplementary Fig. S7D). These data indicate that loss of STK11 increases engraftment of human MPN cells in a xenotransplantation model.

Loss of STK11 Is Associated with Leukemia Progression in Human MPNs

We performed a number of studies to determine whether the murine phenotypes observed with Stk11 loss in cells with activated JAK/STAT signaling are relevant to patients. First, we assayed the mRNA expression level of STK11 in matched bone marrow specimens from patients at chronic and blast phase MPN. We observed downregulation of STK11 in all cases, with several patients showing more than a 50% decrease in expression at the blast phase (Supplementary Fig. S8). Second, to determine whether the level of LKB1 was altered with progression, we performed IHC on matched bone marrow samples from patients in chronic and blast phases. We observed a consistent and significant decrease in LKB1 staining in the bone marrow (Fig. 4A). Together, these results confirm that downregulation of LKB1 is a feature of MPN progression. We further stained the same chronic and blast phase sections for HIF1α and observed increased staining in the blast phase of the disease consistent with LKB1 loss, leading to the stabilization of HIF1α (Fig. 4B).

Figure 4.

LKB1 loss is a feature of human MPN. A, IHC for LKB1 in bone marrow sections from chronic and blast phase MPN. Left, representative IHC; right, area of staining quantification for five paired samples. Original magnification, ×400. The average ± SD are shown. *, P < 0.05 by Student t test. B, IHC for HIF1α in bone marrow sections from chronic and blast phase MPN. Left, representative IHC; right, area of staining quantification for five paired samples. Original magnification, ×400. The average ± SD are shown. *, P < 0.05 by Student t test. Images from A and B are from the same patient. C, PCA of RNA-seq data from five paired samples of chronic phase myelofibrosis (MF) and blast phase disease (AML). D, Unsupervised clustering of differentially expressed genes between chronic phase (MPN) and blast phase (AML).) E, GSEA of downregulated genes in mouse RNA-seq against human RNA-seq data set. F, GSEA revealing enrichment of a published hypoxia-related gene set (19). G, Comparison of normalized enrichment scores (NES) of all pathways between the mouse and human RNA-seq data sets. Significance at FDR < 0.1. H, Number of hematopoietic colonies generated by CD34+ progenitors from healthy donors treated with echinomycin, mitotempo, PP242, PT2977, and ruxolitinib at various concentrations versus DMSO control. Dotted line, mean of the DMSO control. **, P = 0.0044 for mitotempo at 500 μmol/L; ****, P < 0.0001 for ruxolitinib at 300 nmol/L. All comparisons by Dunnet multiple comparisons test versus DMSO control. I, Number of hematopoietic colonies generated by peripheral blood mononuclear cells from MPN-BP patient samples treated with echinomycin, mitotempo, PP242, PT2977, and ruxolitinib at various concentrations versus DMSO control. Dotted line, mean of the DMSO control. *, P = 0.0119; ***, P = 0.0001 for echinomycin at 500 pmol/L and 1 nmol/L, respectively. **, P = 0.0020; ****, P < 0.0001 for mitotempo at 200 and 500 μmol/L, respectively. *, P = 0.0312 for PP242 at 100 nmol/L. *, P = 0.0161 for PT2977 at 300 nmol/L. *, P = 0.0136 for ruxolitinib at 300 nmol/L. All comparisons by Dunnet multiple comparisons test against DMSO control. The average ± SEM are shown.

Figure 4.

LKB1 loss is a feature of human MPN. A, IHC for LKB1 in bone marrow sections from chronic and blast phase MPN. Left, representative IHC; right, area of staining quantification for five paired samples. Original magnification, ×400. The average ± SD are shown. *, P < 0.05 by Student t test. B, IHC for HIF1α in bone marrow sections from chronic and blast phase MPN. Left, representative IHC; right, area of staining quantification for five paired samples. Original magnification, ×400. The average ± SD are shown. *, P < 0.05 by Student t test. Images from A and B are from the same patient. C, PCA of RNA-seq data from five paired samples of chronic phase myelofibrosis (MF) and blast phase disease (AML). D, Unsupervised clustering of differentially expressed genes between chronic phase (MPN) and blast phase (AML).) E, GSEA of downregulated genes in mouse RNA-seq against human RNA-seq data set. F, GSEA revealing enrichment of a published hypoxia-related gene set (19). G, Comparison of normalized enrichment scores (NES) of all pathways between the mouse and human RNA-seq data sets. Significance at FDR < 0.1. H, Number of hematopoietic colonies generated by CD34+ progenitors from healthy donors treated with echinomycin, mitotempo, PP242, PT2977, and ruxolitinib at various concentrations versus DMSO control. Dotted line, mean of the DMSO control. **, P = 0.0044 for mitotempo at 500 μmol/L; ****, P < 0.0001 for ruxolitinib at 300 nmol/L. All comparisons by Dunnet multiple comparisons test versus DMSO control. I, Number of hematopoietic colonies generated by peripheral blood mononuclear cells from MPN-BP patient samples treated with echinomycin, mitotempo, PP242, PT2977, and ruxolitinib at various concentrations versus DMSO control. Dotted line, mean of the DMSO control. *, P = 0.0119; ***, P = 0.0001 for echinomycin at 500 pmol/L and 1 nmol/L, respectively. **, P = 0.0020; ****, P < 0.0001 for mitotempo at 200 and 500 μmol/L, respectively. *, P = 0.0312 for PP242 at 100 nmol/L. *, P = 0.0161 for PT2977 at 300 nmol/L. *, P = 0.0136 for ruxolitinib at 300 nmol/L. All comparisons by Dunnet multiple comparisons test against DMSO control. The average ± SEM are shown.

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Next, to better understand the molecular signatures associated with progression to the blast phase, we performed RNA-seq on matched peripheral blood mononuclear cells from 11 patients who progressed from chronic to blast phase MPN over a period of time ranging from 12 months to 13 years (Supplementary Table S5). We observed variable separation between the groups by principal component analysis (PCA) and unsupervised clustering (Supplementary Fig. S9A and S9B), but also some significant variability in both groups. The variation may be due to differences in the genetic composition at the blast stage among the patients, differential timing of disease evolution, or other factors. Both PCA and unsupervised clustering indicated a subset of chronic samples and a subset of blast samples that were clearly well separated from each other and a smaller number of samples from each group that exhibited intermediate, mixed expression patterns with features of both of the two well-separated subsets. We chose to remove those sample pairs for which one or both of the samples fell in the middle of the distribution with intermediate expression patterns where blast and chronic phase appeared to overlap and focused on five well-separated pairs (Fig. 4C) in order to avoid potential confounders that might not be related to the transition between these two disease states. Unsupervised clustering of these five pairs revealed major differences in the transcriptome between the chronic and blast phases of MPN (Fig. 4D). To compare the mouse transcriptome of cells overexpressing MPLW515L alone or with Stk11 loss and the human transcriptome of chronic and blast phase MPN, we performed GSEA using differentially expressed genes in the mouse MPLW515L versus MPLW515L/Stk11Δ/Δ comparison and in the human chronic phase versus blast phase MPN as gene sets. GSEA showed a strong concordance between human and mouse downregulated genes in the two data sets (Fig. 4E). Moreover, GSEA of a published gene set of hypoxia-induced genes in CD34+ cells (19) revealed enrichment of the hypoxia signature in human blast phase MPN (Fig. 4F). We also compared normalized enrichment scores from the GSEA in both comparisons. Strikingly, we observed extensive concordance between the pathways enriched in the blast phase of the disease and the ones in MPLW515L cells lacking Stk11, including pathways related to hypoxia, oxidative phosphorylation, and translation (Fig. 4G; Supplementary Table S6; Supplementary Fig. S10A and S10B). Finally, we returned to the 11 pairs and confirmed that there was extensive concordance between the pathways identified by GSEA in this complete set with the subset of five pairs, including the Manalo hypoxia gene set (Supplementary Fig. S9C and S9D). Together, these results confirm that loss of LKB1 is a common feature and potential driver of blast phase MPN progression in humans.

Finally, we treated primary MPN-BP samples and healthy CD34+ controls with drugs targeting the HIF, mTOR, and JAK/STAT pathways. Echinomycin and mitotempo were tested based on our observation that they led to destabilization of HIF1α in cells with MPLW515L that lacked LKB1 (Fig. 2E). We also tested PT2977, a small molecule that inhibits HIF2α (20), based on our observation that HIF2α is also stabilized by expression of MPLW515L in cells lacking Stk11 (Supplementary Fig. S11), as well as the mTOR pathway inhibitor PP242 and the JAK2 inhibitor ruxolitinib. With the exception of the highest doses of mitotempo and ruxolitinib, the drugs had no significant effect on colony formation by healthy CD34+ cells (Fig. 4H). By contrast, we observed consistent, dose-dependent inhibition of colony formation of the five primary MPN-BP specimens with all compounds, with the most striking effects caused by echinomycin and mitotempo (Fig. 4I). Of note, the cells were largely resistant to ruxolitinib with little discrimination between the MPN-BP and healthy CD34+ cells, consistent with the poor activity of this drug in patients with MPN-BP. Together, these results suggest that drugs which target the HIF pathway should be considered in this disease.

Loss of Stk11 is a key event in the progression of several solid malignancies as well as the dominant genetic mutation that leads to Peutz–Jeghers syndrome, characterized by increased risk of cancer development (21, 22). Prior studies have shown that loss of LKB1 in hematopoietic cells leads to an initial burst of proliferation of HSPCs followed by bone marrow failure as opposed to tumor development (10–12). Our findings that LKB1 loss imparts enhanced self-renewal of cells with activated JAK/STAT signaling strongly suggest that continued stimulation of this pathway allows for growth of HSPCs that lack LKB1. Of note, we did not detect mutations of STK11 in a cohort of patients with chronic or blast phase MPN; thus, downregulation of this tumor suppressor is likely the driving event.

Deletion of Stk11 in MPN cells induced expression of genes related to hypoxia and mitochondrial function. At the molecular level, stabilization of HIF1α under normal oxygen tension was a striking feature of Stk11-deleted MPN cells: this effect is shared with a mouse model of Peutz–Jeghers syndrome and mouse embryonic fibroblasts (23, 24). HIF1α is a transcriptional factor widely known for its role in solid malignancies, where it is consistently stabilized to promote tumor cell survival under hypoxia, tumor angiogenesis, and cell proliferation. In hematopoietic cells with enhanced JAK/STAT signaling, HIF1α promotes self-renewal of MPN cells likely through induction of genes related to stemness and proliferation. With respect to the link between LKB1 loss and HIF1 stabilization, increased mitoROS produced by the electron transport chain during OXPHOS has been linked to the stabilization of HIF1α in hypoxia (15, 16). We surmise that the observed increase in mitoROS impairs the normal prolyl hydroxylase function needed for VHL-mediated HIF1α ubiquitination and degradation by the proteasome.

A number of genetic alterations have been modeled in mouse models of MPN to mimic the alterations found in human MPN-BP, including loss of TP53 and JARID2. We show that deletion of Stk11 in the MPLW515L mouse model of MPN resulted in increased lethality with intense osteosclerosis and bone marrow fibrosis, accompanied by >20% immature blasts in an otherwise hypocellular bone marrow. Furthermore, deletion of STK11 in PMF patient samples and transplantation in NSGS recipients caused an increase in human myeloid cell engraftment, rarely seen in PMF xenografts, but no overt leukemia, suggesting that additional mutations present in the patient samples may cooperate with STK11 loss to produce a leukemic phenotype in humans.

Of note, the two libraries contained sgRNAs that target a number of genes associated with MPN progression and myeloid leukemia, including TET2, ASXL1, EZH2, and DNMT3A. It is notable that none of these sgRNAs were enriched in JAK2-mutant cells at platings 3 or 5. Although this may be a consequence of poor gene editing, it suggests that loss of these genes individually does not confer enhanced self-renewal and argues that STK11 is a more potent tumor suppressor in the MPNs.

Pseudohypoxia and stabilization of HIF1α have been recently described in MDS and MPN chronic phase (25, 26). With respect to the latter observation, there was only a modest increase in HIF1α levels and this was observed primarily in MPN cell lines that have been derived from patients with blast phase disease (27). Our IHC data reveal that HIF1α is present at the chronic phase, but that it is greatly increased at the blast phase, and our RNA-seq data demonstrate that HIF-induced pathways are markedly enriched in the leukemia phase.

Our findings provide insights into potential therapeutic approaches to better treat blast phase disease. Mice that lack HIF1α did not develop any detrimental phenotype under steady-state conditions, suggesting that it is a viable target (28). Moreover, recent developments in structure-based design approaches for drug discovery made possible the identification of a selective HIF2α antagonist, PT2399, which can dissociate HIF2α from its partner HIF1b, preventing its translocation to the nucleus (29). It has been reported that PT2399 provides on-target efficacy in both in vitro and in vivo preclinical studies of kidney cancer (29). Here we demonstrate that PT2977, a potent and selective analogue of PT2399 that is being investigated in an open-label phase II study of clear cell renal carcinoma, selectively inhibited colony formation of MPN-BP cells, which demonstrate stabilization of both HIF1α and HIF2a. Thus, our work lends a strong rationale for the use of HIF inhibitors in the leukemia phase of the MPNs.

Mice

All animals were of the C57BL/6 background. Jak2V617F knock-in (IMSR cat. # JAX:031658, RRID:IMSR_JAX:031658), Stk11 floxed (IMSR cat. # JAX:014143, RRID:IMSR_JAX:014143), Vav-Cre (IMSR cat. # JAX:008610, RRID:IMSR_JAX:008610), Mx1-Cre (IMSR cat. # JAX:003556, RRID:IMSR_JAX:003556), and Rosa26-Cas9 knock-in mice (IMSR cat. # JAX:026175, RRID:IMSR_JAX:026175) were purchased from The Jackson Laboratories. NSGS mice (IMSR cat. # JAX:013062, RRID:IMSR_JAX:013062) were purchased from The Jackson Laboratories. All mice were genotyped for the presence of the correct alleles by PCR. Animal studies were approved by the Northwestern University Institutional Animal Care and Use Committee (IACUC) and the Washington University IACUC.

Patient Samples

All specimens were studied with approval by the Institutional Review Boards of Northwestern University, Memorial Sloan Kettering, Washington University, and the Mayo Clinic. Patient data are provided in Supplementary Table S5.

CRISPR/Cas9 Screen

We generated a mouse sgRNA library for CRISPR-KO with 4× coverage targeted against the genes listed in the Uniprot Curated List of Tumor Suppressors as well as several MPN-associated genes (Supplementary Table S1). Given that loss of TP53 has been previously reported to be a transforming event in MPN to AML (8), we did not include this gene in the library. To perform the screen, lineage-negative HSPCs were isolated from bone marrow of Jak2V617F/Vav-Cre/Cas9 or Vav-Cre/Cas9 mice and transduced with either of two lentiviral sgRNA libraries or empty vector control at multiplicity of infection of 0.5. Transduced cells were selected from 24 hours with 2 μg/mL blasticidin (Sigma-Aldrich, 15205) and then plated on M3434 methylcellulose media (STEMCELL Technologies, M3434) with 1 μg/mL blasticidin. Every 7 days of culture, colonies were enumerated and cells were recovered for serial replating over five generations. DNA of cells from platings 1, 3, and 5 was extracted with the GenElute Mammalian Genomic DNA Miniprep Kit (Sigma-Aldrich, G1N70), and NGS was performed to evaluate enrichment of guide RNAs of platings 3 and 5 against plating 1 as a baseline. sgRNA enrichment was determined using PinAPL-Py (30). The same approach was used to target Jak2V617F/Vav-Cre/Cas9 bone marrow cells for Trp53 with the pLX-sgRNA vector (Addgene, 50662) containing an sgRNA with protospacer sequence 5′- CATAAGGTACCACCACGCTG -3′ targeting exon 6 of Trp53.

sgRNA/Cas9 RNP Delivery

Gene editing with Cas9 RNPs was achieved using the Alt-R CRISPR/Cas9 system (IDT). Briefly, equimolar amounts of CRISPR RNA (crRNA) targeting mouse Stk11 or/and trans-activating CRISPR RNA (trcrRNA) were annealed to form the gRNA. Nontargeting control crRNA #1 (IDT, #1072544) was used for control conditions. 18 pmol/L of recombinant Cas9 (IDT, 1081061) was combined with 22 pmol/L of gRNA to form RNP complexes, which were then delivered to c-Kit+ HSPCs using the NEON electroporation system (Thermo Scientific) with settings 1700 V, 20 ms, 1 pulse as described previously (31). After 24 hours, cells were plated in M3434 methylcellulose media (STEMCELL Technologies) and serially replated every 7 days over 6 generations.

Viral Transduction

High titer retrovirus was obtained by transfecting Platinum E cells (Cell Biolabs, RV-101, RRID:CVCL_B488) with 12 μg of retroviral construct using X-tremeGENE 9 transfection reagent (Roche, XTG9-RO) and collecting viral supernatant after 48 hours. Viral transduction was performed by spinoculation; 2–5 × 106 cells were mixed with virus and centrifuged for 90 minutes at 2,500 RPM at 32°C. Transduction efficiency was evaluated by flow cytometry after 24 hours of culture post-transduction.

Flow Cytometry

Bone marrow cells were isolated by crushing long bones with mortar and pestle in phosphate-buffered saline and filtered through a 70-μm nylon mesh to obtain a single-cell suspension. The HSPC compartment was analyzed using an anti-mouse V450-lineage-negative antibody cocktail (BD Biosciences; cat. #561301, RRID:AB_10611731), anti-mouse APC-CD117 (BD Biosciences; cat. #553356, RRID:AB_398536), and anti-mouse PE-Cy7-Sca1 (Thermo Fisher Scientific cat. #25-5981-82, RRID:AB_469669). Flow cytometry was performed on an LSRII flow cytometer (BD Biosciences). To measure mitoROS, whole bone marrow cells were incubated with 1.5 μmol/L mitoSOX (Thermo Scientific, M36008) in Earle Balanced Salt Solution (EBSS) supplemented with 0.5% BSA in a tissue culture incubator for 30 minutes, washed with EBSS, and immediately analyzed. For colony-forming assays with sorted cells, GFP+ mCherry+ double transduced cells were isolated 36 hours after transduction by FACS using a FACSAria II (BD Biosciences).

Transplantation

Bone marrow from Stk11fl/fl Mx1-Cre+ or Stk11fl/fl mice was isolated by crushing femurs and tibias and c-Kit+ cells isolated using magnetic enrichment (Miltenyi Biotec CD117 MicroBeads, mouse # 130-091-224) and cultured overnight in Stem Span media supplemented with 50 ng/mL mouse stem cell factor (SCF), 10 ng/mL mouse IL6, and 10 ng/mL mouse IL3. c-Kit+ cells were then transduced with the MPLW515L-GFP retrovirus by spinoculation and 0.4 × 106 GFP+ cells transplanted into lethally irradiated CD45.1 recipients. MPN development and engraftment was confirmed by CBC and flow cytometry at 3 weeks after transplantation, and pIpC injections were performed at 4 weeks after transplantation for 3 times at increasing dose every other day (2, 4, and 8 mg/kg).

Xenotransplantation

Human myelofibrosis (MF) peripheral blood mononuclear cells were isolated with Ficoll (GE Healthcare) and mononuclear cells were cryopreserved within 24 hours after collection in Hank's Balanced Salt Solution buffer (Corning; #21021CV) containing penicillin/streptomycin (100 Units/mL; Fisher Scientific; #MT30002CI), HEPES (10 μmol/L; Life Technologies; #15630080), and FBS (2%; Sigma; #14009C). For xenotransplantations, CD34+ HSPCs isolated were isolated using magnetic enrichment (Miltenyi Biotec; #130-100-453) from patients with JAK2V617F-positive (ID# 953 and 179) or CALRfs-positive (ID# 293) MF. Enriched CD34+ cells were incubated in SFEMII media (STEMCELL Technologies #09605) supplemented with penicillin–streptomycin (50 Units/mL), human SCF (50 ng/mL), human thrombopoietin (TPO; 50 ng/mL), and human FLT3 L (50 ng/mL). Twelve to 24 hours post-sort, CD34+ cells were nucleofected with Cas9/ribonucleorprotein complexed with sgRNA targeting STK11 as previously described (31). Forty-eight hours after nucleofection, these cells were transplanted into sublethally irradiated (200 rad) NSGS (IMSR; cat. #JAX:013062, RRID:IMSR_JAX:013062) mice via X-ray guided intratibial injections. Engraftment of human cells in xenotransplants was assessed by flow cytometry with antibodies targeting human CD45 (BioLegend; cat. #368511, RRID:AB_2566371) and mouse CD45 (BioLegend; cat. #103139, RRID:AB_2562341) cells.

RNA-seq and Data Analysis

The mRNA-seq on stranded libraries was conducted in the Northwestern University NUSeq Core Facility. Briefly, total RNA examples were checked for quality using RNA integrity numbers (RIN) generated from Agilent Bioanalyzer 2100. RNA quantity was determined with Qubit fluorometer. The Illumina TruSeq Stranded mRNA Library Preparation Kit was used to prepare sequencing libraries from 100 ng of high-quality RNA samples (RIN > 7). The kit procedure was performed without modifications. This procedure includes mRNA purification and fragmentation, cDNA synthesis, 3′ end adenylation, Illumina adapter ligation, library PCR amplification and validation. Illumina NextSeq 500 sequencer was used to sequence the libraries with the production of single-end, 75 bp reads at the depth of 20–25 M reads per sample.

Resulting raw sequencing data quality was assessed using FastQC and then the sequencing data were mapped to the mouse UCSC mm10 genome using the STAR RNA-seq aligner (STAR, RRID:SCR_015899). Feature and read summarization was performed using FeatureCounts from the Subread package (Subread, RRID:SCR_009803). Differential expression analysis was performed using EdgeR (EdgeR, RRID:SCR_012802) using the QLF test. GSEA (RRID:SCR_003199) was performed on normalized transcript per million (TPM) values from all samples using the GSEA software with the MSigDB gene sets. These RNA-seq data are available in the Gene Expression Omnibus (accession number GSE159737).

RNA-seq Analysis of Paired Patient Data

Raw reads were trimmed for quality (threshold of 15) and adapter sequences using version 0.4.5 of TrimGalore (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore), and then aligned to human assembly hg38 with STAR v2.4 using default parameters. Post-alignment quality and transcript coverage were assessed using the Picard tool CollectRNASeqMetrics (http://broadinstitute.github.io/picard/). Raw read count tables were created using HTSeq v0.9.1. Normalization and expression dynamics were evaluated with DESeq2 using the default parameters with library size factor normalization. Potential outliers were removed based on the separation of labeled sample pairs along PC1 of the PCA. GSEA (RRID:SCR_003199) was run using MSigDB v6 with “pre-ranked” mode and log2 fold change for pairwise comparisons. Pathway concordance between mouse and human was evaluated by linking gene set names with the normalized enrichment scores and highlighting pathways with FDR < 0.1 in either data set. The human sample RNA-seq data are available in dbGAP.

Western Blotting

Cells were lysed in RIPA lysis buffer supplemented with halt phosphatase inhibitor cocktail (Thermo Scientific, 78420) and complete protease inhibitor cocktail (Roche). Proteins were separated on a mini protean TGX 4%–15% polyacrylamide gel (Bio-Rad) and transferred on a PVDF membrane (Millipore). Antibodies included the following: anti-LKB1 (Cell Signaling Technology, cat. #3050, RRID:AB_823559, cat. #3047, RRID:AB_2198327), anti-HIF1α (Cell Signaling Technology, cat. #36169, RRID:AB_2799095), anti-HIF2α (Novus, cat. #NB100-122, RRID:AB_10002593), anti-HKII (Cell Signaling Technology, cat. # 2867, RRID:AB_2232946), anti-pAMPKa thr172 (Cell Signaling Technology, cat. #2535, RRID:AB_331250), anti-AMPKa (Cell Signaling Technology, cat. #5832, RRID:AB_10624867), anti-HIF1α-OH Pro564 (Cell Signaling Technology, cat. #3434, RRID:AB_2116958), anti-PHD2 (Novus Biologicals; cat. #NB100-137, RRID:AB_10003054), anti-GRB2 (BD Biosciences; cat. #610112, RRID:AB_397518), and anti-ACTB (Cell Signaling Technologies; cat. #3700, RRID:AB_2242334).

Histology

Mouse tissues for histology were fixed in 10% neutral buffered formalin for 24 hours and then processed for hematoxylin and eosin staining. IHC was performed using standard protocols with anti-LKB1 (Cell Signaling Technology, cat. #13031, RRID:AB_2716796) and anti-HIF1α (Abcam, cat. #ab16066, RRID:AB_302234) antibodies.

Colony-Forming Unit Assays with Human MPN-BP Cells

Peripheral blood mononuclear cells (150,000) collected from patients at the blast phase of the disease were plated in H4434 methylcellulose media (STEMCELL Technologies) supplemented with echinomycin (Sigma-Aldrich), mitotempo (Sigma-Aldrich), PP242 (Selleck Chemicals), PT2977 (MedChem Express), or ruxolitinib at four different concentrations. Colonies were enumerated after 14 days. Peripheral blood mobilized CD34+ cells from healthy individuals were similarly cultured with drugs to compare their effects in a nonmalignant setting.

B. Stein reports other support from Pharmaessentia and Constellation outside the submitted work. D.E. Root reports grants from AbbVie, Bristol-Myers Squibb, Janssen, Merck, and Vir outside the submitted work. N.S. Chandel reports personal fees from Rafael Pharma outside the submitted work. R.L. Levine reports personal fees and other support from Qiagen and C4, personal fees from Lilly and Janssen, and other support from Prelude, Zentalis, Isoplexis, Mission Bio, Ajax, and Auron outside the submitted work. R.K. Rampal reports grants and personal fees from Constellation, Incyte, Celgene/BMS, and Stemline personal fees from Promedior, CTI, Blueprint, Galecto, Pharmaessentia, and AbbVie outside the submitted work. G.A. Challen reports grants from Incyte outside the submitted work. J.D. Crispino reports grants from NIH, Samuel Waxman Cancer Research Foundation, and ALSAC during the conduct of the study. No disclosures were reported by the other authors.

C. Marinaccio: Conceptualization, formal analysis, investigation, methodology, writing–original draft, writing–review and editing. C.A. Famulare: Resources, writing–review and editing. N. Farnoud: Formal analysis, writing–review and editing. B. Stein: Conceptualization, resources, writing–review and editing. M. Schieber: Investigation, writing–review and editing. S. Gurbuxani: Formal analysis, writing–review and editing. D.E. Root: Conceptualization, resources, writing–review and editing. S.T. Younger: Conceptualization, resources, writing–review and editing. R. Hoffman: Resources, writing–review and editing. N. Gangat: Resources, writing–review and editing. P. Ntziachristos: Methodology, writing–review and editing. P. Suraneni: Conceptualization, validation, investigation, visualization, methodology, writing–original draft. N.S. Chandel: Conceptualization, methodology, writing–review and editing. R.L. Levine: Conceptualization, writing–review and editing. R.K. Rampal: Conceptualization, investigation, writing–review and editing. G.A. Challen: Conceptualization, writing–review and editing. A. Tefferi: Conceptualization, writing–review and editing. J.D. Crispino: Conceptualization, resources, funding acquisition, visualization, methodology, writing–original draft, project administration. H. Celik: Conceptualization, investigation, visualization, methodology, writing–review and editing. A. Volk: Conceptualization, investigation, visualization, methodology, writing–review and editing. Q.J. Wen: Investigation, writing–review and editing. T. Ling: Investigation, writing–review and editing. M. Bulic: Investigation, writing–review and editing. T. Lasho: Investigation, visualization, methodology, writing–review and editing. R.P. Koche: Formal analysis, writing–review and editing.

This work was supported by the NIH grants R01CA237039 and R01HL112792 to J.D. Crispino, R01HL147978 to G.A. Challen, R35CA197532 to N.S. Chandel, R01CA248770 to P. Ntziachristos, R50CA211534 to Q.J. Wen, and the MPN Research Consortium P01CA108671 to R. Hoffman, R.L. Levine, J.D. Crispino, and R.K. Rampal. A. Volk was supported by K99CA230314, R.K. Rampal is supported by K08CA188529-01, and M. Schieber was supported by the Northwestern University Physician Scientist Training Program as well as by a Conquer Cancer Young Investigator Award. We also acknowledge the support of Memorial Sloan Kettering Cancer Center Support Grant NIH P30 CA008748. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. G.A. Challen is a scholar of the Leukemia and Lymphoma Society. H. Celik was supported by an Edward P. Evans Foundation Young Investigator Award, the Leukemia Research Foundation, and the When Everyone Survives Foundation. Additional support was provided by the Janus Fund (R.L. Levine), the Samuel Waxman Cancer Research Foundation (J.D. Crispino), and St. Jude/ALSAC (J.D. Crispino).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Cerquozzi
S
,
Tefferi
A
. 
Blast transformation and fibrotic progression in polycythemia vera and essential thrombocythemia: a literature review of incidence and risk factors
.
Blood Cancer J
2015
;
5
:
e366
.
2.
Cervantes
F
,
Tassies
D
,
Salgado
C
,
Rovira
M
,
Pereira
A
,
Rozman
C
. 
Acute transformation in nonleukemic chronic myeloproliferative disorders: actuarial probability and main characteristics in a series of 218 patients
.
Acta Haematol
1991
;
85
:
124
7
.
3.
Dunbar
AJ
,
Rampal
RK
,
Levine
R
. 
Leukemia secondary to myeloproliferative neoplasms
.
Blood
2020
;
136
:
61
70
.
4.
Tefferi
A
,
Rumi
E
,
Finazzi
G
,
Gisslinger
H
,
Vannucchi
AM
,
Rodeghiero
F
, et al
Survival and prognosis among 1545 patients with contemporary polycythemia vera: an international study
.
Leukemia
2013
;
27
:
1874
81
.
5.
Heaney
ML
,
Soriano
G
. 
Acute myeloid leukemia following a myeloproliferative neoplasm: clinical characteristics, genetic features and effects of therapy
.
Curr Hematol Malig Rep
2013
;
8
:
116
22
.
6.
Tam
CS
,
Nussenzveig
RM
,
Popat
U
,
Bueso-Ramos
CE
,
Thomas
DA
,
Cortes
JA
, et al
The natural history and treatment outcome of blast phase BCR-ABL-myeloproliferative neoplasms
.
Blood
2008
;
112
:
1628
37
.
7.
Tefferi
A
,
Mudireddy
M
,
Mannelli
F
,
Begna
KH
,
Patnaik
MM
,
Hanson
CA
, et al
Blast phase myeloproliferative neoplasm: Mayo-AGIMM study of 410 patients from two separate cohorts
.
Leukemia
2018
;
32
:
1200
10
.
8.
Rampal
R
,
Ahn
J
,
Abdel-Wahab
O
,
Nahas
M
,
Wang
K
,
Lipson
D
, et al
Genomic and functional analysis of leukemic transformation of myeloproliferative neoplasms
.
Proc Natl Acad Sci U S A
2014
;
111
:
E5401
10
.
9.
Celik
H
,
Koh
WK
,
Kramer
AC
,
Ostrander
EL
,
Mallaney
C
,
Fisher
DAC
, et al
JARID2 functions as a tumor suppressor in myeloid neoplasms by repressing self-renewal in hematopoietic progenitor cells
.
Cancer Cell
2018
;
34
:
741
56
.
10.
Gan
B
,
Hu
J
,
Jiang
S
,
Liu
Y
,
Sahin
E
,
Zhuang
L
, et al
Lkb1 regulates quiescence and metabolic homeostasis of haematopoietic stem cells
.
Nature
2010
;
468
:
701
4
.
11.
Gurumurthy
S
,
Xie
SZ
,
Alagesan
B
,
Kim
J
,
Yusuf
RZ
,
Saez
B
, et al
The Lkb1 metabolic sensor maintains haematopoietic stem cell survival
.
Nature
2010
;
468
:
659
63
.
12.
Nakada
D
,
Saunders
TL
,
Morrison
SJ
. 
Lkb1 regulates cell cycle and energy metabolism in haematopoietic stem cells
.
Nature
2010
;
468
:
653
8
.
13.
Hsiau
T
,
Conant
D
,
Rossi
N
,
Maures
T
,
Waite
K
,
Yang
J
, et al
Inference of CRISPR edits from sanger trace data
.
bioRxiv
2019
:
251082
.
14.
Kondo
K
,
Klco
J
,
Nakamura
E
,
Lechpammer
M
,
Kaelin
WG
 Jr
. 
Inhibition of HIF is necessary for tumor suppression by the von Hippel-Lindau protein
.
Cancer Cell
2002
;
1
:
237
46
.
15.
Brunelle
JK
,
Bell
EL
,
Quesada
NM
,
Vercauteren
K
,
Tiranti
V
,
Zeviani
M
, et al
Oxygen sensing requires mitochondrial ROS but not oxidative phosphorylation
.
Cell Metab
2005
;
1
:
409
14
.
16.
Klimova
T
,
Chandel
NS
. 
Mitochondrial complex III regulates hypoxic activation of HIF
.
Cell Death Differ
2008
;
15
:
660
6
.
17.
Hamanaka
RB
,
Weinberg
SE
,
Reczek
CR
,
Chandel
NS
. 
The mitochondrial respiratory chain is required for organismal adaptation to hypoxia
.
Cell Rep
2016
;
15
:
451
9
.
18.
Orr
AL
,
Vargas
L
,
Turk
CN
,
Baaten
JE
,
Matzen
JT
,
Dardov
VJ
, et al
Suppressors of superoxide production from mitochondrial complex III
.
Nat Chem Biol
2015
;
11
:
834
6
.
19.
Wierenga
AT
,
Vellenga
E
,
Schuringa
JJ
. 
Convergence of hypoxia and TGFbeta pathways on cell cycle regulation in human hematopoietic stem/progenitor cells
.
PLoS One
2014
;
9
:
e93494
.
20.
Xu
R
,
Wang
K
,
Rizzi
JP
,
Huang
H
,
Grina
JA
,
Schlachter
ST
, et al
3-[(1S,2S,3R)-2,3-Difluoro-1-hydroxy-7-methylsulfonylindan-4-yl]oxy-5-fluorobenzo nitrile (PT2977), a hypoxia-inducible factor 2alpha (HIF-2alpha) inhibitor for the treatment of clear cell renal cell carcinoma
.
J Med Chem
2019
;
62
:
6876
93
.
21.
Shorning
BY
,
Clarke
AR
. 
Energy sensing and cancer: LKB1 function and lessons learnt from Peutz–Jeghers syndrome
.
Semin Cell Dev Biol
2016
;
52
:
21
9
.
22.
Li
F
,
Han
X
,
Li
F
,
Wang
R
,
Wang
H
,
Gao
Y
, et al
LKB1 inactivation elicits a redox imbalance to modulate non-small cell lung cancer plasticity and therapeutic response
.
Cancer Cell
2015
;
27
:
698
711
.
23.
Faubert
B
,
Vincent
EE
,
Griss
T
,
Samborska
B
,
Izreig
S
,
Svensson
RU
, et al
Loss of the tumor suppressor LKB1 promotes metabolic reprogramming of cancer cells via HIF-1alpha
.
Proc Natl Acad Sci U S A
2014
;
111
:
2554
9
.
24.
Shackelford
DB
,
Vasquez
DS
,
Corbeil
J
,
Wu
S
,
Leblanc
M
,
Wu
CL
, et al
mTOR and HIF-1alpha-mediated tumor metabolism in an LKB1 mouse model of Peutz–Jeghers syndrome
.
Proc Natl Acad Sci U S A
2009
;
106
:
11137
42
.
25.
Hayashi
Y
,
Zhang
Y
,
Yokota
A
,
Yan
X
,
Liu
J
,
Choi
K
, et al
Pathobiological pseudohypoxia as a putative mechanism underlying myelodysplastic syndromes
.
Cancer Discov
2018
;
8
:
1438
57
.
26.
Baumeister
J
,
Chatain
N
,
Hubrich
A
,
Maie
T
,
Costa
IG
,
Denecke
B
, et al
Hypoxia-inducible factor 1 (HIF-1) is a new therapeutic target in JAK2V617F-positive myeloproliferative neoplasms
.
Leukemia
2020
;
34
:
1062
74
.
27.
Uozumi
K
,
Otsuka
M
,
Ohno
N
,
Moriyama
T
,
Suzuki
S
,
Shimotakahara
S
, et al
Establishment and characterization of a new human megakaryoblastic cell line (SET-2) that spontaneously matures to megakaryocytes and produces platelet-like particles
.
Leukemia
2000
;
14
:
142
52
.
28.
Takubo
K
,
Goda
N
,
Yamada
W
,
Iriuchishima
H
,
Ikeda
E
,
Kubota
Y
, et al
Regulation of the HIF-1alpha level is essential for hematopoietic stem cells
.
Cell Stem Cell
2010
;
7
:
391
402
.
29.
Cho
H
,
Du
X
,
Rizzi
JP
,
Liberzon
E
,
Chakraborty
AA
,
Gao
W
, et al
On-target efficacy of a HIF-2alpha antagonist in preclinical kidney cancer models
.
Nature
2016
;
539
:
107
11
.
30.
Spahn
PN
,
Bath
T
,
Weiss
RJ
,
Kim
J
,
Esko
JD
,
Lewis
NE
, et al
PinAPL-Py: a comprehensive web-application for the analysis of CRISPR/Cas9 screens
.
Sci Rep
2017
;
7
:
15854
.
31.
Gundry
MC
,
Brunetti
L
,
Lin
A
,
Mayle
AE
,
Kitano
A
,
Wagner
D
, et al
Highly efficient genome editing of murine and human hematopoietic progenitor cells by CRISPR/Cas9
.
Cell Rep
2016
;
17
:
1453
61
.