A Humanized Animal Model Predicts Clonal Evolution and Therapeutic Vulnerabilities in Myeloproliferative Neoplasms

Abstract

Myeloproliferative neoplasms (MPNs) are chronic blood diseases with significant morbidity and mortality. While sequencing studies have elucidated the genetic mutations that drive these diseases, MPNs remain largely incurable with a significant proportion of patients progressing to rapidly fatal secondary acute myeloid leukemia (sAML). Therapeutic discovery has been hampered by the inability of genetically-engineered mouse models to generate key human pathologies such as bone marrow fibrosis. To circumvent these limitations, here we present a humanized animal model of myelofibrosis (MF) patient-derived xenografts (PDXs). These PDXs robustly engrafted patient cells that recapitulated the patient’s genetic hierarchy and pathologies such as reticulin fibrosis and propagation of MPN-initiating stem cells. The model can select for engraftment of rare leukemic subclones to identify MF patients at-risk for sAML transformation, and can be used as a platform for genetic target validation and therapeutic discovery. We present a novel but generalizable model to study human MPN biology.

INTRODUCTION

Myeloproliferative neoplasms (MPN) are clonal hematologic diseases characterized by the aberrant proliferation of one or more myeloid lineages, and progressive bone marrow (BM) fibrosis. BCR-ABL negative MPNs are characterized by an excess of red blood cells (polycythemia vera [PV]) or platelets (essential thrombocythemia [ET]), or by the deposition of reticulin fibers in the BM (myelofibrosis [MF]) (1). MF is the deadliest MPN subtype with median survival for patients of approximately five years, and can occur as a de novo neoplasm or progression from pre-existing ET or PV. The most commonly mutated genes in MPNs are JAK2 (2–4), MPL (5) and CALR (6,7), which are responsible for disease initiation. The acquisition of additional mutations in epigenetic regulators, transcription factors, and signaling components can modify the course of the disease and contribute to disease progression and leukemic transformation (8,9). JAK2, MPL, and CALR mutations share a hallmark of aberrant JAK-STAT activation. As such, the JAK1/2 inhibitor ruxolitinib is a front line therapy (in particular for MF) and can alleviate constitutional symptoms of the disease (10), but does not eliminate the malignant clone and has minimal impact on BM fibrosis and overall survival (11), highlighting the need for more effective therapies.

As the genetic basis of MPN has been elucidated, murine models have been developed to dissect disease origins and mechanisms. Transgenic and conditional knock-in mice have shown that physiological expression of JAK2^V617F alone can induce a PV- or ET-like MPN in vivo (12), and the hematopoietic stem cell (HSC) pool contains the disease-initiating potential (13,14). However, current mouse models do not recapitulate the clinical heterogeneity, genetic composition, or morphological features of MPN. Apart from retroviral over-expression of MPL^W515L (5,15), mouse MPN models do not typically generate robust reticulin fibrosis in the BM, the most significant MF pathology. The lack of faithful pre-clinical MPN models presents a major barrier to developing effective therapies.

To circumvent the limitations of conventional mouse models, patient-derived xenografts (PDXs) are increasingly used as tools for pre-clinical drug development and target validation, and have been shown to recapitulate the pathology and genetics of the patients from which they are derived in various malignancies (16). Technological developments in immunodeficient mouse strains (17,18) have enabled successful xenotransplantation of normal human CD34+ hematopoietic stem and progenitor cells (HSPCs), as well as patient samples from myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) subtypes that were previously refractory to engraftment. However, efforts to generate MF PDXs have been largely unsuccessful due to poor engraftment potential of MPN-disease initiating cells (19), or require specialized techniques (20).

In a previous study, we demonstrated that genetic inhibition of the polycomb repressive 2 (PRC2) co-factor JARID2 in MPN patient samples permitted engraftment in NSGS mice (21). This caused us to revisit methodology to determine if technological advances might facilitate a generalizable MPN PDX system. Here, we present a generalizable method for xenotransplantation of human MF CD34+ cells into newer generation immunodeficient mice by X-ray guided intra-tibial injection. These PDXs reproduce the hallmarks of MF, including most importantly, reticulin fibrosis in the BM. Genetic analysis shows faithful maintenance of MF patient clonal architecture within the engrafted cell population. Enhancing the utility of the model, we show this system can predict for clonal progression to secondary AML (sAML) in patients samples obtained far prior to clinical manifestation, and can be manipulated to provide a platform for genetic and pharmacological target validation in MF. Thus, this model presents a robust and malleable platform to study MPN genetics and therapeutics.

RESULTS

Credentialing a Humanized Animal Model of Myelofibrosis

In our previous study, genetic inhibition of the PRC2 co-factor JARID2 by lentiviral shRNA permitted sustained engraftment of CD34+ cells from MF patients in the blood, bone marrow (BM) and spleens of NSGS mice accompanied by marked reticulin fibrosis (21). However, we noted evidence of engraftment and modest reticulin fibrosis in recipients of MF patient cells transduced with the negative control shRNA vector. This encouraged us to revisit the methodology to determine if techniques could be adapted for a generalizable PDX model of MF. CD34+ cells were freshly isolated from the peripheral blood mononuclear cell (PBMC) fraction from MF patients (Supplementary Fig. 1). Selection criteria for patient samples included blast count <5%, with over 80% of patient samples having no detectable blasts. MF CD34+ cells were cultured for 16-hours in serum free media with hematopoietic cytokines (SCF, FLT3L and TPO), then transplanted into sublethally (200 rads) irradiated NSGS mice via X-ray guided intra-tibial (ITib) injection (Fig. 1A). NSGS mice express humanized SCF, GM-CSF and IL3 (17) and demonstrate improved myeloid engraftment from normal human CD34+ hematopoietic stem and progenitor cells (HSPCs) and AML subtypes that were previously difficult to engraft (22,23). The technical adaptation of ITib injection has facilitated PDX models from difficult to engraft diseases such as CMML (24). Comparison of ITib versus intra-venous injection showed superior engraftment for both normal and neoplastic human CD34+ cells (Fig. 1B). We reasoned these technological advances may be sufficient to generate reliable MF PDXs.

Figure 1. Credentialing a Humanized Animal Model of Myelofibrosis.

A, X-ray guided intra-tibial injection of CD34+ cells from MF patients. B, Comparison of BM engraftment 12-weeks post-transplant resulting from either retro-orbital or intra-tibial injection of CD34+ cells from cord blood and MF patient samples (two-tailed t-test for each individual patient sample). C, Flow cytometric identification of engrafted human cells in NSGS mice. D, Engraftment levels of MF patient cells in BM and spleens of NSGS mice 12-weeks post-transplant. E, Engraftment of erythroid progenitor cells (hCD45− Ter119− CD71+ CD235a+) from MF patient samples in NSGS BM 12-weeks post-transplant. F, Reticulin staining showing fibrosis in the BM of NSGS mice transplanted with MF patient samples, but not in untransplanted mice or mice transplanted with cord blood CD34+ cells. Representative reticulin fibrosis grading is indicated. G, Quantification of degree of reticulin fibrosis from each patient sample. H, Representative flow cytometric analysis of the BM of recipient mice 12-weeks post-primary and post-secondary transplant patient sample MF 300179.

Error bars indicate mean ± S.E.M. * p<0.05, ** p<0.01, *** p<0.001. N.D. = not determined.

While the engraftment of human cells in the peripheral blood was highly variable between patient samples (Supplementary Fig. 2A), virtually all NSGS mice that received >100,000 CD34+ MF patient cells showed robust engraftment in the BM (Fig. 1C) and spleen at 12-weeks post-transplant (Fig. 1D). Consistent with MPN, engrafted human cells were almost exclusively CD33+ myeloid cells (Fig. 1C) or immature erythroid progenitors (Fig. 1E). Except for one sample, there was no difference in BM engraftment between the injected and contralateral legs (Supplementary Fig. 2B). Engraftment levels were not correlated with number of CD34+ cells transplanted (Supplementary Fig. 2C), but rather inherent properties of individual samples. Analysis revealed other pathologies characteristic of MPN such as activated JAK/STAT signaling (Supplementary Fig. 2D) and altered blood counts (Supplementary Fig. 2E, Supplementary Table 1). Strikingly, most MF PDXs showed marked reticulin fibrosis in the BM and spleen compared to mice transplanted with cord blood CD34+ cells, or NSGS mice that were irradiated and then monitored for 12-weeks (Fig. 1F,G). The most aggressive patient samples were able to induce a lethal MPN in NSGS mice (Supplementary Fig. 2F). Mice that succumbed to lethal disease did not show evidence of transformation to sAML such as increased blood counts or circulating blasts. Rather, lethal MPN was significantly associated with the degree of reticulin fibrosis in the BM (Supplementary Fig. 2G) and peripheral anemia (Supplementary Fig. 2H), indicative of ineffective hematopoiesis. To determine if the disease could be serially transplanted, 1×10⁶ hCD45+ cells from primary PDXs were transferred to secondary NSGS recipients using the same technical approach. Despite robust engraftment in primary transplantation (Fig. 1H), MF patient cells were unable to engraft or propagate disease pathologies to secondary recipients (Supplementary Fig. 2I). This however does indicate that the samples initially transplanted, while neoplastic, were not transformed and the resultant engraftment was not due to leukemic subclones. Despite the lack of serial propagation, this methodology provides a robust and reproducible model for establishing PDXs from MF patient samples.

MF HSCs Show Robust Engraftment in NSGS Mice

To ensure the engrafted MF cells in NSGS mice retained the molecular properties of the patient cells, single cell RNA-seq was performed. PBMCs from two independent cord blood and MF patient samples were compared to the engrafted hCD45+ cells from the BM of NSGS mice 12-weeks post-transplant. UMAP analysis showed that the PBMCs from both cord blood samples clustered together, but the MF PBMCs clustered distinctly from the normal cells as well as from each other (Fig. 2A). Although JAK2^V617F was the driver mutation in both these MF patients, the separation from each other was likely driven by the different cooperating mutations (e.g. MF 585953 = TET2, ASXL1; MF 784981 = SETBP1, CUX1, ZRSR2). Importantly, the separation of sample-specific cell clusters was maintained in engrafted PDX cells (Fig. 2A). Although the sequencing platform here did not permit simultaneous detection of genomic mutations in single cells, we selected MF patient samples for this experiment based on high variant allele fraction (VAF) of JAK2^V617F (MF 585953 = 79%, MF 784981 = 97%), and independent analysis of hCD45+ cells from the BM of NSGS mice showed the VAF was sustained in the engrafted cells (see next section for details). Thus, it is likely the majority of cells sequenced in this experiment expressed the oncogene. Annotation of cell clusters using marker gene expression showed that the MPN-specific cell clusters were enriched for myeloid cells, platelets, and HSPCs in both the patients and the PDXs (Fig. 2A). This informs that the distinct molecular profiles of MF patient cells are maintained in this PDX model.

Figure 2. MF HSCs Show Robust Engraftment in NSGS Mice.

A, UMAP plots of single cell RNA-seq data showing clustering of PBMC cells from two cord blood samples and two MF patients (Patients; MF 585953 and MF 784981) and hCD45+ cells from the same donors isolated from the BM of NSGS mice 12-weeks post-transplant (PDX). The top panels show clustering of samples by genotype in Patients and PDX. The bottom panels show identification of cell populations by marker genes. Dashed red lines indicate population identities of MF-only cell clusters. B, Flow cytometric identification of human HSCs (hCD45+ Lineage^low CD34+ CD38− CD45RA− CD90+) and multilymphoid progenitors (MLPs) in the BM of NSGS mice. C, Quantification of human HSCs in the BM of NSGS mice 12-weeks post-transplant. D, Four-week peripheral blood engraftment of MF 504293 patient cells prior to treatment initiation, and four-weeks after ruxolitinib therapy. E, BM engraftment of MF 504293 patient cells four-weeks post-treatment (two-tailed t-test). F, Representative spleen images from mice of the different treatment groups. G, Spleen weights of NSGS four-weeks post-treatment (two-tailed t-test). H, Quantification of human HSC abundance in the BM of NSGS mice post-treatment.

Error bars indicate mean ± S.E.M. * p<0.05, **** p<0.0001. N.D. = not determined.

Experimental models implicate HSCs as the disease-initiating cell population in MPN (13,14). Moreover, MPN founding events such as JAK2^V617F and CALR frameshift mutations (CALR^fs) can be detected in humans with clonal hematopoiesis (CH)(25–27), further suggesting a HSC origin as the mutational reservoir. Most MF therapies are likely ineffective because they fail to eradicate this mutant HSC population in patients. We sought to determine if the MPN mutant HSCs were propagated in this PDX model, which could provide a system to evaluate the impact of novel therapeutics specifically on the disease-initiating cell population. Flow cytometric analysis of the BM of recipient NSGS mice showed that human HSCs (Lineage^low CD34+ CD38- CD45RA- CD90+) were not maintained in animals xenografted with cord blood CD34+ cells (Fig. 2B). This is likely due to the inflammatory environment driving HSCs towards terminal differentiation as opposed to self-renewal (28). Conversely, analysis of NSGS mice xenografted with CD34+ cells from MF patients showed that human HSCs were readily detectable in most cases (Fig. 2C), suggesting that this is a permissive niche for the propagation of MPN disease-initiating cells.

Given that MPN disease-initiating HSCs were propagated, we sought to benchmark the therapeutic relevance of the system by evaluating the effect of ruxolitinib as current standard of care for MF. NSGS mice were xenografted with MF CD34+ cells, and then four-weeks post-transplant were randomized for treatment with ruxolitinib (or vehicle control) based on engraftment of human cells in the peripheral blood. Engraftment and pathology of MF patient cells were evaluated after four-weeks of therapy. While ruxolitinib treatment did not affect the engraftment of MF cells in the peripheral blood (Fig. 2D), burden of human cells was significantly reduced in the BM (Fig. 2E) accompanied by a dramatic reduction in splenomegaly (Fig. 2F,G). But consistent with human patients, treatment with ruxolitinib did not affect the abundance of human HSCs in the BM (Fig. 2H).

MF Patient Clonal Architecture is Maintained in PDX Models

The genetic hierarchy of MPN is hypothesized to influence treatment response to JAK/STAT inhibitors. Exome sequencing was performed on MF patient cells prior to transplantation and hCD45+ cells 12-weeks post-transplant to determine if the patient’s clonal architecture was preserved in PDXs (Supplementary Table 2). The mutational landscape observed in MF patients was maintained in the xenografted cells from NSGS mice (Supplementary Fig. 3). There was high reproducibility for the same patient sample xenografted into different NSGS mice (Fig. 3A) and the VAF of MPN driver mutations showed excellent correlation between patient and PDX cells (Fig. 3B). Other co-operating recurrently mutated genes mutations also showed consistent VAFs comparing CD34+ cells from the MF patients and hCD45+ cells from the BM of NSGS mice (Fig. 3C).

Figure 3. MF Patient Clonal Architecture is Maintained in PDX Models.

A, Comparison of the variant allele fraction (VAF) of mutations in CD34+ cells from MF patient 784981 versus hCD45+ cells isolated from BM and spleens of NSGS mice 12-weeks post-transplant. B, Comparison of average VAF of MPN driver genes in MF patient CD34+ cells and PBMCs versus VAF of same mutation in hCD45+ BM cells from NSGS mice 12-weeks post-transplant. C, Comparison of VAFs of recurrently mutated genes in this cohort between MF patient CD34+ cells and PDX-derived hCD45+ cells. D, Flow cytometry plots showing isolation of different cell populations from PDX of patient MF 300179 and the VAF of mutations in each respective cell populations. E, Model for clonal evolution in patient MF 300179 based on mutational profile of cell populations derived from PDX.

In almost all PDXs, the engrafted human cells were virtually exclusively myeloid (CD33+). However, xenografted cells from MF patient 300179 generated significant lymphoid progeny in NSGS mice (Supplementary Fig. 4A), which allowed comparison of mutant allele burden in different cell lineages and analysis of the developmental trajectory of this patient. Heterozygous DNMT3A^P307L and TET2^P1962L mutations were found in all cells from the patient donor sample and the xenografted cells. Homozygous JAK2^V617F and TP53^M246V mutations were detected at a lower VAF in the bulk post-transplant hCD45+ cells compared to the donor sample, due to the fact these variants were completely absent from the B-cells (CD19+) in the PDX (Fig. 3D). This suggests the B-cells were the progeny of a non-neoplastic CH clone with DNMT3A^P307L and TET2^P1962L mutations, as they also lacked evidence of promiscuous myeloid lineage marker expression (Supplementary Fig. 4B). For MPN evolution, this clone subsequently acquired homozygous JAK2^V617F and TP53^M246V mutations either in a HSC or downstream myeloid progenitor cell which drove excess myeloid differentiation and clinical manifestation (Fig. 3E).

PDX System can Predict Clonal Evolution to Secondary AML

One of the most feared complications of MPN is disease progression to sAML. Up to 20% of patients with MF transform sAML, which is driven by the acquisition of additional co-operating mutations. Patients with post-MF sAML have a dismal prognosis, with a median survival of only six-months (9). Earlier identification of MF patients who are more susceptible to sAML transformation could stratify such individuals for alternative interventions. Such predictions are not possible with the limit of mutation detection for conventional genomic approaches. For the PDXs from patient MF 504293, exome sequencing detected a pathogenic EZH2^Y663H mutation in the xenografted human cells which was not identified in the input CD34+ cells isolated from the patient (Fig. 4A). Ectopic expression of EZH2^Y663H in EZH2-null HEL cells indicated this mutation encodes a loss-of-function protein with severely compromised H3K27me3 activity (Supplementary Fig. 5A). Review of patient history uncovered that this individual eventually underwent disease progression to sAML (Fig. 4B). Strikingly, clinical sequencing performed at the time of sAML diagnosis identified the same EZH2^Y663H mutation present in the PDX, which had never been observed in previous clinical sequencing performed throughout the patient history (Fig. 4C). Of note, the PBMC sample used for PDX input was obtained from this patient 516 days prior to sAML diagnosis. This implies that the selection pressure of xenotransplantation facilitated expansion of a very rare subclone that was responsible for leukemic transformation. As the xenografted cells were obtained from the patient in the chronic MF stage years before sAML diagnosis (Fig. 4B,C), this suggests the PDX system might serve as a prediction model for patients with rare, rising sAML subclones who are at-risk for leukemic progression. To examine this, droplet digital PCR (ddPCR) was performed with an EZH2^Y663H-specific probe on an independent patient sample banked at the same time as the specimen used for xenotransplantation. ddPCR analysis (Supplementary Fig. 5B) indeed confirmed the presence of very rare EZH2^Y663H-mutant cells in the PBMCs of this patient (0.17% of cells), with enrichment in the CD34+ cell population (0.63% of cells), although still far below the sensitivity of detection of conventional exome sequencing (Fig. 4D).

Figure 4. PDX System can Predict Clonal Evolution to Secondary AML.

A, Comparison of the variant allele fraction (VAF) of mutations in CD34+ cells from patient MF 504293 versus hCD45+ cells isolated from BM of NSGS mice 12-weeks post-transplant. B, Clinical course of patient MF 504293. C, VAF of EZH2^Y663H variant from clinical NGS during treatment history of patient MF 504293. D, Quantification of EZH2^Y663H variant from indicated samples by ddPCR. E, Clinical course of patient MF 764338. F, Comparison of VAF of mutations in CD34+ cells from patient MF 764338 versus PBMCSs and hCD45+ cells isolated from BM of NSGS mice 12-weeks post-transplant. G, Quantification of TP53^R248Q variant from indicated samples by ddPCR.

Analysis of other exome sequencing cases identified another individual (MF 764338) in which a pathogenic variant was detected exclusively in the human cells from the PDX, but not in the input CD34+ cells at time of collection. Approximately one year after this sample was obtained, the patient was noted to have increasing circulating blasts, and was under consideration for a bone marrow transplant. Clinical sequencing at that time identified the TP53^R248Q mutation in the patient PBMCs, which was the first time in the patient history this variant had been observed (Fig. 4E). The hCD45+ cells from the PDX were found to harbor the TP53^R248Q mutation, one of the most common TP53 variant in de novo AML and post-MPN sAML (29), at a VAF of 15–20% (Fig. 4F). We returned to an independent PBMC sample from the time of collection which was used for xenotransplantation to determine if TP53^R248Q-mutant could be identified by ddPCR. In whole PBMCs, TP53^R248Q-mutant cells were at the level of sensitivity of ddPCR (Supplementary Fig. 5C). But in CD34+ cells enriched from this timepoint, a distinct population of TP53^R248Q-mutant cells (0.48% of cells) could be identified (Fig. 4G). Cumulatively, these two cases demonstrate that rare disease-transforming clones are present in MF patients long prior to diagnosis of clinical progression. While these clones are undetectable using current clinical sequencing methodology, they can be readily identified in this PDX model.

There was one additional patient (MF 145790) in this cohort that eventually transformed to sAML. Exome sequencing of the sAML sample compared to PBMCs and CD34+ cells from the pre-sAML MF stage did not identify sharp acquisition of pathogenic variants in the sAML phase. Two potentially pathogenic sAML-specific variants were identified, ASXL1^G643X and SRSF2^P95L, but the VAF of these variants was less than 5% of the total tumor fraction, which questions the functional relevance of these variants in the transformation process. As for the two patient samples described above, both of these variants were identified in PDX-derived hCD45+ MF cells (Supplementary Fig. 5D). Interestingly, exome sequencing of the engrafted patient cells from three independent NSGS mice showed the SRSF2^P95L variant was identified in two mice, and the ASXL1^G643X variant was only identified in one mouse, and these mice were not overlapping (Supplementary Table 2). This result suggests the ASXL1^G643X and SRSF2^P95L variants may have been present in distinct subclones that were not part of the malignant clone, or perhaps independent pre-malignant clones arising from normal CH processes in this individual.

Genetic and Pharmacological Validation of Novel Therapeutic Targets in MF

We sought to establish the utility of this model for genetic and pharmacological target validation. Proof-of-principle focused on PIM kinase inhibition. The PIM family (PIM1-3) of kinases regulate a number of cellular processes through phosphorylation of a variety of target substrates. The proto-oncogenic potential of PIM kinases was initially described in MYC-driven lymphomagenesis (30), and PIM inhibition (PIMi) is being explored for a variety of solid tumors as well as hematopoietic malignancies (31,32). In JAK2-mutant MPN cell lines, PIMi has been shown to restrain cell proliferation and overcome drug resistance through destabilization of MYC and suppression of pro-survival signaling pathways (33). PIM1 kinase is also upregulated in MF CD34+ cells regardless of their genetic background (34). Resultantly, PIMi has been presented as a therapeutic approach in JAK2-mutant MPN in combination with JAK/STAT inhibition (35). Our system provides a unique opportunity to validate these in vitro studies with cell lines using primary patient samples in vivo.

To determine the specificity of PIMi, cord blood (normal control) or MF patient CD34+ cells were targeted for PIM1 deletion via CRISPR/Cas9 RNP nucelofection (36). A gRNA targeting the inert AAVS1 locus was used as a CRISPR/Cas9 negative control. Analysis of targeted cells via deep-sequencing 72-hours post-nucleofection confirmed high efficiency editing (Supplementary Fig. 6A). Edited CD34+ cells were transplanted into NSGS recipients as described, and mice were sacrificed 12-weeks post-transplant to evaluate function of targeted cells. While loss of PIM1 had no effect on the engraftment of cord blood-derived cells, PIM1-targeted MF cells showed reduced splenomegaly (Supplementary Fig. 6B) and markedly compromised engraftment in the BM (Supplementary Fig. 6C) which was not due to absence of targeted PIM1 populations (Supplementary Fig. 6A). These data suggest that PIM1 may be selectively required for MF cell function.

To evaluate pharmacological potential, PDXs were established from MF patient samples and then randomized for treatment with the pan-PIMi INCB053914 (37), either as a single agent or in combination with ruxolitinib. Treatment was initiated four-weeks post-transplant, then effects were evaluated after four-weeks of treatment (Fig. 5A). In comparison to vehicle-treated control mice, monotherapy with either INCB053914 or ruxolitinib modestly inhibited engraftment of MF cells and splenomegaly for each of three individual patient samples to varying degrees. However, combination therapy markedly inhibited engraftment of patient cells (Fig. 5B) and reduced peripheral blood counts (Supplementary Fig. 6D). Strikingly, while treatment with either single agent had no effect on the burden of human HSCs in the BM, combination therapy was effective in eradicating the JAK2^V617F-mutant MPN-initiating cell population (Fig. 5C). Both agents also reduced BM fibrosis (Supplementary Fig. 6E), although given the timeline for this experiment this may reflect inhibition of MF cell engraftment rather than reversal of fibrosis. To determine if MPN would relapse after cessation of treatment, a cohort of NSGS recipients were monitored for a four-week recovery after discontinuation of treatment. While peripheral blood counts did rebound after discontinuation of treatment, most values still remained lower than vehicle-treated control mice (Supplementary Fig. 6F). After four-weeks of recovery, human bone marrow engraftment (Supplementary Fig. 6G), splenomegaly and human HSC burden recovered somewhat in mice treated with PIMi plus ruxolitinib, but still remained significantly suppressed compared to vehicle-treated mice (Fig. 5D). These results show that PIMi in combination with JAK/STAT inhibition specifically targets MF, particularly JAK2^V617F-mutant cells, and present this combination as an attractive therapeutic approach for MF patients.

Figure 5. Genetic and Pharmacological Validation of Novel Therapeutic Targets in MF.

A, Schematic for PIMi plus ruxolitinib combination therapy using PDX model. B, Cumulative data showing MF patient cell peripheral blood engraftment pre-treatment, and post-treatment blood and BM engraftment, spleen weight and human HSC burden in the BM (one-way ANOVA with treatment arms compared to vehicle, Dunnett multiple comparison correction). C, Representative flow cytometry plots showing human HSC burden from NSGS mice transplanted with MF 784981 and then exposed to the indicated treatments. D, Peripheral blood counts, bone marrow engraftment, spleen weights and human HSC burden from NSGS mice xenografted with indicated MF patient samples following four-weeks of indicated treatment, then after a four-week recovery (two-tailed t-test for each individual patient sample).

Error bars indicate mean ± S.E.M. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001.

BET Bromodomain Inhibition Plus Ruxolitinib Reduces Fibrosis

Although we observed reduced BM fibrosis in MF PDXs in the above experiment with PIMi plus ruxolitinib combination therapy (Supplementary Fig. 6E), this result could be attributed to the effect of ruxolitinib on inhibiting engraftment of MF patient cells because treatment was started four-weeks post-transplant. Because robust reticulin fibrosis was observed in the vehicle-treated PDXs from MF samples 504293 and 585953 after four-weeks of treatment (eight-weeks total post-transplant), an experimental model was established to more specifically test the effect of therapeutics in reversing fibrosis. The BET bromodomain inhibitor JQ1 has been shown to be an effective anti-fibrosis therapy in a mouse retroviral MPL^W515L model of MF, largely through inhibiting the function of BRD4 in promoting NF-κB-driven inflammation (38). JQ1 was effective for inhibiting fibrosis even as a monotherapy, but showed particular potency in combination with JAK/STAT inhibition (38). To test this combination in the humanized MF model, NSGS mice were xenografted with CD34+ cells from patients MF 504293 and 585953 or control cord blood CD34+ cells, then randomized based on four-week peripheral blood engraftment levels. At eight-weeks post-transplant, cohorts began treatment with JQ1, ruxolitinib, combination therapy, or vehicle control (Fig. 6A). Combination therapy inhibited total BM engraftment and human HSC burden in both cord blood and MF transplant recipients, although splenomegaly was specifically reduced in mice receiving MF patient samples (Fig. 6B). Blood counts were variably reduced with some selectivity for MF patient cells (Supplementary Fig. 7). The most important outcome from this experiment was effect on reticulin fibrosis. While monotherapy with either JQ1 or ruxoltinib was able to modestly inhibit BM fibrosis over this timecourse, with possible JAK2^V617F versus CALR genotype-specific sensitivities (Fig. 6C), combination therapy was able to almost completely abrogate BM fibrosis (Fig. 6D). These results confirm murine data showing BET bromodomain inhibition as a potential anti-fibrosis therapy, and validate this system as an effective model for assessing investigational drugs targeting fibrosis in human MF.

Figure 6. BET Bromodomain Inhibition Plus Ruxolitinib Reduces Fibrosis.

A, Schematic for JQ1 plus ruxolitinib combination therapy using PDX model. B, Cumulative data showing MF patient cell pre-treatment peripheral blood engraftment (four-weeks post-transplant, four-weeks pre-treatment), and post-treatment BM engraftment, spleen weight and human HSC burden in the BM (one-way ANOVA with treatment arms compared to vehicle, Dunnett multiple comparison correction). C, Quantification of BM reticulin fibrosis for indicated MF patient samples xenografted into NSGS mice then exposed to indicated treatments (one-way ANOVA with treatment arms compared to vehicle, Dunnett multiple comparison correction). D, Representative images showing reticulin staining in the BM of NSGS mice transplanted with MF 504293 and then exposed to indicated therapies.

Error bars indicate mean ± S.E.M. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001.

DISCUSSION

MPNs are largely incurable hematopoietic diseases. While symptoms can be managed in most cases, many patients remain at risk for thrombohemorrhagic complications and disease transformation. Curative therapies would alleviate a substantial burden on public health, but require methods to effectively eradicate the founding MPN clone. New therapeutic approaches based on patient molecular profiles are needed, which has been hampered by the inability of genetically engineered mouse models to recapitulate key MF pathologies such as reticulin fibrosis. Here, we present a system for establishing PDXs, which accurately propagates the genotypes and phenotypes of MF patients. The model produces robust engraftment of patient-derived cells in all major hematopoietic organs, sustains disease-initiating MPN HSCs, and disseminates the most critical MF pathology of BM fibrosis. However, one limitation of this model is that the disease could not be serially transplanted. This indicates some critical human factor(s) required to serially propagate human MPN-initiating HSCs is still lacking. This may limit the utility of this PDX system because it necessitates procurement of fresh samples from MF patients. However, MF as a hematologic disease is amenable to such an approach. Patients in the chronic phase have regular clinical appointments, and the fibrotic BM niche results in a high proportion of HSPCs in circulation. Sufficient CD34+ cells for experimentation can be collected from routine blood draws for most patients in our experience. Another potential caveat is that CD34+ cells from the peripheral blood of MF patients may have different biological properties than HSPCs still residing in the BM, although studies have suggested the VAF of MPN-initiating mutations is similar between blood and BM cells (39). Bone marrow samples from MF patients were unavailable for direct comparison in this study due to the difficulty in obtaining cells from BM biopsy of these patients (“dry tap”).

One of the most feared consequences for MPN patients is clonal evolution to sAML. Approximately 20% of MF patients progress to sAML, which is associated with a dismal clinical prognosis and median survival of less than six months (40), largely due to the lack of targeted therapies. Earlier identification of MF patients who are at-risk for sAML transformation may allow stratification for more aggressive therapies, bone marrow transplantation, or precision medicine approaches based on their mutation profile. However, the limit of detection of ~2% VAF for most clinical sequencing approaches combined with the fact that many of these assays only sample a portion of the genome prohibit this type of prediction. The PDX model presented here is able to identify rare leukemic subclones present in MF PBMC samples years prior to clinical diagnosis of sAML. Presumably, the engraftment of these subclones is favored in NSGS mice due to the selective pressure of xenotransplantation. Even in samples from patients that have not progressed to sAML, there was enrichment for activated signaling mutations associated with high-risk MF (41,42) in the PDXs relative to the patient cells such as KIT^956W in MF 455643, KRAS^Q61R in MF 530675, and NRAS^G12S in MF 542924. The lack of such selective pressures in the chronic phase of MF means these clones may lay dormant for substantial periods of time in the patients. This is much like the case in therapy-related myeloid neoplasms where TP53-mutant subclones lay dormant until challenged with the selective pressure of chemotherapy (43). The engraftment of these clones in this PDX model facilitated identification of the relevant co-operating mutations responsible for disease progression in the patients, with these sAML-specific mutations far below the level of detection of exome sequencing at the time of sample collection, years prior to clinical diagnosis of sAML. Using patient MF 504293 as an example, PDXs were established from Day 532 patient samples and incubated for 12-weeks (+84-days = Day 616). If samples are then processed and submitted for sequencing, assuming a six-week turnaround for genomic analysis (+42-days = Day 658), this would have identified the pathogenic subclone 390 days prior to clinical diagnosis of sAML. It could be argued that further technological advances in high-resolution sequencing could identify these potentially transforming mutations at low abundance in MF patients during the chronic phase. However, error-corrected sequencing has shown that many potentially pathogenic mutations are acquired in people during age-related CH (44) and MDS (45), the vast majority of which are not functionally relevant without the right context. The power of this PDX system is that is able to discriminate variants with functional relevance by selection during the xenotransplantation process. Thus, not only can this system prospectively identify rising sAML subclones in MF patients long before clinical presentation, it can serve as an avatar to test novel therapeutic approaches for individual patients based on their co-operating mutations. With regard to modeling precision medicine, we hypothesized the EZH2^Y663H variant from patient MF 504293 may represent a gain-of-function variant given its proximity and similarity to the EZH2^Y646 activating mutations recurrently found in lymphoma (46). This may render the patient cells vulnerable to EZH2 inhibitors such as tazemetostat, which could be tested in the PDX model. However, our analysis showed the EZH2^Y663H variant was a loss-of-function mutation with impaired H3K27me3 methyltransferase function, consistent with previous observations regarding EZH2 mutations in myeloid malignancies (47). Nevertheless, the tractability of this system as evidenced by our combination therapy experiments should allow it to be leveraged to quickly test precision intervention approaches for individual high-risk cases.

As JAK2^V617F, CALR^fs and MPL^W515 mutations all converge on JAK/STAT signaling, the JAK1/2 inhibitor ruxolitinib is currently front line therapy for MF. Most patients experience a reduction in splenomegaly and an improved quality of life (48), but it does not eliminate the malignant clone and has little to no impact on BM fibrosis and overall survival (11). Moreover, 75% of MPN patients on ruxolitinib discontinue treatment within five years due to development of dose-limiting cytopenias and/or non-hematological toxicities (49). Therefore, there is a pressing need for new treatment modalities. However, pharmacological discovery in MPN has been hampered by the lack of appropriate models within which to evaluate the therapeutic effect on the key MF pathologies of BM fibrosis and MPN-initiating cell burden. We demonstrate here this PDX model can be used as a platform for clinical discovery for MF, recapitulating the patient experience with ruxolitinib of reduced splenomegaly without reducing MPN-initiating cell burden. Using this system, combination therapy of ruxolitinib with pan-PIM inhibition (currently in clinical trials for solid tumors) was able to effectively diminish MF patient cell engraftment and reduce splenomegaly. Most importantly, the combination of these agents was able to substantially reduce the burden of human JAK2^V617F-mutant HSCs in the BM of these mice. While these results are encouraging, unfortunately this particular combination therapy has not proven feasible in MPN patients as myelosuppression has been observed with pan-PIM kinase inhibitors. In terms of specific fibrosis-inhibiting agents, this system was able to validate results from murine models regarding the efficacy of JQ1 in reversing BM fibrosis, and support the continued clinical development of BET inhibitors for myelofibrosis patients (phase III clinical trial NCT04603495). It should be noted that while this PDX model may be closer to the human disease, it is premature to imply it is fully predictive of human clinical outcomes with potential therapeutic agent(s). Nevertheless, our experiments serve as proof-of-principle that this system can serve as a platform for therapeutic screening. In addition to constitutive JAK/STAT activation, other oncogenic signaling pathways including MAP kinase, PI3 kinase and NFκB pathways, are hyperactivated in MF patients (38,50). Combinatorial approaches with inhibitors of these pathways, many of which are FDA-approved for the treatment of other cancers, may yield therapeutic synergy with JAK/STAT inhibitors in MPN patients. These types of hypotheses can be readily tested using this system due to the lack of specialized techniques and materials, and this model should represent a generalizable tool that can be quickly adapted across labs in hematology research.

METHODS

Mice and transplantation

The Institutional Animal Care and Use Committee at Washington University approved all animal procedures. All mice used in this study were NOD-scid-Il2rg-null-3/GM/SF (NSGS; The Jackson Laboratory #013062). Human cells were transplanted into sublethally irradiated (200 rads) 6–8 week-old NSGS mice via X-ray guided (UltraFocus100, Faxitron) intra-tibial injections (right leg) in a volume of 30 μL into with 27-gauge U-100 insulin syringes (Easy Touch # 08496-2755-01). For intra-tibial injections, mice were anesthetized with an intraperitoneal injection of Ketamine/Xylazine mixture (2 mg/mouse; KetaVed, Vedco). Needle was inserted approximately 0.8 cm deep into the tibia and cells are gradually released into BM while the needle is gently removed. Supplementary Figure 1 details the number of CD34+ cells transplanted for individual patient samples.

Human Samples

De-identified cord blood specimens were obtained from the St. Louis Cord Blood Bank. Peripheral blood samples were obtained from MPN patients after obtaining written informed consent in accordance with Declaration of Helsinki ethical guidelines. Human studies were approved by an institutional review board, the Washington University Human Studies Committee (protocol WU #01-1014). De-identified peripheral blood mononuclear cells (PBMCs) from MPN patients and cord blood samples were isolated by Ficoll gradient extraction according to standard procedures. CD34+ cells were isolated using magnetic enrichment (Miltenyi Biotec #130-100-453) and cultured overnight in SFEMII media (StemCell Technologies #09605) supplemented with Pen-Strep (50 Units/mL), human stem cell factor (SCF; 100 ng/mL), human thrombopoietin (TPO; 100 ng/mL), and human FLT3L (100 ng/mL).

Flow Cytometry

All antibody staining was performed in HBSS buffer (Corning #21021CV) containing Pen/Strep (100 Units/mL; Fisher Scientific #MT30002CI), HEPES (10uM; Life Technologies #15630080) and FBS (2%; Sigma #14009C). Briefly, bone marrow (BM) cells isolated from tibias, femurs, and iliac crests were combined for calculating total BM from each mouse. 1.0×10⁸ cells/mL were suspended in complete HBSS and incubated on ice for 20 min with the desired antibodies listed in the table below. The following antibodies were used at 1:100 dilutions - anti-mouse CD45-BV605 (clone 30-F11; BioLegend #103139), anti-human CD45-APC (clone 2D1; BioLegend #368512), anti-human CD71-APCcy7 (clone CY1G4; BioLegend #334110), anti-human CD235a-PE (clone HI264; BioLegend #349105), anti-human CD3-FITC (clone OKT3; BioLegend #317306), anti-human CD19-PECy7 (clone HIB19; BioLegend #302215), anti-human CD33-BV421 (clone WM53; BD #565949), anti-human CD34-PE (clone 561; BioLegend #343606), anti-human CD90-PECy7 (clone 5E10; BioLegend #328124), anti-human CD45RA-BV421 (clone HI100; BioLegend #304130), anti-human CD38-FITC (clone HB7; Invitrogen #11-0388-42), anti-human Lineage cocktail-APC (BioLegend #348803), anti-human CD45-biotin (clone HI30; BioLegend #304004), and Streptavidin-APCcy7 (BD #554063).

Western Blot

10 μg of protein samples were separated in pre-casted 4–15% gradient SDS gels (Biorad, #456-1084) and transferred to nitrocellulose membranes (Millipore #IPVH00010). Membranes were subsequently probed with antibodies to detect pSTAT3 (Cell Signaling Technology #9145S; RRID:AB_2491009), pSTAT5 (Cell Signaling Technology #4322S), EZH2 (Cell Signaling Technology #3147S), H3K27me3 (Cell Signaling Technology #C36B11), total H3 (Cell Signaling Technology #D1H2) and β-ACTIN (Santa Cruz #SC-47778; RRID:AB_2714189). Detection was performed using horseradish peroxidase conjugated secondary mouse or rabbit antibody and chemiluminescence HRP substrate (Millipore #WBKLS0100).

Histopathology

Mouse tibias were fixed in 10% neutral buffered formalin (Fisher Scientific #SF100-4) overnight at 4°C. Immediately after overnight fixation, tibias were decalcified in 14% EDTA for 12 days. This was followed by series of hydration steps: 20% EtOH for 1hr, 30% EtOH for 1hr, 50% EtOH for 1hr and 70% EtOH for hr. Tibias were rinsed with PBS and processed for paraffin embedding and sectioned at 5 μM. Reticulin staining was performed by the Washington University Musculoskeletal Histology and Morphometry Core. Images were captured using an AxioObserver D1 inverted microscope (Zeiss, Thrownwood, NY) equipped with an Axiocam 503 color camera. Images were acquired with Plan-Apochromat objective at 63X, 1.4 NA objective using the ZEN 2 (blue edition) software.

Single Cell RNA-seq

Cells were resuspended at 1,200 cells/uL in PBS + 0.04% BSA. cDNA was prepared after the GEM generation and barcoding, followed by the GEM-RT reaction and bead cleanup steps. Purified cDNA was amplified for 11–13 cycles before being cleaned up using SPRIselect beads. Samples were then run on a Bioanalyzer to determine the cDNA concentration. GEX libraries were prepared as recommended by the 10x Genomics Chromium Single Cell 3’ Reagent Kits v3 user guide with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. For sample preparation on the 10x Genomics platform, the Chromium Single Cell 3’ GEM Library and Gel Bead Kit v3 (PN-1000075), Chromium Chip B Single Cell Kit (10x Genomics, PN-10000153), and Chromium Dual Index Kit TT Set A (PN-1000215) were used. The concentration of each library was determined through qPCR utilizing the KAPA library Quantification Kit according to the manufacturer’s protocol (KAPA Biosystems/Roche) to produce appropriate cluster counts Illumina NovaSeq6000 instrument. Normalized libraries were sequenced on a NovaSeq6000 S4 Flow Cell (Illumina) using the XP workflow and a 28×10×10×150 sequencing recipe. A median sequencing depth of 50,000 reads/cell was targeted for each library. scRNA-seq data were demultiplexed and aligned to the Genome Reference Consortium Human genome, CRChg38. The aligned data were then annotated and UMI-collapsed using Cellranger (v3.1.0, 10x Genomics). Cells with more than 10% mitochondrial gene expression and with top 5% unique feature counts were excluded. Principal component analysis was performed to reduce data using Seurat 3.0. Clusters were identified applying the dimensional reduction techniques (tSNE and UMAP) using the same package. Expression levels of conventional cell surface markers were examined to annotate clusters. Differentially expressed genes were identified within the cluster of interest. The fgsea package was employed to determine enriched signaling pathways.

Exome Sequencing

Genomic DNA was extracted using the PureLink genomic DNA extraction kit (Invitrogen #K1820-02), and submitted for exome sequencing at the McDonnell Genome Institute at Washington University at an average coverage depth of 180x. Whole exome sequence data was aligned to reference sequence build GRCh38 using BWA-mem (Sniffles, RRID:SCR_017619) version 0.7.10 (params: -t 8), then merged and deduplicated using picard version 1.113, (Picard, RRID:SCR_006525). Variants, including SNVs and indels, were detected using VarScan(2) (RRID:SCR_006849) version 2.4.2 (params: --min-coverage 8 --min-var-freq 0.1 –min-reads 2). Combined SNVs and indels were annotated by DoCM (Database of Curated Mutations, params: --filter-docm-variants true), and further by Ensembl Variant Effect Predictor (VEP) of GRCh38 v95 (params: --coding-only false --everything --plugs [Downstream, Wildtype]) by providing gnomAD (The Genome Aggregation Database) and ClinVar (RRID:SCR_006169) VCF files. Variants were filtered by removing low quality variants (params: --min-base-quality 15, --min-mapping-quality 20), and removing sites that exceeded 0.1% population allele frequency in gnomAD projects. CALR frameshift mutations were manually called using BAM files in IGV.

Droplet Digital PCR (ddPCR)

Genomic DNA was extracted as above. 20 ng of total genomic DNA was used to perform ddPCR. All primers and probes used for ddPCR were designed as per MIQE guidelines. Amplicon context sequences used to design these probes are as follows: EZH2 p.Y663H, hg19|chr7:148,507,406-148,507,528 and TP53 p.R248Q, hg19|chr17:7,577,477–7,577,599. Briefly, a PCR reaction mixture was prepared with 10 μL 2x Supermix for Probes without dUTP (Bio-Rad #1863023), 1 μL 20x target (FAM) and wild-type (HEX) primers/probe (Bio-Rad) and 9 uL of ddH2O. The PCR sample was partitioned into ~20,000 nanoliter-sized discrete droplets using the QX-100 Droplet Generator according to the manufacturer’s instruction. These droplets were then gently transferred into a 96-well plate (Bio-Rad #12001925), and ddPCR was performed using a thermocycler with following conditions: 95◦C for 10 min, 40 cycles of 94◦C for 30 s, 55◦C for 60 s and 10 min at 98◦C. The mutant allele frequencies were measured and calculated using Bio-Rad QX-100 droplet reader and QuantaSoft v1.7.4 software, respectively. Each plate contained at least one wild-type DNA control (Promega, #G152A).

CRISPR/Cas9 and Targeted Deep Sequencing

CD34+ cells were cultured overnight in SFEMII media (Stemcell Technologies #09605) supplemented with Pen-Strep (50 Units/mL), human stem cell factor (SCF; 100 ng/mL), human thrombopoietin (TPO; 100 ng/mL), and human Flt3L (100 ng/mL). 12–24h post-culture, CD34+ cells were nucleofected with Cas9/ribonucleoprotein (IDT #1074181) complexed with gRNAs as previously described (36). Synthetic gRNAs sequences were purchased from Synthego as follows: gPIM1.1: GUGGCGUGCAGGUCGUUGCA, gPIM1.2: CUGGAGUCGCAGUACCAGGU, gEZH2.1: CTTCTGTGAGCTCATTGCGC, gEZH2.2: TTATGATGGGAAAGTACACG. A gRNA targeting the AAVS1 locus was used as a negative control: GGGGCCACUAGGGACAGGAU. 48 hrs post-nucleofection, approximately 100,000 cells were set aside to measure CRISPR/Cas9 targeting efficiency using PCR amplicon-based deep sequencing. The remaining cells were transplanted into sublethally irradiated (200 rads) NSGS mice via X-ray guided intra-tibial injection.

Drug Treatments

CD34+ cells isolated from MF patients were transplanted into NSGS mice. Four-week post-transplant, xenografted animals were randomized into four groups to generate cohorts with equal levels of peripheral blood engraftment for treatment as follows: vehicle (5% dimethylacetamide/95% of 0.5% methylcellulose, 2x/day), INCB053914 (30 mg/kg, 2x/day), ruxolitinib, and JQ1 (50 mg/kg, 1x/day; MedChemExpress). Ruxolitinib was administered in chow formulation (2g ruxolitinib / 1kg chow; Incyte #INCB018424). Effects were evaluated at stated timepoints by flow cytometric and histological analysis as described above.

Statistics

Student t-test, one-way, and two-way ANOVA’s were used for statistical comparisons where appropriate (see figure legends for type of statistical test used for each experiment). Survival curves were analyzed using a Mantel-Cox logrank test. Significance is indicated using the following convention: *p <0.05, **p <0.01, ***p <0.001, ****p <0.0001. All graphs represent mean ± S.E.M.

STATEMENT OF SIGNIFICANCE.

Although the genetic events driving myeloproliferative neoplasms (MPNs) are well-defined, therapeutic discovery has been hampered by the inability of murine models to replicate key patient pathologies. Here, we present a patient-derived xenograft (PDX) system to model human myelofibrosis that reproduces human pathologies and is amenable to genetic and pharmacological manipulation.