Introduction

Myeloproliferative neoplasms (MPNs) comprise a group of chronic and heterogenous hematological malignancies that exhibit terminal myeloid cell expansion, including erythrocytes, thrombocytes, and leukocytes [1,2,3]. The three main Philadelphia chromosome–negative MPN subentities, polycythemia vera (PV), essential thrombocytosis (ET), and primary myelofibrosis (PMF), are characterized by chronic activation of the JAK-STAT pathway, resulting from transforming mutations in JAK2, calreticulin, or MPL genes [3,4,5,6,7,8]. Genetic analysis of patients with MPNs revealed that more than 95% of patients with PV and ∼50% of patients with ET or PMF carry an activating point mutation in the JAK2 gene (JAK2V617F) [9,10,11,12,13]. It is necessary to note that, despite the presence of the same JAK2V617F mutation, the clinical presentation of patients with different types of MPN varies considerably, which indicates that other “driver factors” also play an important role in MPNs.

The bone marrow (BM) niche is a complex and dynamic structure composed of a multitude of cell types which functionally create an interactive network that facilitates hematopoietic stem cell (HSC) development and maintenance [14,15,16,17]. Monocytes/macrophages are the key component of the BM microenvironment, which have been reported to support the development of erythroid cells [18,19,20], HSCs [21, 22], and megakaryocytes [23] in normal conditions. It has also been reported that macrophages promote erythroid cell [18, 24] and platelet production [23] in mouse models. In addition, Marina Dorigatti Borges et al. found that PB monocytes expressed several higher molecules, including cell adhesion, iron metabolism, and those capable of identifying and engulfing damaged and senescent erythrocytes, which suggests that monocytes may be more likely to attach erythroid cells and could, therefore, contribute to form erythroblastic islands (EBIs) if differentiated from macrophages [25]. In contrast, macrophages, which have been shown to induce the proliferation of myofibroblasts via vitamin D receptor signaling [26]], have been found to be increased in BM biopsies of PMF patients [27]. These studies demonstrate that monocytes/macrophages play distinct roles in MPNs; however, the roles of BM monocytes/macrophages in human MPN patients remain unclear.

Although experiments and clinical studies have revealed that the JAK2V617F mutation is associated with MPNs, the transcriptional consequences of the JAK2V617F mutation in different cellular components of the BM have not yet been fully elucidated. Using ScRNA-seq, Tong et al. report that HSCs with the JAK2V617F mutation in ET show strong megakaryocyte (Mk) lineage priming, are more sensitive to IFN signaling than to Mk differentiation, and exhibit distinct signatures upon treatment [3]. Van Egeren et al. found the same results of JAK2V617F mutant HSCs [28]. In addition, they also found that monocytes with JAK2V617F have a pro-inflammatory intermediate monocyte phenotype, and JAK2V617F monocytes express SLAMF7, which is associated with fibrosis in MPNs [28]. Maekawa et al. also report that SLAMF7high monocytes increased in the PB of patients with MF in correlation with the JAK2V617F mutation [4], and anti-SLAMF7 antibodies suppressed monocyte-derived fibrocyte differentiation and could be a potent therapeutic agent for MF [4]. Therefore, an understanding of the mechanism that drives activated monocytes/macrophages in MPN will guide strategies to target monocytes/macrophages in this disease.

In this study, we aimed to investigate the role of monocytes/macrophages in MPN patients with the JAK2V617F mutations. We performed flow cytometry to examine the expression of CD163, CD14, and CD16 in monocytes/macrophages from JAK2V617F mutant MPNs and present RNA-seq analysis of BM monocytes/macrophages of four healthy controls (HCs, also known as normal bone marrow, NBM), four PV patients, three ET patients, and five PMF patients. The analysis in our study shows that either CD163 or combined CD14 and CD16 are significantly elevated in MPN and correlates closely with the clinical phenotype of MPNs. RNA-seq analysis of BM monocytes/macrophages of four HCs, four PV patients, three ET patients, and five PMF patients demonstrated that different subtypes of MPN have relatively specific BM immune microenvironments. And the comprehensive transcriptomic characterization of BM monocytes/macrophages provides important resources to serve as a basis for future studies and future targets for the treatment of MPN patients.

Materials and methods

Patients and bone marrow samples

Eighty-five PV patients, 131 ET patients, and 42 PMF patients with the JAK2V617F mutation who were treated at the First Affiliated Hospital of Zhengzhou University between January 14, 2017, and March 05, 2021, were enrolled in this study for the analysis of peripheral blood routine and BM aspiration biopsy. An amount of 3–5 ml BM was aspirated from four HCs, four PV patients, three ET patients and five PMF patients. This study was approved by the Ethics Committee at the First Affiliated Hospital of Zhengzhou University. All methods and procedures associated with this study were conducted in accordance with the Good Clinical Practice guidelines and the ethical principles of the Declaration of Helsinki, as well as the local laws.

Preparation of single cell mononuclear cells and enrichment of CD163+ monocytes/macrophages

The BM of MPN patients were collected and processed for single-cell preparation for flow cytometry and enrichment of CD163+ monocytes/macrophages. The single cell suspensions were prepared as previously described [18, 29]. Then, BM CD163+ monocytes/macrophages from HCs and MPN patients were enriched with the CD163 MicroBead Kit (Miltenyi, Cat#:130–124-420), according to the manufacturer's instructions. BM cells were first incubated with CD163-biotin for 15 min on ice in the dark. The cells were then washed with PBS plus 2% FBS and 2 mM EDTA, centrifuged at 1200 rpm for 10 min, and then incubated with anti-biotin microbeads for 15 min on ice in the dark. The cells were again washed with PBS plus 2% FBS and 2 mM EDTA, again centrifuged at 300 g for 10 min, and then resuspended with 2-mL PBS plus 2% FBS and 2 mM EDTA. Finally, the BM CD163+ monocytes/macrophages were enriched with Quadro MACS, according to the manufacturer’s instructions.

Flow cytometry staining and analyses

Flow cytometry staining and analyses were performed as previous described [18, 29,30,31]. Briefly, 5 × 106 mononuclear cells (MNCs) were blocked with 50-μL human Fc receptor blocking (dilution 1:100) for 15 min at 4 °C, then stained with APC-CD163, Percp-CD14, and PE-CY7-CD16 for 30 min on ice in the dark. After staining, the cells were washed once with PBS plus 0.5% BSA and 2 mM EDTA. DAPI was used to gate out dead cells. Then the cells were resuspended with PBS plus 0.5% BSA and 2 mM EDTA, and run on a BD Air III (BD bioscience). Flow Jo software (BD) was used to analyze the data.

RNA-sequencing and analysis

RNA-seq was prepared and analyzed as previously described [29, 31,32,33,34]. RNA was extracted from the monocytes/macrophages of the control and MPN patients. Approximately 100 ng of total RNA was used as input for the cDNA library preparation, which was preformed using an Illumina TruSeq kit followed by sequencing with an Illumina HiSeq 4000 platform (Beijing Genomics Institute, BGI, China). Gene read counts for Gencode hg19 version 31 protein coding genes were generated using Kallisto for the analysis of the RNA-seq data. Differential gene expressions were examined with DESeq2, using a Wald test with a 0.05 adjusted p value cutoff and independent filtering to remove genes with lower expression levels, as previously described [29, 31,32,33,34]. The KEGG signaling pathway was performed as previously described [29, 31,32,33,34].

Cytospins and Giemsa-Wright staining

Cytospins and Giemsa-Wright staining of monocytes/macrophages from the control and MPN patients were performed as described in our previous papers [18, 29, 31].

Statistics

GraphPad Prism 9.0 software (GraphPad Software, Inc.) was used to perform the statistical analysis. All the experiments were repeated at least three times. All data were reported as mean ± SEM. Comparisons between different groups were performed by the student’s t test. Pearson correlation coefficient analysis was used to detect the correlations between monocytes/macrophages CD163 and CD14 combined with CD16 with the MPN phenotype. P < 0.05 was selected to indicate a statistically significant difference.

Results

The proportion of BM CD163+ or CD14+CD16+ monocytes/macrophages increased in MPN and correlated with different MPN subtypes

To evaluate the hypothesis that CD163+ monocytes/macrophages play significant roles in MPN, we collected the BM samples of MPN patients with the JAK2V617F mutation. We first confirmed that phenotype of distinct MPN using blood routine and BM biopsies (Supplementary Fig. 1A and B). Then, we examined the percentage of BM CD163+ monocytes/macrophages in the subtypes of MPN. Figure 1A demonstrates the representative flow cytometry image of CD163 in PV, ET, PMF, and HCs. A quantitative analysis indicated that the percentage of BM CD163+ monocytes/macrophages significantly increase in MPNs (Fig. 1B). Furthermore, the BM CD163+ monocytes/macrophages populations in HC and in MPNs were morphologically different (Fig. 1C). Next, we analyzed the correlation of the BM CD163+ monocyte/macrophage percentage with clinical phenotypes of MPNs. Figure 1D indicates that the BM CD163+ monocyte/macrophage percentage is positively correlated with the HGB levels in PV patients. Figure 1E shows that BM CD163+ monocyte/macrophage percentage is positively correlated with PLT in ET patients. In contrast, BM CD163+ monocyte/macrophage percentage is negatively associated with HGB in PMF patients (Fig. 1F). CD14+CD16+ monocytes/macrophages display an inflammatory function [30, 35, 36]. We next performed flow cytometry to analyze the CD14+CD16+ subset in CD163+ monocytes/macrophages in MPNs. Similarly, the percentage of the CD14+CD16+ subpopulation was also found to increase in PV, ET and PMF as compared to HCs (Supplementary Fig. 2A and B). The BM CD14+CD16+ subpopulation percentage is positively correlated with HGB in PV patients (Supplementary Fig. 2C), but is negatively correlated with HGB in PMF patients (Supplementary Fig. 2E), while there is no correlation between the CD14+CD16+ subpopulation percentage and PLT in ET patients (Supplementary Fig. 2D). Collectively, these data suggest that the BM monocyte/macrophage percentage correlates with MPN phenotypes.

Fig. 1
figure 1

The detection and correlation analysis between the percentage of BM CD163+ monocytes/macrophages and MPN phenotype. A Representative plot of CD163 versus FSC-H of DAPI− BM monocytes/macrophages in HC, PV, ET, and PMF. B Quantitative analysis of CD163 proportion in HC (N = 6), PV (N = 10), ET (N = 10), and PMF (N = 8). C Representative cytospin images of BM monocytes/macrophages in HC, PV, ET, and PMF. D The correlation between RBC, HGB and the percentage of BM CD163+ monocytes/macrophages in PV patients (N = 10). E The correlation between PLT and the percentage of BM CD163+ monocytes/macrophages in ET patients (N = 10). F The correlation between WBC, RBC, HGB, PLT, and the percentage of BM CD163+ monocytes/macrophages in PMF patients (N = 8)

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Significant transcriptional differences of monocytes/macrophages in PV patients compared to NBM

We then performed an RNA-seq analysis of BM monocytes/macrophages between treatment-naive PV patients and HCs to characterize the underlying molecular changes of the monocytes/macrophages. Principal component analysis (Fig. 2A) and hierarchical clustering analysis (Supplementary Fig. 3A) indicated that the monocytes/macrophages of treatment-naive PV patients clustered distinctly from those of HCs. A heatmap of the differential expression of genes between the two groups is shown in Fig. 2B. A total of 2,236 genes are differentially expressed, of which 1070 are upregulated and 1166 are downregulated in treatment-naive PV patients versus HCs (Supplementary Fig. 3B). All the differentially expressed genes are listed in Supplementary Table 1. Finally, the upregulated pathways of PV include cytokine–cytokine receptor interaction, cytokine and cytokine receptor, the Rap1 signaling pathway, the cGMP-PKG signaling pathway, platelet activation, and complement and coagulation cascades (Supplementary Fig. 3C). The downregulated pathways of PV include ribosome, cell cycle, oxidative phosphorylation, and the pathways of neurodegeneration-multiple diseases (Supplementary Fig. 3D).

Fig. 2
figure 2

Comparison of RNA-seq data of monocytes/macrophages between PV patients and healthy controls. A Principal component analysis between PV patients (N = 4) and healthy controls (N = 4). B Heatmap of the differentially expressed genes between PV patients (N = 4) and healthy controls (N = 4). C The FPKM value of cytokines and chemokines, CCL5, CXCL5, CXCL9, CXCL10, VEGF-C, and IL27 in PV and NBM. D The FPKM value of FCGR3A, CCR2, TLR1, TLR6, TLR8, and TLR9 in PV and NBM. E The FPKM value of C1QA, C1QB, and C2 in PV and NBM. F The FPKM value of APOL1, APOL2, APOL3, and APOL4 in PV and NBM. G The FPKM value of SLC25A16, SLC46A1, and SLC6A12 in PV and NBM. H The FPKM value of ITGA2, ITGA7, ITGB3, and ITGB5 in PV and NBM. I The FPKM value of NR1H3, CEBPA, and PPARGC1B in PV and NBM

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Our research, as well as that of other groups, indicates that the expression levels of genes encoding proteins that are known to be important for the macrophage function of supporting erythropoiesis include adhesion molecules, molecules for nucleus engulfment and digestion, iron recycling molecules, and growth factors [18,19,20,21, 24, 29, 37,38,39,40,41,42]. Fig. 2C demonstrates the increased cytokines and chemokines, including CCL5, CXCL5, CXCL9, CXCL10, and VEGF-C. Monocytes/macrophages in treatment-naive PV patients also increased some of the receptors expressed by inflammatory monocytes/macrophages [5, 40, 43,44,45], including FCGR3A, CCR2, TLR1, TLR6, TLR7, TLR8, and TLR9 (Fig. 2D). C1QA, C1QB, and C2 are phagocytosis facilitators [46], which also increased in treatment-naive PV patients (Fig. 2E). APOL families play an important role in lipid metabolism and transport [47]. Significantly, the expression of APOL1, APOL2, APOL3, and APOL4 increased in treatment-naive PV patients (Fig. 2F). Solute carrier families play significant roles in ions exchange and homeostasis [48]. Interestingly, the expression of SLC25A16, SLC25A30, SLC46A1, and SLC6A12 also increased in treatment-naive PV patients (Fig. 2G). Integrins are known to participate in cell adhesion as well as cell-surface-mediated signaling [49]. We found that the expression of ITGA2, ITGA7, ITGB3, and ITGB5 increased significantly in treatment-naive PV patients (Fig. 2H). Gene expression is regulated by transcription factors. Finally, we demonstrated that the expression of the transcription factors NR1H3, CEBPA, and PPARGC1B increased significantly in treatment-naive PV patients (Fig. 2I).

Monocytes/macrophages promote ET via several distinct mechanisms compared to NBM

Using the same approach, we examined transcriptional alterations in monocytes/macrophages in the BM microenvironment of ET patients. Principal component analysis (Fig. 3A) and hierarchical clustering analysis (Supplementary Fig. 4A) indicated that treatment-naive ET patients cluster differently from HCs. A heatmap of the differential expression of genes is shown in Fig. 3B. A total of 2161 genes are differentially expressed, of which 1040 are upregulated and 1121 are downregulated in treatment-naive ET patients versus HCs (Supplementary Fig. 4B). All the differentially expressed genes are listed in Supplementary Table 2. The KEGG pathways analysis demonstrated that the upregulated pathways of ET include platelet activation, cell adhesion molecules, ECM-receptor interaction, focal adhesion, and the regulation of actin cytoskeleton (Supplementary Fig. 4C). The downregulated pathways of ET include viral protein interaction with cytokine and cytokine receptors, oxidative phosphorylation, thermogenesis, the NF-kappa B signaling pathway, the TNF signaling pathway, and the IL-17 signaling pathway (Supplementary Fig. 4D).

Fig. 3
figure 3

Comparison of RNA-seq data of monocytes/macrophages between ET patients and healthy controls. A Principal component analysis between ET patients (N = 3) and healthy controls (N = 4). B Heatmap of the differentially expressed genes between ET patients (N = 3) and healthy controls (N = 4). C The FPKM value of CCL5, PDGFA, PDGFB, VWF, FGF13, EGF, and IGF2 in ET and NBM. D The FPKM value of ITGA2, ITGA2B, ITGA6, and ITGA9 in ET and NBM. E The FPKM value of SLC40A1 in ET and NBM. F The FPKM value of MMP9 and MMP25 in ET and NBM. G The FPKM value of FOS, ARG1 and CEBPA in ET and NBM

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Emerging evidence suggests that effective megakaryopoiesis depends on the homeostasis of the BM macrophage microenvironment [23, 50]. Fig. 3C demonstrates that the expression of CCL5, PDGFA, PDGFB, VWF, FGF13, EGF, and IGF2 increased significantly in treatment-naive ET patients. Integrins are known to mediate the adhesion of platelets and other cell types to the extracellular matrix to maintain the homeostasis of megakaryopoiesis [51]. Consistent with this, we found that the expression of ITGA2, ITGA2B, ITGA6, and ITGA9 increased significantly (Fig. 3D). SLC40A1 is involved in iron export from duodenal epithelial cells or macrophages, which is important for erythropoiesis [18]. Megakaryopoiesis also requires iron export macrophages. Significantly, the expression of SLC40A1 increased in treatment-naive ET patients (Fig. 3E). The matrix metalloproteinase (MMP) family is involved in the breakdown of extracellular matrix in normal physiological processes, such as embryonic development, reproduction, tissue remodeling, and megakaryocytes migration [52,53,54]. Fig. 3F indicates that the expression of MMP9 and MMP25 increased significantly. Studies have indicated that M2 macrophages, but not M1 macrophages, are significant for megakaryopoiesis [23]. Consistent with this, the expression of the M2 macrophage marker ARG1 increased significantly (Fig. 3G). Two transcription factors, FOS and CEBPA expressions, were also found to be expressed in treatment-naive ET patients (Fig. 3G).

Monocytes/macrophages of PMF distinct heterogeneous expression of M1 and M2 markers compared to NBM

We examined the transcriptional alterations in monocytes/macrophages in the BM microenvironment of PMF patients. Principal component analysis (Fig. 4A) and hierarchical clustering analysis indicated that treatment-naïve clustering in PMF patients differ from clustering in HCs (Supplementary Fig. 5A). A heatmap of the differential expression of genes is shown in Fig. 4B. A total of 2252 genes are differentially expressed, of which 1347 are upregulated and 905 are downregulated in treatment-naive ET patients versus HCs (Supplementary Fig. 5B). All the differentially expressed genes are listed in Supplementary Table 3. The upregulated pathway of PMF includes cytokine–cytokine receptor interaction, platelet activation, a JAK-STAT signaling pathway, complement and coagulation cascades, and Fc gamma R-mediated phagocytosis (Supplementary Fig. 5C). However, the downregulated pathways only include the coronavirus disease COVID-19 and ribosome (Supplementary Fig. 5D).

Fig. 4
figure 4

Comparison of RNA-seq data of monocytes/macrophages between PMF patients and healthy controls. A Principal component analysis between PMF patients (N = 5) and healthy controls (N = 4). B Heatmap of the differentially expressed genes between PMF patients (N = 5) and healthy controls (N = 4). C The FPKM value of FCGR1A, FCGR1B, FCGR1C, FCGR3A, FCGR3B, HLA-DOA, HLA-DPA1, and HLA-DPB1 in PMF and NBM. D The FPKM value of STAT1, IFITM1, IFITM2, IFITM3, IFIT1, IFIT2, IFIT3, and IFIT27 in PMF and NBM. E The FPKM value of CCL5, GAS6, CCL25, CXCL9, CXCL10, CXCL12, VEGF-C, EGF, VWF, PDGFA, PDGFB, and IL27 in PMF and NBM. F The FPKM value of SIGLEC1, VCAM1, AXL, CD5L, and SLAMF7 in PMF and NBM. G The FPKM value of SPIC in PMF and NBM

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It has been shown that macrophages increase in PMF [27]; however, transcriptional alterations in monocytes/macrophages in the BM microenvironment of PMF patients have not been performed. Figure 4C demonstrates that the expressions of FCGR1A, FCGR1B, FCGR1C, FCGR3A, FCGR3B, HLA-DOA, HLA-DPA1, and HLA-DPB1 increased significantly. Figure 4D indicates that many interferon-inducible genes, including STAT1, IFITM1, IFITM2, IFITM3, IFIT1, IFIT2, IFIT3, and IFIT27 increased significantly. We analyzed the production of cytokines and chemokines next and found that the expressions of CCL5, GAS6, CCL25, CXCL9, CXCL10, CXCL12, VEGF-C, EGF, VWF, PDGFA, PDGFB, and IL27 increased significantly (Fig. 4E). SIGLEC1, VCAM1, AXL, CD5L, and SLAMF7 were also found to be significantly increased (Fig. 4F), and, finally, we found that the transcription factor SPIC was also significantly increased (Fig. 4G).

Monocytes/macrophages in PMF, PV, and ET have relatively specific transcriptional profiles

We have shown that monocytes/macrophages in PMF, PV, and ET demonstrate distinct transcriptional expressed genes compared to NBM. To investigate the distinct transcriptional profiles of monocytes/macrophages in PMF, PV, and ET, we performed a two-by-two comparison of the transcriptional expression of monocytes/macrophages in the BM microenvironment of these three different types of MPN. Significantly, we still obtained similar results using this analysis (Supplementary 6A-F, Supplementary Tables 4, 5, and 6, Fig. 5A–H). Taken together, monocytes/macrophages may play relatively specific role in distinct MPNs.

Fig. 5
figure 5

Comparison of differential expression genes of monocytes/macrophages between PV, ET, and PMF patients. A The FPKM value of CCL18, CCL25, CXCL5, CXCL10, GAS6, IL15, IL27, IL18BP, and S100A12 in PV, ET and PMF. B The FPKM value of NR1H3, KLF1, HIF1α, MAFB, and ARG1 in PV, ET and PMF. C The FPKM value of STAT1, IRF1, IFITM3, IFI27, and AIM2 in PV, ET, and PMF. D The FPKM value of SLC2A5, SLC31A2, SLC40A1, and SLC6A12 in PV, ET and PMF. E The FPKM value of APOL1, APOL2, APOL3, and APOL4 in PV, ET and PMF. F The FPKM value of DNASE2, ICAM1, and MARCO in PV, ET and PMF. G The FPKM value of MMP8 and MMP9 in PV, ET, and PMF. H The FPKM value of HLA-DPB1, HLA-DQA1, HLA-DRB1, HLA-DMB, HLA-DRA, HLA-A, HLA-DMA and CD74 in PV, ET, and PMF

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Discussion

The classical view is that malignant clonal expansion of hematopoietic stem/progenitor cells is the central driver of MPN development, but the same JAK2V617F mutation allows MPN to manifest in three clinical phenotypes, namely PV, ET, and PMF [9,10,11,12]. Studies have illustrated the complexity of MPN pathogenesis and the heterogeneity of clinical manifestations well, and there is increasing evidence that the BM microenvironments may play important roles [55,56,57]. Medical interventions, immune dysregulation, and inflammation have all been shown to alter selective pressures for mutant clones in the BM. Transcriptome analysis of PBMCs has shown that MPN patients are significantly enriched for genes related to inflammation, immune response, and oxidative stress [58]. Immune infiltration analysis as well as mathematical modeling studies have also suggested the presence of complex immune remodeling in the MPN microenvironment [59, 60]. It has also been shown that there is significant immune activation in the microenvironments of MPN patients, including decreased levels of anti-inflammatory cytokines, increased levels of pro-inflammatory cytokines, as well as a significant Th1/Th2 immune bias [61]. Despite these studies, however, the role of monocytes/macrophages in the BM microenvironment in MPN is still unclear. In the present study, we found that CD163+ monocytes/macrophages in the BM of MPN increased significantly compared to HCs. Interestingly, there was significant variability in the morphology of monocytes/macrophages in different subtypes of MPN, suggesting that monocytes/macrophages may have relatively specific functions in the different subtypes of MPN. Correlation analyses showed a positive correlation between monocyte/macrophage counts and elevated hemoglobin in patients with PV. Monocyte/macrophage counts in ET patients were positively correlated with elevated platelets. In contrast, the monocyte/macrophage count in PMF patients was positively correlated with a decrease in hemoglobin. Overall, our study suggests that the BM monocyte/macrophage may associate to the development of MPN.

CD14+CD16+ monocytes/macrophages are thought to be involved in a variety of inflammation-related diseases in humans [62,63,64,65]. Bassan et al. reported that the peripheral blood CD14+CD16+ monocytes were significantly elevated in different MPN subtypes [66]. Importantly, the JAK2V617F mutation was significantly associated with the percentage of CD14+CD16+ monocytes. Borges et al. demonstrated that the peripheral blood CD14+CD16+ non-classical monocytes significantly expressed CD169, CD206, CD163, SIRPα, and CD106, which are involved in erythropoiesis, in PV [25]. Despite these findings, studies have mainly focused on peripheral blood inflammatory monocytes in MPN. In contrast, alterations in the immune microenvironment of the BM may be more influential in the development and progression of MPN. However, the role of CD14+CD16+ inflammatory monocytes/macrophages in the BM microenvironment in MPN is still unclear. In this study, we found that the percentage of CD14+CD16+ inflammatory monocytes/macrophages in BM increases in the three subtypes of MPN. Interestingly, the percentage of BM CD14+CD16+ inflammatory monocytes/macrophages was positively associated with hemoglobin in PV and platelets in ET. In contrast, the percentage of BM CD14+CD16+ inflammatory monocytes/macrophages was negatively associated with hemoglobin in PMF. In conclusion, our study demonstrates for the first time that inflammatory monocytes/macrophages are elevated in different subtypes of MPN and further confirms that the BM microenvironment of MPN presents an inflammatory microenvironmental state.

Macrophages can promote erythropoiesis through a number of different mechanisms [18,19,20, 24, 29, 39, 40]. The removal of macrophages from PV mice resulted in a significant decrease in erythrocytes and hemoglobin, suggesting that macrophages are also involved in the development of PV [67]. In the present study, we performed RNA-seq of CD163+ monocytes/macrophages from PV and NBM. Our study found that several cytokines and chemokines, such as CCL5, CXCL5, CXCL9, CXCL10, VEGF-C and IL27, increased significantly compared to NBM. Fang et al. demonstrated that VEGF-C is essential for the mobilization, maturation, and enucleation of primitive erythroblasts, and VEGF-C deletion compromises liver colonization by erythro-myeloid progenitors and subsequent macrophage/erythroid expansion [68]. The same group also indicates that VEGF-C deletion in endothelial or LepR+ cells compromises the bone marrow perivascular niche and hematopoietic stem cell maintenance and exogenously administered VEGF-C improves hematopoietic recovery after irradiation by accelerating endothelial and LepR+ cell regeneration [69]. Therefore, VEGF-C is significant for erythropoiesis, and our study extends the understanding of the role of monocytes/macrophages’ VEGF-C in the development of PV. Our study indicates that GM-CSF causes erythrocytopenia by affecting the formation of EBI [29]. IL27 suppresses the GM-CSF expression [70]. Therefore, IL27 may be a novel cytokine that can promote the production of red blood cells, and further studies should be performed to confirm this. Furthermore, it would also be worth examining the roles of other cytokines or chemokines that are enhanced in the development of PV. The immune microenvironment of PV patients is an inflammatory microenvironment, and an inflammatory microenvironment in BM inhibits erythropoiesis [29, 71] and induces extramedullary erythropoiesis [40, 72]. This is also illustrated by our data on the elevated expression of TLRs and FCGR3A in PV. CCR2 is significant for the homing of HSCs/HPCs to sites of inflammation [44], and CCR2+ monocyte-derived macrophages expand the murine stress erythropoietic niche during recovery from anemia [40]. In conjunction with our finding of an elevated monocyte/macrophage CCR2 expression in the BM microenvironment of PV patients, we hypothesize that PV patients may also have an inflammatory microenvironment that recruits CCR2+ monocytes into the BM microenvironment to differentiate into EBI macrophages that promote erythropoiesis. This should be verified in the future in a mouse model of PV. C1QA [73], C1QB [74], and C2 [74] are significant for phagocytosis. APOL1, APOL2, APOL3, and APOL4 are significant for lipid metabolism [47, 75]. SLC25A16, SLC46A1, and SLC6A12 are significant for ion transport, and ITGA2, ITGA7, ITGB3, and ITGB5 are significant for cell adhesion. These genes may be involved in the occurrence and progression of PV; however, more research should be conducted to demonstrate this. Furthermore, the increased expression of transcription factors in PV included Nr1H3, CEBPA, and PPARGC1B. The exact role of these genes in PV is unclear, and more studies should be conducted to confirm the role of these genes in PV.

Huang’s group report that TGF-β released by M2 macrophages may facilitate megakaryopoiesis through the upregulation of the JAK2/STAT5 and MAPK/ERK pathways in megakaryocytes [23]. In the present study, the expression of ARG1, a specific marker for M2 macrophages, was significantly enhanced in ET. The finding in our study confirms that macrophages in ET patients incline more to the M2 type. We also found that several cytokines and chemokines expressed by monocytes/macrophages were significantly enhanced in ET patients. Previous studies have indicated that CCL5 enhances megakaryocyte differentiation and development [76,77,78,79]. We found in our study that CCL5 expression by monocytes/macrophages was significantly elevated in ET, which further demonstrates that monocytes/macrophages can promote platelet production by secreting CCL5. Previous studies have also found that EGF transcript levels and cytokine levels from platelets were significantly elevated in ET [80, 81]. Our study extends the origin of EGF to monocytes/macrophages in ET. MMP9 is involved in platelet formation and the migration of megakaryocytes [52, 53, 82]. We found that monocyte/macrophage expression of MMP9 was significantly elevated in ET patients, which revealed a novel mechanism of platelet production promotion by monocytes/macrophages. Other cytokines, such as PDGFA, PDGFB, VWF, FGF13, and IGF2; cell adhesion molecules, such as ITGA2, ITGA2B, ITGA6, and ITGA9; the iron exporter gene, SLC40A1, matrix metalloproteinase family gene; MMP25 and transcription factors FOS, and CEBPA have also been found to be increased in ET patients. However, the exact roles of these genes expressed by monocytes/macrophages in ET are unclear, and more studies should be conducted to confirm the role of these genes in ET.

Several studies on mouse models have been used to explain the mechanism of myelofibrosis development caused by megakaryocytes [83, 84], stromal cells [85, 86], monocytes [4, 87], and macrophages [26, 88]. However, the transcriptional expression of monocytes/macrophages in PMF patients is still not completely clear. In the present study, we found that the expression of FCGR1A, FCGR1B, FCGR1C, FCGR3A, FCGR3B, HLA-DOA, HLA-DPA1, and HLA-DPB1; the interferon-inducible genes STAT1, IFITM1, IFITM2, IFITM3, IFIT1, IFIT2, and IFIT3; and IFI27 by monocytes/macrophages increased significantly in PMF. These genes expressed by monocytes/macrophages correlate with an inflammatory microenvironment. Our study further confirms that PMF bone marrow microenvironment is an inflammatory microenvironment. Studies have indicated that PDGF-A and -B, as well as PDGF receptor α (PDGFRα) and PDGF receptor β (PDGFRβ) expression is increased in the BM of PMF patients [89]. Decker et al. identified Lepr+ stromal lineage cells as the origin of myofibroblasts in PMF. The PDGFRA pathway in BM Lepr+ cells lead to the expansion of these cells and extramedullary hematopoiesis, and this suggests that targeting PDGFRA signaling could be an effective way to treat BM fibrosis [86]. Kramer et al. have demonstrated that PDGFRβ and PDGF-B protein expression in overt fibrotic BM and PDGFRβ–PDGF-B interaction were significantly increased [90]. In the present study, we found that the expression of PDGFA and PDGFB derived from monocytes/macrophages increased significantly. Mouse models should also confirm the roles of PDGFA and PDGFB derived from monocytes/macrophages in PMF. The expression of CXCL12 by perivascular mesenchymal stromal cells (MSCs) plays an essential role in HSC maintenance [91,92,93]. Wang et al. report that the splenic microenvironment in MF is characterized by increased levels of intact, functional CXCL12, which contributes to the localization of MF CD34+ cells to the spleen and the establishment of extramedullary hematopoiesis [94]. In the present study, we found that CXCL12 expression by monocytes/macrophages significantly increase in PMF patients. Therefore, we hypothesize that elevated CXCL12 expression may play a compensatory hematopoietic role in the PMF BM hematopoietic microenvironment, and further studies should be conducted to confirm the role of CXCL12 expressed by BM monocytes/macrophages in PMF mouse models. The expression of CCL5 and CXCL9 were also found to be increased in PMF mouse models [95]. Our study confirms that the expression of CCL5 and CXCL9 from monocytes/macrophages also increased in PMF patients. Beitzen-Heineke et al. found that AXL is abundantly activated in MPN cells and that its ligand growth arrest-specific gene 6 is upregulated in MPN patients [96]. The findings from our present study, which involved the expression of AXL and GAS6 from monocytes/macrophages in PMF patients, are consistent with their findings. Xu et al. report that the soluble vascular cell adhesion molecule-1 (sVCAM-1) increases dramatically in myelofibrosis [97]. Increased VCAM1 expression may contribute to the retention of hematopoietic stem cells/PCs in the spleen and play a role in the initiation of extramedullary hematopoiesis in the early stages of MF [98, 99]. Our study found that VCAM1 expressed by monocytes/macrophages in PMF increases significantly. Further studies should be conducted to examine the roles of monocytes/macrophages VCAM1 in PMF models. Maekawa et al. found that SLAMF7high monocytes increase in the PB of patients with MF, in correlation with the JAK2V617F mutation and anti-SLAMF7 antibodies suppressed monocyte-derived fibrocyte differentiation and could be a potent therapeutic agent for MF [4]. In this study, we found that the expression of SLAMF7 in monocytes/macrophages increase significantly in the BM of PMF patients with the JAK2V617F mutation and confirmed that SLAMF7 could be a new therapeutic target for PMF.

In normal conditions, the expression of SPIC by macrophages is significant for iron metabolism [100, 101]. Our previous study also demonstrates that EBI macrophages, but not non-EBI macrophages, express SPIC, which provides iron for erythropoiesis [18]. Inflammatory disorders and infections are associated with cytopenias, including anemia and thrombocytopenia [43]. In a mouse model of macrophage activation syndrome, Akilesh et al. demonstrated that TLR7 or TLR9 signaling in monocytes causes these cells to differentiate into inflammatory hematophagocytes (iHPCs), which highly expressed SPIC [43], and the iHPCs showed higher phagocytic uptake of RBCs [43]. In combination, the increased expression of SPIC in PMF may share similar function to inflammatory disorders. Further studies are also required to examine the exact role of SPIC in PMF models.

Studies have shown that PV is more easily converted into PMF than ET and that the BM microenvironment may play an important role in this process [102, 103]. We compared the transcriptional differences between the monocytes/macrophages in PV, ET, and PMF. Consistent with the easier conversion of PV to PMF, the transcriptional profile of monocytes/macrophages in PV is more similar to those of PMF relative to ET. The differences in the monocyte/macrophage expression profiles in PMF compared to ET patients were both different and identical to those in PMF and in healthy controls. These genes included CCL25, CXCL10, GAS6, IL27, NR1H3, MAFB, STAT1, IFITM3, IFI27, SLC31A2, SLC6A12, APOL1, APOL2, APOL3, APOL4, ICAM1, MARCO, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DRB1, HLA-DMB, HLA-DRA, HLA-A, HLA-DMA, and CD74. According to our study, it seems that many genes of monocytes/macrophages could be involved in PV, ET, and PMF and play similar or specific roles in these three MPN subtypes. Further studies should be performed to confirm the roles of these genes in distinct types of MPN.

However, this study has limitations. The way that differentially expressed genes regulate the development of distinct MPNs should be studied further. Single-cell sequencing of monocytes/macrophages in different subtypes of MPN should also be performed to investigate the similarities and differences in monocytes/macrophages in different subtypes of MPN in-depth. And independent studies are required to confirm the findings of this study. Nevertheless, we have characterized that BM CD163 or CD14 in combination with CD16 expression in monocytes/macrophages increase and may correlate with the clinical phenotypes of MPN. Transcriptome sequencing of monocytes/macrophages in PV, ET, and PMF also showed relatively specific transcriptional profiles of monocytes/macrophages in these three types of MPN, which suggests that monocyte/macrophage-mediated immune remodeling of different subtypes of MPN may also plays a role in MPN.