Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Feb 1.
Published in final edited form as: Exp Hematol. 2023 Nov 23;130:104131. doi: 10.1016/j.exphem.2023.11.005

Transcriptional and Functional Consequences of Oncostatin M Signaling on Young Dnmt3a-Mutant Hematopoietic Stem Cells

Logan S Schwartz 1,2, Kira A Young 1, Timothy M Stearns 1, Nathan Boyer 1, Kristina D Mujica 1, Jennifer J Trowbridge 1,2,*
PMCID: PMC10922717  NIHMSID: NIHMS1950809  PMID: 38000729

Abstract

Age-associated clonal hematopoiesis (CH) occurs due to somatic mutations accrued in hematopoietic stem cells (HSCs) that confer a selective growth advantage in the context of aging. The mechanisms by which CH-mutant HSCs gain this advantage with aging are not comprehensively understood. Using unbiased transcriptomic approaches, we identified Oncostatin M (OSM) signaling as a candidate contributor to age-related Dnmt3a-mutant CH. We found that Dnmt3a-mutant HSCs from young adult mice (3–6 months old) subjected to acute OSM stimulation do not demonstrate altered proliferation, apoptosis, hematopoietic engraftment, or myeloid differentiation. Dnmt3a-mutant HSCs from young mice do transcriptionally upregulate an inflammatory cytokine network in response to acute in vitro OSM stimulation as evidenced by significant upregulation of the genes encoding IL-6, IL-1β and TNFα. OSM-stimulated Dnmt3a-mutant HSCs also demonstrate upregulation of the anti-inflammatory genes Socs3, Atf3 and Nr4a1. In the context of an aged bone marrow (BM) microenvironment, Dnmt3a-mutant HSCs upregulate pro-inflammatory genes but not the anti-inflammatory genes Socs3, Atf3 and Nr4a1. The results from our studies suggest that aging may exhaust the regulatory mechanisms that HSCs employ to resolve inflammatory states in response to factors such as OSM.

Graphical Abstract

graphic file with name nihms-1950809-f0001.jpg

INTRODUCTION

The process of aging has a profound impact on tissues and cells throughout the body. In the hematopoietic stem and progenitor cell (HSPC) compartment, aging is accompanied by acquisition of somatic mutations. Given the long-lived nature of the HSPC pool, these mutations can be propagated for many cellular generations and through most mature hematopoietic cell progeny. While most of these somatic mutations are considered ‘neutral’, a subset can confer a selective growth advantage to HSPCs, leading to a condition termed age-associated clonal hematopoiesis (CH). The most common CH mutations are found in a subset of genes that encode canonical epigenetic or chromatin regulatory proteins such as DNA methyltransferase 3A (DNMT3A), tet methylcytosine dioxygenase 2 (TET2) and additional sex combs like-1 (ASXL1)[1, 2]. While CH is not a disease per se, it is associated with increased risk of age-associated pathologies such as blood cancers and ischemic stroke[1–7]. Understanding the cellular and molecular mechanisms underlying the selective advantage of HSPCs harboring somatic mutations, and how and in whom this is a risk factor for age-associated disease, will further inform our understanding of CH-associated conditions.

By creating and utilizing genetically engineered mouse models, many research groups have reported functional and molecular consequences of the most common human CH-associated mutations in DNMT3A, TET2, and ASXL1[1, 2, 7–9]. In some of these studies, chronic stress and inflammation were found to act as selective pressures contributing to expansion of CH and development of CH-associated pathologies[1, 10, 11]. CH-mutant HSCs have different molecular and functional responses to pro-inflammatory cytokine signaling[12, 13], and recent work suggests that CH-mutant hematopoietic cells can induce and maintain a pro-inflammatory state[14]. For example, Dnmt3a-mutant hematopoiesis is associated with elevated levels of IFNγ[15, 16], IL-6[17] and TNFα[18]. Tet2-mutant hematopoiesis is associated with elevated levels of IL-6[19], IL-8[20], IL-1β[21–23] and TNFα[24]. Asxl1-mutant CH is associated with increased IFNγ and TNFα[25]. The extent to which multiple cytokines activate the same underlying inflammatory network contributing to CH and CH-associated pathologies, or whether individual cytokines have context-dependent effects, remains unknown. Addressing this gap in knowledge is important when considering therapeutic interventions that will be most effective in individuals at risk of CH-associated pathologies.

Using a Cre-inducible mouse model that we previously engineered to express a specific Dnmt3a mutation associated with CH and acute myeloid leukemia (Dnmt3aR878H)[26], we found that placing Dnmt3a-mutant HSPCs in a middle-aged BM microenvironment in the context of elevated pro-inflammatory cytokines promoted their selective advantage[18]. We discovered that TNFα:TNFR1 signaling was a key mediator of the selective advantage of Dnmt3a-mutant HSCs in the context of a middle-aged BM microenvironment[18]. However, as described above, TNFα is not the only cytokine known to contribute to Dnmt3a-mutant CH. Here, we report on our findings investigating Oncostatin M (OSM) as a pro-inflammatory cytokine associated with CH in Dnmt3a-mutant mice.

RESULTS

Dnmt3a-Mutant HSCs Activate Oncostatin M (OSM) Signaling in an Aged Bone Marrow Microenvironment

Our previously published work profiled molecular signatures associated Dnmt3a-mutant (R878H/+) hematopoiesis in a middle-aged BM microenvironment by performing RNA sequencing (RNA-seq) on independent biological replicates of control and Dnmt3a-mutant HSCs re-isolated from young and middle-aged recipient mice[18] (Figure 1A). In new analysis of these data, enrichment of a hallmark inflammatory response signature was observed in Dnmt3a-mutant HSCs compared to control HSCs in middle-aged recipient mice but not in young recipient mice (Figure 1B), suggesting that a middle-aged environment promotes transcriptional responses in Dnmt3a-mutant HSCs to inflammatory factors. Examining the top leading-edge genes using gene set enrichment analysis (GSEA), increased expression of the IFNγ-regulated genes Bst2, Klf6 and Icam1, the inflammatory-responsive receptors Tlr2 and Ccrl2, and the copper transporter Slc31a2 was observed. Osm was the only leading-edge gene encoding a secreted molecule, Oncostatin M (OSM), which is an IL-6 family cytokine known to be involved in the immunopathogenesis of solid tumors and myeloma [27–31]. Given this observation, we hypothesized that increased expression of Osm results in a feed-forward loop of activation of the OSM signaling pathway.

Figure 1. Dnmt3a-mutant HSCs upregulate Osm and OSM signaling genes in a middle-aged BM environment.

Figure 1.

Open in a new tab

(A) Schematic of transplant design into young (2mo) and middle-aged (13–14mo) recipient mice. HSCs (Lin− c-Kit+ Sca-1+ Flt3− CD150+ CD48−) were isolated at 4 months post-transplant and used for RNA-sequencing[18]. n = 3–4 biological replicates. (B) Gene set enrichment analysis of a hallmark inflammatory response signature in control vs. Dnmt3a-mutant (R878H/+) HSCs in young recipient mice (left) and in middle-aged recipient mice (right). (C) Heatmap of log2(FC) expression in OSM signaling pathway genes in Dnmt3a-mutant (R878H/+) compared to control HSCs in young (left column) and middle-aged (right column) recipient mice. *P<0.05. (D) Ingenuity pathway analysis showing predicted activation of OSM signaling in Dnmt3a-mutant (R878H/+) vs. control HSCs in middle-aged recipient mice.

To test this hypothesis, we interrogated the expression of a subset of genes known to be involved in and/or regulated by OSM signaling including transcripts encoding OSM signaling receptors (Osmr, Il6st), downstream kinases and signaling molecules (ex. Shc1, Mapk14, Prkcb, Nfkb1), and transcription factor targets (ex. Egr1, Fos, Junb, Jund). We observed trends toward increased expression and significant increase in expression (P<0.05) in most genes examined in Dnmt3a-mutant HSCs compared to control HSCs in middle-aged recipient mice but not in young recipient mice (Figure 1C). We used the upstream regulator analysis feature of ingenuity pathway analysis (IPA) as a complementary approach to examine activation of OSM signaling in Dnmt3a-mutant HSCs compared to control HSCs in middle-aged recipient mice. Activation of an OSM-driven IL-6:STAT3 module was observed in Dnmt3a-mutant HSCs in middle-aged recipient mice (Figure 1D). These results are consistent with activation of OSM signaling in Dnmt3a-mutant HSCs in the specific context of a middle-aged environment.

Acute OSM Stimulation Does Not Impact Cell Cycle, Apoptosis, Proliferation or Myeloid Differentiation of Young Dnmt3a-Mutant HSPCs

Given that activation of OSM signaling is associated with expanded Dnmt3a-mutant hematopoiesis in an aged BM microenvironment, we hypothesized that OSM as a single stimulus would be sufficient to promote the selective advantage of young Dnmt3a-mutant HSPCs. To test the effect of recombinant OSM on young Dnmt3a-mutant HSPC cycling, cell cycle status was evaluated using Ki-67 and DAPI staining. Control and Dnmt3a-mutant HSPCs were prospectively isolated from young adult mice (3–6 months old) and stimulated overnight with 0, 100 or 500ng/ml recombinant murine OSM. Following flow cytometry analysis, cells were gated into G0 (Ki-67− DAPI−), G1 (Ki-67+ DAPI−) and S/G2/M (Ki-67+ DAPI+) fractions. No significant differences were observed in these proportions across any of the conditions, although there was a trend towards increased S/G2/M in Dnmt3a-mutant HSPCs with increasing doses of OSM (Figure 2A). To test the effect of recombinant OSM on young Dnmt3a-mutant HSPC survival, apoptosis was assessed using Annexin V and PI staining. Control and Dnmt3a-mutant HSPCs were prepared and stimulated overnight as detailed above. Following flow cytometry analysis, cells were gated into live (Annexin V− PI−), early apoptotic (Annexin V+ PI−), late apoptotic (Annexin V+ PI+), and necrotic (Annexin V− PI+) fractions. No significant differences in these proportions were observed across any of the conditions (Figure 2B). Together, these data suggest that young control and Dnmt3a-mutant HSPCs do not respond to acute OSM stimulation with respect to altered cell cycle and apoptosis parameters.

Figure 2. Cell cycle, apoptosis, proliferation, and myeloid differentiation in young Dnmt3a-mutant HSPCs are unaltered by acute OSM stimulation.

Figure 2.

Open in a new tab

(A) Frequency of control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs in G0, G1, and S/G2/M cell cycle phases after stimulation with 0, 100, or 500ng/ml OSM for 24hrs. Bars represent mean ± SEM of n = 3. (B) Frequency of control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs in live, early apoptotic, late apoptotic or necrotic gates after stimulation with 0, 100, or 500ng/ml OSM for 24hrs. Bars represent mean ± SEM of n = 3. (C) Colony-forming units (CFU) in control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs with 0, 100 or 500ng/ml OSM. Dots show individual mice. n = 5. (D) Serial CFU in control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs (left) and HSCs (right) with 0 or 500ng/ml OSM. Dots show individual mice, bars represent mean ± SEM of n = 3–4. **p < 0.01; ****p < 0.0001 by two-way ANOVA with Tukey’s multiple comparisons test. (E) Total viable cells from control (+/+) and Dnmt3a-mutant (R878H/+) HSCs, MPPG/M and GMP after 48h culture with 0 or 500ng/ml OSM. Dots show individual mice, bars represent mean ± SEM of n = 3.

To test the effect of recombinant OSM on myeloid differentiation potential, control and Dnmt3a-mutant HSPCs were prospectively isolated from young adult mice and plated into a myeloid methylcellulose media to quantify colony-forming units (CFU). The myeloid methylcellulose media was supplemented with 0, 100 or 500ng/ml recombinant murine OSM. After 7-day culture, no differences in CFU formation were observed across any of the conditions (Figure 2C). This result suggests that control and Dnmt3a-mutant HSPCs do not respond to OSM with respect to altering their myeloid differentiation potential. To examine CFU re-plating potential, control and Dnmt3a-mutant HSPCs as well as HSCs with 0 or 500ng/ml recombinant murine OSM continued to be passaged. As expected, increased CFU re-plating potential from Dnmt3a-mutant vs. control HSPCs and HSCs was observed (Figure 2D). However, there was no observed effect of OSM on either control or Dnmt3a-mutant CFU re-plating capacity.

A limitation of the above CFU studies is that the effect of OSM is being evaluated in the presence of a full complement of cytokines that drive robust myelo/erythroid cell differentiation (SCF, IL-3, IL-6, and EPO). To examine the effects of OSM on HSPC proliferation in conditions replicating stress, 0 or 500ng/ml recombinant murine OSM was added to previously defined ‘cytokine-poor’ (SCF, G-CSF) and ‘cytokine-rich’ (SCF, GM-CSF, IL-3, IL-11, Flt3L, TPO, EPO) medias[32] to replicate stress and non-stress conditions, respectively. Control and Dnmt3a-mutant HSCs, as well as two progenitor populations (granulocyte/macrophage-primed multipotent progenitors or MPPG/M and granulocyte-macrophage progenitors or GMPs), were prospectively isolated from young adult mice and cultured in cytokine-poor and cytokine-rich medias for 48 hours. After this culture period, total viable cell counts were obtained using flow cytometry. No significant differences in total viable cell counts were observed between genotype and treatment groups for any of the input cell populations (Figure 2E). Together, these data suggest that young control and young Dnmt3a-mutant HSPCs do not respond to acute OSM stimulation by altered cell cycling, apoptosis, myeloid differentiation, or proliferation.

Acute OSM Stimulation Does Not Alter Engraftment Potential or Lineage Output from Young Dnmt3a-Mutant HSPCs

As in vitro assays do not fully reflect the in vivo functional potential of HSPCs, we next tested the hypothesis that recombinant OSM as a single stimulus would be sufficient to promote the selective advantage of young Dnmt3a-mutant (R878H/+) HSPCs and HSCs in vivo. First, 50 prospectively isolated HSCs from young adult donor CD45.2+ control or Dnmt3a-mutant mice were cultured in conditions designed to promote HSC self-renewal[33] supplemented with 500ng/ml recombinant murine OSM or vehicle control (Figure 3A). After 7d culture, the resulting cells in each well were transplanted into lethally irradiated CD45.1+ recipient mice to assess hematopoietic engraftment and lineage potential. At 16wks post-transplant, no significant differences were observed in donor engraftment (% CD45.2+) in the peripheral blood or bone marrow of recipient mice (Figure 3B). Analysis of lineage composition of the peripheral blood graft revealed an increased proportion of B cells from Dnmt3a-mutant vs. control vehicle-treated HSCs, as we have previously observed[18] (Figure 3C). However, no significant differences were observed in peripheral blood lineage composition in recipient mice based on acute OSM stimulation. We also did not observe changes in donor-derived bone marrow HSPCs subsets due to acute OSM stimulation, including HSCs, MPPG/M, common myeloid progenitors (CMP) and GMP (Figure 3D).

Figure 3. Engraftment potential and lineage output from young Dnmt3a-mutant HSPCs is unaltered by acute OSM stimulation.

Figure 3.

Open in a new tab

(A) Schematic of transplant design. (B) Frequency of donor CD45.2+ cells in the peripheral blood (PB) and bone marrow (BM) at 16wks post-transplant of control (+/+) and Dnmt3a-mutant (R878H/+) HSCs treated with 0 or 500ng/ml OSM for 7d. (C) Donor-derived PB lineage (myeloid, B and T cell) frequencies. (D) Donor-derived BM hematopoietic stem and progenitor cell frequencies. (E) Schematic of competitive transplant design. (F) Normalized frequency of donor CD45.2+ cells in PB and BM at 16wks post-transplant of control (+/+) and Dnmt3a-mutant (R878H/+) HSCs treated with 0 or 500ng/ml OSM for 7d. (G) Donor-derived PB lineage (myeloid, B and T cell) frequencies. (H) Donor-derived BM hematopoietic stem and progenitor cell frequencies. In all figures, dots show individual mice and bars represent mean ± SEM of n = 3–8. **p < 0.01 by two-way ANOVA with Tukey’s multiple comparisons test.

To evaluate the effect of OSM on cellular competition between Dnmt3a-mutant and control hematopoiesis, we utilized competitive transplantation. 25 prospectively isolated HSCs from young adult donor CD45.2+ control or Dnmt3a-mutant mice were mixed with 25 prospectively isolated HSCs from competitor CD45.2+ CD45.1+ (F1 hybrid) mice. These were cultured in the same conditions as above, supplemented with 500ng/ml recombinant murine OSM or vehicle control (Figure 3E). After 7-day culture, the resulting cells in each well were transplanted into lethally irradiated CD45.1+ recipient mice to assess hematopoietic engraftment and lineage potential. At 16wks post-transplant, no significant differences in donor engraftment (% CD45.2+) were observed in the peripheral blood or bone marrow of recipient mice (Figure 3F). Analysis of lineage composition of the peripheral blood graft revealed an increased proportion of B cells from Dnmt3a-mutant vs. control vehicle-treated HSCs (Figure 3G), consistent with the findings above. However, no significant differences were observed in peripheral blood lineage composition in recipient mice based on acute OSM stimulation. In addition, no changes were observed in donor-derived bone marrow HSPCs subsets due to acute OSM stimulation, including HSCs, MPPG/M, CMP and GMP (Figure 3H). Together, these data suggest that acute OSM stimulation does not lead to changes in engraftment or lineage potential of young Dnmt3a-mutant HSPCs in non-competitive or competitive transplant.

Young Dnmt3a-Mutant HSCs are Responsive to Acute OSM Stimulation via STAT3 Phosphorylation and Transcriptional Alterations

Based on a lack of phenotypic alterations associated with recombinant OSM stimulation of young control and young Dnmt3a-mutant HSCs in vitro and in vivo, we evaluated the extent to which these cells have the capacity to directly bind and respond to recombinant murine OSM. We first considered antibody-based assessment of levels of the OSM receptor subunit OSMR on the cell surface. Due to a lack of specific and commercially available anti-mouse OSMR antibodies[34], recombinant OSM was fluorescently labeled (OSM-AF488) and used to test binding and labelling of Dnmt3a-mutant and control HSCs, in comparison to negative (no OSM-AF488) and positive (liver cells with OSM-AF488) controls. OSM-AF488 was found to bind both control and R878H/+ HSCs (Extended Data Figure 1A), supporting that control and Dnmt3a-mutant HSCs are capable of directly binding recombinant murine OSM.

To test STAT3 activation by recombinant OSM, we prospectively isolated control and Dnmt3a-mutant HSPCs from young adult mice, stimulated ex vivo with 500ng/mL of recombinant murine OSM over a time course and evaluated phosphorylation of STAT3 and STAT5 by flow cytometry (Figure 4A). Acute OSM stimulation of Dnmt3a-mutant HSPCs resulted in greater pSTAT3 compared to vehicle-stimulated Dnmt3a-mutant HSPCs as well as compared to OSM-stimulated control HSPCs after 60min (Figure 4B). No differences were observed in pSTAT3 in any condition after 20min stimulation or 80min stimulation, indicating tight regulation of the OSM-STAT3 signaling response. No differences were observed in pSTAT5 in any condition at any of the tested time points (Extended Data Figure 1B), demonstrating selectivity of acute OSM signaling response towards STAT3 activation in young Dnmt3a-mutant HSPCs.

Figure 4. Acute OSM stimulation activates STAT3 phosphorylation and transcriptional responses in young Dnmt3a-mutant HSCs.

Figure 4.

Open in a new tab

(A) Schematic of experimental design. (B) Mean fluorescence intensity (MFI) of pSTAT3 (Y705) in control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs treated with 0 or 500ng/ml OSM for 20, 60 and 80min. Dots show individual mice and bars represent mean ± SEM of n = 6–10. **p < 0.01; ***p < 0.001 by mixed-effects analysis with Tukey’s multiple comparisons test. (C, D) Volcano plot showing differential gene expression of (C) control (+/+) and (D) Dnmt3a-mutant (R878H/+) HSCs treated with 0 or 500ng/ml OSM for 60min. n = 6 biological replicates. Select genes involved in STAT3 signaling and inflammation are labelled. (E, F) Enrichment analysis of significantly differentially expressed genes in (E) control (+/+) and (F) Dnmt3a-mutant (R878H/+) HSCs treated with 500ng/ml vs. 0ng/ml OSM for 60min.

We tested the transcriptional consequences of OSM-STAT3 signaling in a more purified control and Dnmt3a-mutant HSC population. Control and Dnmt3a-mutant HSCs were prospectively isolated from young adult mice, stimulated ex vivo with 500ng/mL of recombinant murine OSM or vehicle control for 60min and immediately flash froze cell pellets for RNA extraction and RNA-seq. We identified significantly differentially expressed genes comparing OSM- vs. vehicle-treated control HSCs, and OSM- vs. vehicle-treated Dnmt3a-mutant HSCs, using P < 0.05 and fold change (FC) ± 1.5 cutoffs. This analysis revealed OSM-treated control HSCs had 385 genes increased in expression and 391 genes decreased in expression (Figure 4C). In contrast, OSM-treated Dnmt3a-mutant HSCs had 507 genes increased in expression and 299 genes decreased in expression (Figure 4D). Of the 385 OSM-activated genes in control HSCs and the 507 OSM-activated genes in Dnmt3a-mutant HSCs, only 19 were overlapping, suggesting a fundamentally distinct transcriptional response of young Dnmt3a-mutant HSCs to acute OSM. Delving further into specific gene alterations, we noted that acute OSM-stimulated Dnmt3a-mutant HSCs had robust upregulation of several key inflammatory molecules, receptors and response factors including Il6, Il1b, Tnf, Il1r2, Csf3r, Ccr1 and Irf1. Apart from Il1b, these were not upregulated in OSM-stimulated control HSCs. These data suggests that a 60min stimulation of young Dnmt3a-mutant HSCs with recombinant OSM is sufficient to induce transcriptional upregulation of inflammatory cytokines associated with Dnmt3a-mutant clonal hematopoiesis.

To further interrogate these transcriptional signatures, we performed enrichment analyses using Gene Ontology (GO) terms as well as using the molecular signatures database (MSigDB). Acute OSM-stimulated genes in Dnmt3a-mutant HSCs were enriched for focused signatures of inflammation, apoptosis, immune defense/stress responses, innate immunity, hematopoiesis, and myeloid cell development (Figure 4F). In contrast, OSM-stimulated genes in control HSCs were enriched for generic signatures of DNA metabolic processes, cell motility and morphogenesis, vesicle-mediated transport, and cell cycle-related processes (Myc/Max targets and E2F4 binding) (Figure 4E). Together, acute stimulation of Dnmt3a-mutant HSCs with recombinant OSM results in OSM binding, STAT3 phosphorylation, and transcriptional activation of an inflammatory gene network including the inflammatory cytokines IL-6, TNFα and IL-1β that are associated with Dnmt3a-mutant clonal hematopoiesis in mice and humans.

Young Dnmt3a-Mutant HSCs Upregulate Anti-Inflammatory Genes and Stabilize Socs3 in Response to Acute OSM Stimulation

We sought to resolve the disconnect we observed between acute OSM-driven STAT3 signaling and transcriptional activation in Dnmt3a-mutant (R878H/+) HSCs and the lack of phenotypic changes in Dnmt3a-mutant HSCs and HSPCs. Previous studies have found elevated expression of suppressors of inflammation such as Socs3, Nr4a1 and Atf3 in CH-mutant HSPCs[35], and OSM has been reported to stimulate expression of Socs3 in other cell types[36, 37]. Thus, we hypothesized that acute OSM stimulation of young Dnmt3a-mutant HSCs results in enhanced expression of suppressors of inflammation. Interrogating our OSM- vs. vehicle-treated Dnmt3a-mutant HSC RNA-seq data revealed that Socs3, Nr4a1 and Atf3 were increased in expression after acute OSM stimulation (Figure 5A).

Figure 5. Dnmt3a-mutant HSCs exhibit upregulation of Socs3, Nr4a1 and Atf3 in response to acute recombinant OSM stimulation.

Figure 5.

Open in a new tab

(A) Socs3, Nr4a1 and Atf3 expression in control (+/+) and Dnmt3a-mutant (R878H/+) HSCs stimulated with 0 or 500ng/ml OSM for 60min. Box plots summarize n = 6 replicates per condition. *p < 0.05. (B) Socs3 expression in control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs stimulated with 0 or 500ng/ml OSM for described amount of time. Bars represent mean ± SEM of n = 3–4 replicates. *p < 0.05 by multiple-ratio, paired sample t test. (C) Socs3 expression in control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs stimulated with 0 or 500ng/ml of OSM for 60min followed by actinomycin D for 0, 20, 60 and 80min. Bars represent mean ± SEM of n = 4 replicates.

To evaluate the dynamics of transcript induction, we focused on Socs3. Control and R878H/+ HSPCs were prospectively isolated from young adult mice and stimulated with 0 or 500ng/ml recombinant murine OSM for up to 80min. Cells were flash-frozen for RNA extraction, cDNA synthesis and quantitative real-time PCR for Socs3. OSM stimulation of control HSPCs resulted in a small, but significant, increase in Socs3 after 60min (Figure 5B). In contrast, OSM stimulation of Dnmt3a-mutant HSPCs resulted in robust increase in Socs3 at 20, 40 and 60min. This result demonstrates that Dnmt3a-mutant HSPCs rapidly respond to OSM stimulation by upregulating Socs3, at both greater levels and a faster rate compared to control HSPCs.

To evaluate stability of the Socs3 mRNA transcript, we prospectively isolated control and Dnmt3a-mutant HSPCs from young adult mice and stimulated with 0 or 500ng/ml recombinant murine OSM for 60min, a timepoint we have consistently shown to result in STAT3 phosphorylation and transcriptional responses in Dnmt3a-mutant HSPCs. OSM stimulation was followed by incubating cells for 0, 20, 60 and 80 minutes with Actinomycin D, to pause transcription and allow the study of transcript stability over time[38]. Cells were flash-frozen for RNA extraction, cDNA synthesis and real-time PCR for Socs3. Consistent with the above results, Socs3 was robustly increased in Dnmt3a-mutant HSPCs by 60min of OSM stimulation (Figure 5C). Furthermore, OSM-stimulated Dnmt3a-mutant HSPCs maintained increased levels of Socs3 for up to 80 minutes of Actinomycin D treatment. These results suggest that OSM-stimulated Dnmt3a-mutant HSPCs have a robust increase in Socs3 transcript expression, and that this transcript is stably maintained for up to 140 minutes following exposure to OSM. We posit that Socs3 activation may suppress STAT3 signaling, silencing transcriptional responses to OSM before functional outcomes are realized.

Dnmt3a-mutant HSCs Do Not Upregulate Anti-Inflammatory Genes in the Context of an Aged Environment

At the beginning of our study, we discovered a transcriptional program of inflammation response in Dnmt3a-mutant compared to control HSCs in middle-aged, but not young, transplant recipient mice (Figure 1B). Thus, we hypothesized that middle-aged mice have elevated ‘chronic’ levels of OSM and that Dnmt3a-mutant HSCs in a middle-aged microenvironment lose the capacity to upregulate suppressors of inflammation such as Socs3, Nr4a1, and Atf3. Bone marrow fluid was collected from young adult (3mo), middle-aged (14mo) and old (22mo) wild-type C57BL/6 mice and quantified OSM abundance using ELISA. A significant and progressive increase was observed in the quantity of OSM in the bone marrow fluid from young to middle-aged to old mice (Figure 6A). We examined our published RNA-seq data of control and Dnmt3a-mutant HSCs re-isolated from transplanted middle-aged wild-type recipient mice, focusing on the key inflammatory molecules identified in our acute OSM-stimulated Dnmt3a-mutant HSCs (Figure 4D) as well as Socs3, Nr4a1 and Atf3. Dnmt3a-mutant HSCs compared to control HSCs in transplanted middle-aged recipient mice had robust upregulation of Il1r2, Il1b, Ccr1, Tnf, and Csf3r (Figure 6B). Unlike acute OSM-stimulated Dnmt3a-mutant HSCs, we did not observe increased expression of Socs3, Nr4a1 or Atf3.

Figure 6. Dnmt3a-mutant HSCs do not differentially express Socs3, Nr4a1 and Atf3 in a middle-aged BM microenvironment.

Figure 6.

Open in a new tab

(A) OSM concentration in bone marrow fluid in young (3mo), middle-aged (14mo) and old (22mo) wild-type C57BL/6 mice. Dots show individual mice, bars represent mean ± SEM of n = 6–7. *p < 0.05; **p < 0.01 by Brown-Forsythe and Welch’s ANOVA with multiple comparisons. (B) Expression of inflammatory genes Il1r2, Il1b, Ccr1, Tnf, and Csf3r, and the anti-inflammatory genes Socs3, Nr4a1, and Atf3 in control (+/+) and Dnmt3a-mutant (R878H/+) HSCs after 4mos post-transplant in middle-aged recipient mice. Box plots summarize n = 3–4 replicates per condition. *p < 0.05; **p < 0.01 by multiple-ratio, paired sample t test. (C) Working model of OSM signaling in Dnmt3a-mutant HSPCs in the context of the young and middle-aged BM environments. Created with BioRender.com licensed by The Jackson Laboratory.

DISCUSSION

We report a role for Oncostatin M (OSM) in transcriptional induction of a cytokine network in Dnmt3a-mutant CH. Our initial discovery was based on transcriptional signatures indicating active OSM signaling in Dnmt3a-mutant HSCs specifically in the context of a middle-aged bone marrow microenvironment. In functional experiments, OSM stimulation of young Dnmt3a-mutant HSCs did not impact hematopoietic cell function or output in vitro or in vivo, however, it did result in STAT3 phosphorylation and a transcriptional inflammatory response including upregulation of Il6, Il1b and Tnf. Focused studies of transcript production and stability revealed a putative negative feedback mechanism in young Dnmt3a-mutant HSCs where OSM signaling results in increased transcription and transcript stability of anti-inflammatory genes including Socs3, Nr4a1 and Atf3. In the context of a middle-aged bone marrow microenvironment, Dnmt3a-mutant HSCs upregulate inflammation-related transcripts which is not accompanied by upregulation of anti-inflammatory genes. Of note, the levels of OSM in our ex vivo versus in vivo studies are distinct, thus we are unable to draw direct conclusions about OSM-responsive genes in the middle-aged microenvironment context. We speculate that chronic inflammation with aging, be it through OSM or mediated by other cytokines, may exhaust the regulatory mechanisms present in young Dnmt3a-mutant HSCs that resolve inflammatory states (Figure 6C).

OSM is an IL-6 family cytokine known to be involved in the immunopathogenesis of colon cancer, breast cancer, pancreatic cancer, myeloma and hepatoblastoma[34]. Whereas IL-6 represents one of the most studied cytokines to date, the physiological activities of OSM are less well known. OSM is predominantly produced by T lymphocytes, macrophages, and neutrophils[19], and in mice, signals through the heterodimeric receptor gp130/OSMR[39]. OSM is a strong inducer of JAK/STAT signaling leading to activation of STAT3 and STAT5[40, 41]. OSM is an important regulator of the bone marrow microenvironment in both steady state and in regeneration after injury[42, 43] with endothelial and mesenchymal cells being major cell types expressing OSMR[34], and plays a role in HSC mobilization via its effects on non-hematopoietic cells in the bone marrow microenvironment[34]. These data and models support a role for OSM as a cytokine produced by mature hematopoietic cells that impacts functionality of non-hematopoietic cells in the bone marrow microenvironment. Previous studies performed in young adult mice have shown that Osmr is not detected in HSPCs or myeloid cells[34] and thus it has been suggested that HSCs and their progeny do not directly respond to OSM. However, Osmr is one of the most upregulated transcripts in old HSCs compared to young HSCs across six independent datasets[44] suggesting that in certain contexts, such as aging, HSCs and their progeny gain the capacity to respond to OSM. Our data show that HSCs, in the context of a CH-relevant mutation in Dnmt3a, do have the capacity to phosphorylate STAT3 and undergo transcriptional alterations in response to recombinant OSM. The extent to which this transcriptional response is physiologically relevant with respect to cellular function is an important question that should be addressed in future studies focused on the aged bone marrow microenvironment.

Previous literature has demonstrated that OSM leads to a stronger and prolonged induction of SOCS3 compared to IL-6 stimulation in HepG2 cells and mouse embryonic fibroblasts (MEFs)[37]. Our observations suggest that stimulation with recombinant OSM at high concentrations results in transcriptional upregulation of the cytokine family member Il6 in addition to Socs3. Given that IL-6 is also a potent inducer of Socs3 and has been identified as a key inflammatory signal in the fatty bone marrow that drives DNMT3A-mutant CH in human and mouse models, it remains a possibility that both OSM and IL-6 contribute to induction and stability of the Socs3 transcript. Recently, Potts et al. reported that splicing factor (Sf3b1) mutant HSPCs had similar STAT3 phosphorylation following stimulation with OSM and IL-6 together compared to OSM alone[45], although they did not directly evaluate Socs3. In a thought-provoking study, Socs3 was found to serve an essential role in maintaining specificity of STAT3 phosphorylation and gene transcription in response to IL-6 versus G-CSF, supporting that STAT3 signaling is uniquely regulated in a cytokine-dependent manner[46]. Distinctions between Socs3 induction and stability driven by OSM versus other STAT3 signaling inducers will be interesting to explore in future studies.

The consequences of OSM signaling have been found to be context dependent, resulting in pro-inflammatory as well as anti-inflammatory/anti-proliferative outcomes[40]. This is consistent with our data in young Dnmt3a-mutant HSCs where both pro-inflammatory cytokines as well as anti-inflammatory molecules are expressed in response to OSM. This anti-inflammatory negative feedback loop may be a conserved mechanism facilitating the selective advantage of mutant HSCs in CH. Recent work using a zebrafish model of human ASXL1-mutant CH found a protective response to pro-inflammatory cytokines in HSPCs via upregulation of socs3a, atf3 and nr4a1[35]. Without the capacity to upregulate nr4a1 and nr4a3, the Asxl1-mutant HSPCs lost their self-renewal capacity and selective growth advantage. In addition to induction of these anti-inflammatory transcripts that work in part through silencing STAT3 activation, complementary mechanisms may allow mutant HSCs to survive in a chronic inflammatory environment associated with aging. For example, in Tet2-mutant CH, HSPCs with hyperactivated SHP2-STAT3 signaling downregulate the apoptotic protein Bim via the anti-apoptotic long non-coding RNA Morrbid[37]. Together, complexities in the regulation of and response to inflammation in various forms of CH prompts careful consideration of effective targeting strategies to ameliorate CH-associated disease states in the context of aging.

MATERIALS AND METHODS

Animals

C57BL/6J (JAX:000664) and B6.SJL-PtprcaPepcb/BoyJ[47] (JAX:002014, referred to as CD45.1+) mice were obtained from, and aged within, The Jackson Laboratory. Dnmt3afl-R878H/+ mice (JAX:032289) were crossed to B6.Cg-Tg(Mx1-cre)1Cgn/J mice (JAX:003556, referred to as Mx-Cre). In all experiments, control (+/+) mice carried a single copy of Mx-Cre allele. The Jackson Laboratory’s Institutional Animal Care and Use Committee approved all experiments. To induce Mx-Cre, mice were intraperitoneally injected once every other day for five total injections with 15 mg/kg high molecular weight polyinosinic-polycytidylic acid (polyI:C) (InvivoGen). In all experiments, mice were used >4 weeks following polyI:C administration.

Peripheral Blood Analysis

Blood was collected from mice via the retro-orbital sinus and red blood cells were lysed prior to staining with the following fluorochrome-conjugated antibodies: BV650 CD45.1 (BioLegend clone A20), AlexaFluor700 CD45.2 (BioLegend clone 104), BUV496 B220 (BD Biosciences clone RA3–6B2), PerCP-Cy5.5 CD3e (BioLegend clone 145–2C11), APC-Cy7 CD11b (BioLegend clone M1/70), APC Ly6g (BioLegend clone 1A8), BV605 Ly6c (BioLegend clone HK1.4), BV421 Ter-119 (BioLegend clone TER-119), PE-Cy7 F4/80 (Invitrogen BM8). Data was collected using a LSRII (BD Biosciences) and analyzed using FlowJo V10 (BD Biosciences).

Isolation and Phenotyping of Hematopoietic Stem and Progenitor Cells

BM cells were isolated from pooled and crushed femurs, tibiae, iliac crests, sternums, forepaws, and spinal columns of individual mice. BM mononuclear cells (MNCs) were isolated by Ficoll-Paque (GE Healthcare Life Sciences) density centrifugation or 1X RBC Lysis Buffer (eBioscience) and stained with a combination of fluorochrome-conjugated antibodies: c-Kit (BD Biosciences, BioLegend clone 2B8), Sca-1 (BioLegend clone D7), CD150 (BioLegend clone TC15–12F12.2), CD48 (BioLegend clone HM48–1), CD34 (BD Biosciences clone RAM34), FLT3 (BioLegend clone A2F10), CD11b (BioLegend clone M1/70), mature lineage (Lin) marker mix (B220 (BD Biosciences, BioLegend clone RA3–6B2), CD4 (BioLegend clone RM4–5), CD5 (BioLegend clone 53–7.3), CD8a (Biosciences, BioLegend clone 53–6.7), Ter-119 (BioLegend clone TER-119), and Gr-1 (BioLegend, Invitrogen clone RB6–8C5)), and the viability stain propidium iodide (PI) or 4′,6-diamidino-2-phenylindole (DAPI). For transplants CD45.1 (BioLegend clone A20), and CD45.2 (BioLegend clone 104) antibodies were used to distinguish genotypes of donor and recipient mice. The following cell surface markers were used to isolate or phenotype HSCs: Lin- Sca-1+ c-Kit+ Flt3- CD150+ CD48−, HSPCs: Lin- Sca-1+ c-Kit+, MPPG/M: Lin- Sca-1+ c-Kit+ Flt3- CD150− CD48+, CMP: Lin-Sca-1- c-Kit+ CD34+ FcγR−, GMP: Lin- Sca-1− c-Kit+ CD34+ FcγR+. Data was collected using a BD FACSymphony A5 or cells were prospectively isolated using a FACSymphony S6 (BD Biosciences). All flow cytometry data was analyzed using FlowJo V10.

Cell Cycle Analysis

5,000 HSPCs were sorted directly into TC-treated 96-well plates (Falcon) containing StemSpan™ SFEM II (Stemcell Technologies) with Pen-Strep (Fisher Scientific) and SCF (100 ng/ml, BioLegend), TPO (50 ng/μl, Peprotech), with or without OSM (500 ng/ml, BioLegend) for 24hrs at 37°C and 5% CO2. Cells were stained with Ghost UV450 viability dye (Cytek Biosciences) and fixed with the FIX & PERM™ Cell Permeabilization Kit (Invitrogen) following the manufacturer’s protocol. Following fixation cells were stained with FITC anti-mouse/human Ki-67 (BioLegend) and DAPI. Data was collected on a BD FACSymphony A5.

Apoptosis Analysis

5,000 HSPCs were sorted directly into 96-well plates containing SFEMII with Pen-Strep and SCF (100 ng/ml), TPO (50 ng/μl), with or without OSM (500 ng/ml) for 24hrs at 37°C and 5% CO2. Cells were stained with Annexin V and Propidium iodide using the Annexin A5 Apoptosis Detection Kit (BioLegend). Data was collected on a FACSymphony A5 (BD Biosciences).

Colony-Forming Unit (CFU) Assay

HSCs or HSPCs were isolated and plated in MethoCult GF M3434 (StemCell Technologies), with or without OSM (500 ng/ml) and cultured at 37°C and 5% CO2. Colonies were scored between 6- and 14-days post-plating using a Nikon Eclipse TS100 inverted microscope. For serial replating, cells were harvested by washing the plates and 10,000 cells (from HSCs) or 15,000 cells (from HSPCs) were replated into fresh MethoCult GF M3434 with or without OSM (500 ng/ml).

In Vitro Culture with Cytokine-Rich and -Poor Media

We followed a published protocol to generate cytokine-rich and cytokine-poor medias[32]. Briefly, 500 cells were sorted directly into 96-well plates in 200μl of IMDM containing 5% FBS, 50 U/ml penicillin, 50μg/ml streptomycin, 2mM L-glutamine, 0.1mM non-essential amino acids, 1mM sodium pyruvate and 50μM 2-mercaptoethanol. For cytokine-rich media, this was supplemented with SCF (25 ng/ml), TPO (25 ng/ml), Flt3L (25 ng/ml), IL-11 (25 ng/ml), IL-3 (10 ng/ml), GM-CSF (10 ng/ml) and EPO (4 U/ml) (all from PeproTech). For cytokine-poor media, this was supplemented with SCF (25 ng/ml) and G-CSF (25 ng/ml, PeproTech). PBS or OSM was added at 500ng/ml to both medias. After 48hr culture at 37°C and 5% CO2, cells were harvested, DAPI was used to determine live cells and data collected on a FACSymphony A5.

PVA Culture and In Vivo Transplantation

For the non-competitive PVA culture and transplant experiment, 50 CD45.2+ HSCs were sorted into a 96-well plate with Ham’s F12 media containing 1X pen/strep/glutamine (Gibco), 10 mmol/l HEPES (Gibco), 1X insulin/transferrin/selenium/ethanolamine (Gibco), 100 ng/ml rmTPO (BioLegend), 10 ng/ml rmSCF (STEMCELL Technologies) and 1 mg/ml polyvinyl alcohol (Sigma), with or without 500 ng/ml rmOSM, and cultured for 7 days at 37°C and 5% CO2, as previously described[33]. 500 ng/ml OSM or vehicle was added to the cultures on days 4 and 6. On day 7, the wells were harvested, mixed with 106 CD45.1+ BM MNCs, and transplanted into young, lethally irradiated (12Gy gamma irradiation, split dose) CD45.1+ recipients. PB and BM data were collected at 6 months after transplant using a BD LSR II instrument.

For competitive PVA culture and transplant, 25 CD45.2+ HSCs from control or R878H/+ donors (CD45.2+) and 25 CD45.1+CD45.2+ HSCs from WT F1 mice were sorted into a 96-well plate with Ham’s F12 media containing 1X pen/strep/glutamine (Gibco), 10 mmol/l HEPES (Gibco), 1X insulin/transferrin/selenium/ethanolamine (Gibco), 100 ng/ml rmTPO (BioLegend), 10ng/ml rmSCF (STEMCELL Technologies) and 1mg/ml polyvinyl alcohol (Sigma), with or without 500 ng/ml rmOSM, and cultured for 7 days at 37°C and 5% CO2, as previously described[33]. 500 ng/ml rmOSM or vehicle was added to the cultures on days 4 and 6. On day 7, the wells were harvested, mixed with 106 CD45.1+ BM MNCs, and transplanted into young, lethally irradiated (12 Gy gamma irradiation, split dose) CD45.1+ recipients. PB and BM were collected at 6 months after transplant using a BD LSR II instrument.

Fluorescent OSM Binding

100 μg rmOSM (BioLegend) was concentrated by centrifugation (Amicon Ultra-0.5 Centrifugal Filter Unit) and fluorescently labeled using the AlexaFluor™ 488 Antibody Labeling Kit following the manufacturers protocol. 107 WBM cells were treated with FC block then stained for 30min with PBS or fluorescently labelled rmOSM at 37°C for 30min. After 30min, cells were stained with an antibody cocktail for identification of HSCs and HSPCs as detailed above. Cells were washed and ran on a BD FACSymphony A5 SE. As positive control, a single cell suspension of liver cells was prepared using the Miltenyi Liver Kit (MiltenyiBiotec).

Phospho-Flow Cytometry

1000 LSK cells were sorted into StemSpan SFEM II media (STEMCELL Technologies). Cells were pelleted and resuspended in StemSpan SFEM II with or without 500 ng/ml rmOSM and incubated at 37°C for 20, 60 or 80min. Cells were then fixed using 16% PFA for 10min at room temperature followed by ice-cold acetone for 10min. Cells were then pelleted, washed and stained with AlexaFluor 488 Mouse Anti-Stat3 (Tyr705) (D3A7) XP Rabbit mAb (Cell Signaling Technologies) or PE-Cy7 Mouse Anti-Stat5 (pY694) (BD) for 30min at room temperature before data collection using a BD FACSymphony A5 SE.

RNA Sequencing

2,000 HSCs were sorted into StemSpan SFEM II media with TPO (50 ng/ml) and SCF (100 ng/ml). PBS or OSM (500 ng/ml) was added to each well and incubated at 37°C for 60min. Total RNA was isolated from flash-frozen pellets using the RNeasy Micro kit (Qiagen) including the optional DNase digest step. RNA concentration and quality were assessed using the RNA 6000 Pico Assay (Agilent Technologies). Libraries were constructed using the SMARTer Stranded Total RNA-Seq Kit v2-Pico (Takara), according to the manufacturer’s protocol. Library concentration and quality were assessed using the D5000 ScreenTape (Agilent Technologies) and Qubit dsDNA HS Assay (ThermoFisher). Libraries were sequenced (2021) 75 bp paired-end on an Illumina NextSeq 500 using the High Output Reagent Kit v2.5 (2022)150 bp paired-end on an Illumina NovaSeq 6000 using the S4 Reagent Kit v1.5 both at a sequencing depth of >35 million reads per sample. Trimmed alignment files were processed using RSEM (v1.3.3). Alignment was completed using Bowtie 2 (v2.4.1). Expected read counts per gene produced by RSEM were rounded to integer values, filtered to include only genes that had at least two samples within a sample group having a counts per million reads >1, and passed to R (v4.1.3) and edgeR (v3.36.0) for differential expression analysis. A negative binomial generalized log-linear model was fit to the read counts for each gene. The dispersion trend was estimated by Cox-Reid approximate profile likelihood followed by empirical Bayes estimate of the negative binomial dispersion parameter for each tag, with expression levels specified by a log-linear model. Likelihood ratio tests for coefficient contrasts in the linear model were evaluated producing a p-value per contrast. The Benjamini and Hochberg’s algorithm (P value adjustment) was used to control the false discovery rate (FDR). Differentially expressed genes were investigated for overlap with published datasets using Gene Set Enrichment Analysis, and upstream regulators were predicted using Ingenuity Pathway Analysis software. Features with fold change (FC) > 1.5 or < −1.5, and P < 0.05, were declared significantly differentially expressed.

Socs3 mRNA Expression Assays

For Socs3 expression assays, HSPCs were sorted into 750 μl of StemSpan SFEM II with vehicle or 500 ng/ml OSM and incubated at 37°C for 20, 40, 60 or 80min. Following each incubation, actinomycin D (Sigma) was added and cells were incubated for an additional 20min at 37°C. Samples were pelleted and flash frozen. For Socs3 stability assays, HSPCs were sorted into 750 μl of StemSpan SFEM II with vehicle or 500 ng/ml OSM and incubated at 37°C for 60min. Actinomycin D was added for 20, 40, 60 or 80min at 37°C. Samples were pelleted and flash frozen. From all samples, RNA was isolated using the RNeasy Microkit (Qiagen) and cDNA was made using the qPCR Bio cDNA synthesis kit (PCR Biosystems). Quantitative PCR was performed using Power SYBR on the QuantStudio 7 Real-Time PCR System (ThermoFisher Scientific). mRNA expression levels were calculated relative to the housekeeping gene, B2m.

ELISA

Bone marrow fluid was collected from 3mo, 14mo, and 22mo C57BL/6J mice by needle flushing of femurs with 200 μl PBS. OSM concentration was determined using the Quantikine ELISA for mouse Oncostatin M (R&D Systems) using a Spectramax i3 (Molecular Devices) plate reader.

Statistical Analysis

All statistical tests including evaluation of the normal distribution of data and examination of variance between groups were performed using Prism 9 software (GraphPad). Figure 6C was created using BioRender.com licensed to The Jackson Laboratory.

Extended Data

Extended Data Figure 1. Binding of OSM to control and Dnmt3a-mutant HSPCs and induction of pSTAT5.

Extended Data Figure 1.

Open in a new tab

(A) Mean fluorescence intensity (MFI) of fluorescently labeled OSM (OSM-AF488) in negative control (no OSM), positive control (liver), control (+/+) and Dnmt3a-mutant (R878H/+) HSCs. Dots show individual mice, bars represent mean ± SEM of n = 3–6. ****p < 0.0001 by one-way ANOVA with Dunnett’s T3 multiple comparisons test. (B) MFI of pSTAT5 (Y694) in control (+/+) and Dnmt3a-mutant (R878H/+) HSPCs treated with 0 or 500ng/ml OSM for 20, 60 and 80min. Dots show individual mice and bars represent mean ± SEM of n = 6–10. **p < 0.01; ***p < 0.001 by mixed-effects analysis with Tukey’s multiple comparisons test.

Highlights.

  • Oncostatin M (OSM) signaling is elevated in Dnmt3a-mutant HSCs with aging

  • OSM does not functionally impact young Dnmt3a-mutant HSCs

  • OSM activates both pro- and anti-inflammatory genes in young Dnmt3a-mutant HSCs

  • In aging, Dnmt3a-mutant HSCs elevate pro- but not anti-inflammatory genes

ACKNOWLEDGEMENTS

This work was supported by National Institutes of Health grants R01DK118072, R01AG069010, U01AG077925, and a grant from the Edward P. Evans Foundation to J.J.T. This work was supported in part by the NIH/NCI Cancer Center Support Grant P30CA034196. J.J.T. was supported by a Leukemia & Lymphoma Society Scholar Award and The Dattels Family Endowed Chair. L.S.S. was supported by F31DK127573 and The Tufts University Scheer-Tomasso Fund philanthropic gift. We thank all members of the Trowbridge Lab for experimental support and manuscript editing. We thank the Scientific Services at The Jackson Laboratory including flow cytometry and genome technologies. We thank Drs. Carol Bult, Ryan Tewhey, Cliff Rosen, and Phil Hinds for their critical input into this work.

Footnotes

Declaration of Interests: J.J.T. has received research support from H3 Biomedicine, Inc., and patent royalties from Fate Therapeutics. All other authors declare no competing interests.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Data Availability

Raw RNA-seq data is available at the Gene Expression Omnibus (GEO) under accession number GSE236693.

REFERENCES

  • [1].Jaiswal S, Fontanillas P, Flannick J, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med. 2014;371:2488–2498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2].Genovese G, Kahler AK, Handsaker RE, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med. 2014;371:2477–2487. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [3].Colom Diaz PA, Mistry JJ, Trowbridge JJ. Hematopoietic Stem Cell Aging and Leukemia Transformation. Blood. 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [4].Bhattacharya R, Zekavat SM, Haessler J, et al. Clonal Hematopoiesis Is Associated With Higher Risk of Stroke. Stroke. 2022;53:788–797. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Mooney L, Goodyear CS, Chandra T, et al. Clonal haematopoiesis of indeterminate potential: intersections between inflammation, vascular disease and heart failure. Clin Sci (Lond). 2021;135:991–1007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Papaemmanuil E, Gerstung M, Malcovati L, et al. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood. 2013;122:3616–3627; quiz 3699. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Xie M, Lu C, Wang J, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med. 2014;20:1472–1478. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Busque L, Patel JP, Figueroa ME, et al. Recurrent somatic TET2 mutations in normal elderly individuals with clonal hematopoiesis. Nat Genet. 2012;44:1179–1181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Nagase R, Inoue D, Pastore A, et al. Expression of mutant Asxl1 perturbs hematopoiesis and promotes susceptibility to leukemic transformation. J Exp Med. 2018;215:1729–1747. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [10].Jaiswal S, Libby P. Clonal haematopoiesis: connecting ageing and inflammation in cardiovascular disease. Nat Rev Cardiol. 2020;17:137–144. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11].Nachun D, Lu AT, Bick AG, et al. Clonal hematopoiesis associated with epigenetic aging and clinical outcomes. Aging Cell. 2021;20:e13366. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].SanMiguel JM, Young K, Trowbridge JJ. Hand in hand: intrinsic and extrinsic drivers of aging and clonal hematopoiesis. Exp Hematol. 2020;91:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13].Trowbridge JJ, Starczynowski DT. Innate immune pathways and inflammation in hematopoietic aging, clonal hematopoiesis, and MDS. J Exp Med. 2021;218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Florez MA, Tran BT, Wathan TK, DeGregori J, Pietras EM, King KY. Clonal hematopoiesis: Mutation-specific adaptation to environmental change. Cell Stem Cell. 2022;29:882–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Zhang CRC, Nix D, Gregory M, et al. Inflammatory cytokines promote clonal hematopoiesis with specific mutations in ulcerative colitis patients. Exp Hematol. 2019;80:36–41 e33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [16].Hormaechea-Agulla D, Matatall KA, Le DT, et al. Chronic infection drives Dnmt3a-loss-of-function clonal hematopoiesis via IFNgamma signaling. Cell Stem Cell. 2021;28:1428–1442 e1426. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [17].Zioni N, Bercovich AA, Chapal-Ilani N, et al. Inflammatory signals from fatty bone marrow support DNMT3A driven clonal hematopoiesis. Nat Commun. 2023;14:2070. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].SanMiguel JM, Eudy E, Loberg MA, et al. Distinct Tumor Necrosis Factor Alpha Receptors Dictate Stem Cell Fitness versus Lineage Output in Dnmt3a-Mutant Clonal Hematopoiesis. Cancer Discov. 2022;12:2763–2773. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [19].Cai Z, Kotzin JJ, Ramdas B, et al. Inhibition of Inflammatory Signaling in Tet2 Mutant Preleukemic Cells Mitigates Stress-Induced Abnormalities and Clonal Hematopoiesis. Cell Stem Cell. 2018;23:833–849 e835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Cook EK, Izukawa T, Young S, et al. Comorbid and inflammatory characteristics of genetic subtypes of clonal hematopoiesis. Blood Adv. 2019;3:2482–2486. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Caiado F, Kovtonyuk LV, Gonullu NG, Fullin J, Boettcher S, Manz MG. Aging drives Tet2+/− clonal hematopoiesis via IL-1 signaling. Blood. 2023;141:886–903. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [22].Fuster JJ, Zuriaga MA, Zorita V, et al. TET2-Loss-of-Function-Driven Clonal Hematopoiesis Exacerbates Experimental Insulin Resistance in Aging and Obesity. Cell Rep. 2020;33:108326. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Bick AG, Weinstock JS, Nandakumar SK, et al. Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020;586:763–768. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Abegunde SO, Buckstein R, Wells RA, Rauh MJ. An inflammatory environment containing TNFalpha favors Tet2-mutant clonal hematopoiesis. Exp Hematol. 2018;59:60–65. [DOI] [PubMed] [Google Scholar]
  • [25].Fujino T, Goyama S, Sugiura Y, et al. Mutant ASXL1 induces age-related expansion of phenotypic hematopoietic stem cells through activation of Akt/mTOR pathway. Nat Commun. 2021;12:1826. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Loberg MA, Bell RK, Goodwin LO, et al. Sequentially inducible mouse models reveal that Npm1 mutation causes malignant transformation of Dnmt3a-mutant clonal hematopoiesis. Leukemia. 2019;33:1635–1649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [27].Tawara K, Scott H, Emathinger J, et al. HIGH expression of OSM and IL-6 are associated with decreased breast cancer survival: synergistic induction of IL-6 secretion by OSM and IL-1beta. Oncotarget. 2019;10:2068–2085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Chauhan D, Kharbanda SM, Ogata A, et al. Oncostatin M induces association of Grb2 with Janus kinase JAK2 in multiple myeloma cells. J Exp Med. 1995;182:1801–1806. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29].Chen M, Ren R, Lin W, Xiang L, Zhao Z, Shao B. Exploring the oncostatin M (OSM) feed-forward signaling of glioblastoma via STAT3 in pan-cancer analysis. Cancer Cell Int. 2021;21:565. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [30].Lee BY, Hogg EKJ, Below CR, et al. Heterocellular OSM-OSMR signalling reprograms fibroblasts to promote pancreatic cancer growth and metastasis. Nat Commun. 2021;12:7336. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Gu ZJ, Costes V, Lu ZY, et al. Interleukin-10 is a growth factor for human myeloma cells by induction of an oncostatin M autocrine loop. Blood. 1996;88:3972–3986. [PubMed] [Google Scholar]
  • [32].Yamashita M, Passegue E. TNF-alpha Coordinates Hematopoietic Stem Cell Survival and Myeloid Regeneration. Cell Stem Cell. 2019;25:357–372 e357. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [33].Wilkinson AC, Ishida R, Kikuchi M, et al. Long-term ex vivo haematopoietic-stem-cell expansion allows nonconditioned transplantation. Nature. 2019;571:117–121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34].Bisht K, McGirr C, Lee SY, et al. Oncostatin M regulates hematopoietic stem cell (HSC) niches in the bone marrow to restrict HSC mobilization. Leukemia. 2022;36:333–347. [DOI] [PubMed] [Google Scholar]
  • [35].Avagyan S, Henninger JE, Mannherz WP, et al. Resistance to inflammation underlies enhanced fitness in clonal hematopoiesis. Science. 2021;374:768–772. [DOI] [PubMed] [Google Scholar]
  • [36].Ehlting C, Bohmer O, Hahnel MJ, et al. Oncostatin M regulates SOCS3 mRNA stability via the MEK-ERK1/2-pathway independent of p38(MAPK)/MK2. Cell Signal. 2015;27:555–567. [DOI] [PubMed] [Google Scholar]
  • [37].Stross C, Radtke S, Clahsen T, et al. Oncostatin M receptor-mediated signal transduction is negatively regulated by SOCS3 through a receptor tyrosine-independent mechanism. J Biol Chem. 2006;281:8458–8468. [DOI] [PubMed] [Google Scholar]
  • [38].Ratnadiwakara M, Anko ML. mRNA Stability Assay Using transcription inhibition by Actinomycin D in Mouse Pluripotent Stem Cells. Bio Protoc. 2018;8:e3072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [39].Adrian-Segarra JM, Schindler N, Gajawada P, Lorchner H, Braun T, Poling J. The AB loop and D-helix in binding site III of human Oncostatin M (OSM) are required for OSM receptor activation. J Biol Chem. 2018;293:7017–7029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Masjedi A, Hajizadeh F, Beigi Dargani F, et al. Oncostatin M: A mysterious cytokine in cancers. Int Immunopharmacol. 2021;90:107158. [DOI] [PubMed] [Google Scholar]
  • [41].Hintzen C, Evers C, Lippok BE, et al. Box 2 region of the oncostatin M receptor determines specificity for recruitment of Janus kinases and STAT5 activation. J Biol Chem. 2008;283:19465–19477. [DOI] [PubMed] [Google Scholar]
  • [42].Mukouyama Y, Hara T, Xu M, et al. In vitro expansion of murine multipotential hematopoietic progenitors from the embryonic aorta-gonad-mesonephros region. Immunity. 1998;8:105–114. [DOI] [PubMed] [Google Scholar]
  • [43].Mahony CB, Pasche C, Bertrand JY. Oncostatin M and Kit-Ligand Control Hematopoietic Stem Cell Fate during Zebrafish Embryogenesis. Stem Cell Reports. 2018;10:1920–1934. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [44].Flohr Svendsen A, Yang D, Kim K, et al. A comprehensive transcriptome signature of murine hematopoietic stem cell aging. Blood. 2021;138:439–451. [DOI] [PubMed] [Google Scholar]
  • [45].Potts KS, Cameron RC, Metidji A, et al. Splicing factor deficits render hematopoietic stem and progenitor cells sensitive to STAT3 inhibition. Cell Rep. 2022;41:111825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Croker BA, Mielke LA, Wormald S, et al. Socs3 maintains the specificity of biological responses to cytokine signals during granulocyte and macrophage differentiation. Exp Hematol. 2008;36:786–798. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [47].Shen FW, Saga Y, Litman G, et al. Cloning of Ly-5 cDNA. Proc Natl Acad Sci U S A. 1985;82:7360–7363. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Raw RNA-seq data is available at the Gene Expression Omnibus (GEO) under accession number GSE236693.

RESOURCES