Chronic interleukin-1 exposure triggers selection for Cebpa-knockout multipotent hematopoietic progenitors

Abstract

The early events that drive myeloid oncogenesis are not well understood. Most studies focus on the cell-intrinsic genetic changes and how they impact cell fate decisions. We consider how chronic exposure to the proinflammatory cytokine, interleukin-1β (IL-1β), impacts Cebpa-knockout hematopoietic stem and progenitor cells (HSPCs) in competitive settings. Surprisingly, we found that Cebpa loss did not confer a hematopoietic cell-intrinsic competitive advantage; rather chronic IL-1β exposure engendered potent selection for Cebpa loss. Chronic IL-1β augments myeloid lineage output by activating differentiation and repressing stem cell gene expression programs in a Cebpa-dependent manner. As a result, Cebpa-knockout HSPCs are resistant to the prodifferentiative effects of chronic IL-1β, and competitively expand. We further show that ectopic CEBPA expression reduces the fitness of established human acute myeloid leukemias, coinciding with increased differentiation. These findings have important implications for the earliest events that drive hematologic disorders, suggesting that chronic inflammation could be an important driver of leukemogenesis and a potential target for intervention.

Graphical abstract

Figure 1.

HSPC-specific Cebpa knockout causes expansion of MPPs. (A–F) Hematopoietic characterization of Cebpa^+/+ and Cebpa^Δ/Δ mice 7 d after deletion. (A) Schematic to achieve traceable, tamoxifen-inducible, HSPC-specific knockout of Cebpa. (B) BM cellularity from one femur and one tibia per mouse. (C) HSPC frequency. (D) Committed progenitor frequency. (E) Mature cell frequency. (F) Complete blood count. CLP, common lymphoid progenitor; LT, long-term; ST, short-term. Data are from three separate experiments with n = 3 per group (n = 9 per genotype), presented as mean ± SD, and analyzed by unpaired Mann–Whitney U test. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

Figure S1.

Characterization of primary Cebpa-knockout mice. (A) PCR products to detect WT (235-bp), floxed (269-bp), or excised allele (361-bp) run on a 2% agarose gel with 1 kb Plus DNA ladder (Thermo Fisher Scientific). (B) Kinetics of tamoxifen-induced YFP expression within Lin⁻Sca1⁺cKit⁺ (LSK), Lin⁻, and Lin⁺ BM fractions. Tamoxifen did not influence HSPC behavior in cell culture or IL-1 levels in BM fluid (data not shown). (C and D) Representative flow cytometry plots to characterize HSPC populations (C) and myeloid progenitors (D) from Cebpa^+/+ and Cebpa^Δ/Δ mice. (E) Cytokine analysis of BM fluid from vehicle or chronic IL-1β–treated mice (n = 3 mice per group; representative of two experiments). Data are presented as mean ± SD and analyzed by unpaired t test (in E). *, P < 0.05; ***, P < 0.001.

Figure 2.

HSPC-specific Cebpa knockout enhances MPP activity. (A) Experimental design for LSK CFU assay. (B–F) LSK CFU assay data. (B) CFU counts per plate for initial plating. (C) Total cell counts per plate for initial plating. (D) Frequencies of CFU types for initial plating. Mk, megakaryocyte. (E) CFU counts per plate on replating 10⁴ cells. n.d., not done because too few cells were recovered. (F) Calculation and data for cumulative CFU potential for second plating. Data are representative of three separate experiments with n = 3 per group, presented as mean ± SD, and analyzed by two-way ANOVA with Tukey’s multiple comparisons test. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. Could not perform statistics for fourth replating due to missing data points.

Figure 3.

Cebpa knockout confers a fitness advantage in the context of chronic IL-1β in competitive transplants. (A) Experimental design for competitive BM transplants. (B) Representative flow cytometry plots to identify donor (CD45.2⁺YFP⁺), competitor (CD45.2⁺YFP⁻), and recipient (CD45.1⁺) populations. FSC, forward scatter. (C) Initial engraftment in the periphery was assessed by frequency of donor-derived (CD45.2⁺YFP⁺) leukocytes 3 wk after transplant. (D–F) Following 20 d of treatment with vehicle or IL-1β, BM was analyzed as follows. (D) Donor chimerism presented as percentage CD45.2⁺YFP⁺ of each indicated HSPC population. LT, long-term; ST, short-term. (E) Absolute numbers of donor-derived (CD45.2⁺YFP⁺) HSPCs in the BM from one femur and one tibia per mouse. (F) Donor chimerism presented as percentage CD45.2⁺YFP⁺ of each indicated myeloid progenitor population. (G) Granulocyte derived from donors in peripheral blood and BM. Data are representative of three separate experiments with n = 10 per group, presented as mean ± SD, and analyzed by unpaired Mann–Whitney U test (C) and two-way ANOVA with Tukey’s multiple comparisons test (D–G). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

Figure S2.

Myeloid differentiation and chimerism in competitor and recipient HSPCs. (A and B) Frequency of MPP3, GMP, and granulocytes derived from competitors (A) and recipients (B) in competitive transplants. Graphs in A and B show the percentage of MPP3 within CD45.1⁺ or CD45.2⁺ YFP⁻ cell gates, respectively. PB, peripheral blood. (C) Recipient chimerism within indicated HSPC population. (D) Competitor chimerism within indicated HSPC population. LT, long-term; ST, short-term. Data are representative of three separate experiments with n = 10 per group, presented as mean ± SD, and analyzed by two-way ANOVA with Tukey’s multiple comparisons test. *, P < 0.05; **, P < 0.01; ****, P < 0.0001.

Figure 4.

Withdrawal of IL-1β eliminates the fitness advantage of Cebpa-knockout HSPCs. (A) Experimental design for competitive BM transplant. (B and C) After treatment with vehicle or IL-1β for 20 d and subsequent withdrawal of treatment for 20 d, BM was analyzed as follows. (B) Donor chimerism presented as percentage CD45.2⁺YFP⁺ of each indicated HSPC population. LT, long-term; ST, short-term. (C) Donor chimerism presented as percentage CD45.2⁺YFP⁺ of each indicated mature cell population. Data are from two separate experiments with n = 3–5 per group, presented as mean ± SD, and analyzed by two-way ANOVA with Tukey’s multiple comparisons test. No comparisons were significant.

Figure 5.

Cebpa mediates many of the chronic IL-1β gene expression changes. (A) Experimental design for RNA-seq (n = 3 of 3–4 mice pooled to obtain 2,000 donor [CD45.2⁺YFP⁺] or competitor [CD45.2⁺YFP⁻] MPP3s). (B) Heatmap of all genes significantly changed (adjusted P < 0.05) by chronic IL-1β, grouped based on pattern of expression: up-regulated (upreg.) with IL-1β, Cebpa-dependent; upreg. with IL-1β, Cebpa-independent; down-regulated (dnreg.) with IL-1β, Cebpa-dependent; dnreg. with IL-1β, Cebpa-independent (genes for heatmap are listed in Table S1). (C) Table showing select significant pathways (adjusted P < 0.05) from ORA.

Figure S3.

Cebpa knockout confers a fitness advantage in the context of chronic IL-1β in vivo. (A) Expression of Cebpa, Il1r1, and Spi1 plotted as log₂(counts per million) from RNA-seq (n = 3 of three to four mice pooled). (B) Heatmap of all genes significantly changed (adjusted P < 0.05) by Cebpa knockout (genes for heatmap are listed in Table S1). (C) Table summarizing the GSEA normalized enrichment score (NES) for select gene sets for “chronic IL-1β effect” and “Cebpa^Δ/Δ modification of chronic IL-1β effect” pairwise comparisons. (D and E) GSEA with “Chambers all myeloid” and “Chambers stem genes” gene sets. (D) Schematic and enrichment plots for pairwise comparison between C57BL/6 MPP3 competed against Cebpa^Δ/Δ or Cebpa^+/+ from chronic IL-1β–treated mice. (E) Schematic and enrichment plots for pairwise comparison between C57BL/6 MPP3 competed against Cebpa^Δ/Δ or Cebpa^+/+ from vehicle-treated mice. FDR, false discovery rate; NES, normalized enrichment score. Data are presented as mean ± SD and analyzed by two-way ANOVA with Tukey’s multiple comparisons test (in A). *, P < 0.05; ****, P < 0.0001.

Figure 6.

Cebpa knockout counteracts chronic IL-1β–driven transcriptional programs. (A–C) GSEA using “Chambers all myeloid,” “hallmark mTORC1 signaling,” and “Giladi cell cycle” gene sets. (A) Schematic and enrichment plots for pairwise comparison between Cebpa^+/+ MPP3 isolated from chronic IL-1β–treated versus vehicle-treated mice (“chronic IL-1β effect”). (B) Schematic and enrichment plots for pairwise comparison between Cebpa^Δ/Δ and Cebpa^+/+ MPP3s isolated from chronic IL-1β–treated mice (“Cebpa^Δ/Δ modification of chronic IL-1β effect”). (C) Heatmaps for leading edge genes from B (genes for heatmap are listed in Table S1). (D) Experimental design for cell cycle analysis (n = 5 per group). (E) Representative flow cytometry plots for Ki67/DAPI cell cycle analysis. (F) Graph of frequency of MPP3 in G0, G1, S/G2/M. FDR, false discovery rate; NES, normalized enrichment score. In D–F, cell cycle data are from one experiment with n = 5 mice per group, presented as mean ± SD, and analyzed by two-way ANOVA with Tukey’s multiple comparisons test. *, P < 0.05; **, P < 0.01.

Figure 7.

Chronic IL-1β triggers aberrant expansion potential of Cebpa-knockout MPP3. (A–C) GSEA using “Giladi stem genes” gene set. (A) Schematic and enrichment plot for pairwise comparison between Cebpa^+/+ MPP3 isolated from chronic IL-1β–treated versus vehicle-treated mice (“chronic IL-1β effect”). (B) Schematic and enrichment plot for pairwise comparisons between Cebpa^Δ/Δ versus Cebpa^+/+ MPP3 isolated from chronic IL-1β–treated mice (“Cebpa^Δ/Δ modification of chronic IL-1β effect”). (C) Heatmap for leading edge genes from B (genes for heatmap are provided in Table S1). (D) Experimental design for Fluidigm Biomark gene expression analysis (one experiment independent from RNA-Seq, eight replicates from n = 5 pooled mice per group). (E) Relative expression of self-renewal genes (Bmi1, Foxo3, Mpl, and Mycn) calculated by first normalizing to Gusb within each group, then normalizing to Cebpa^+/+ vehicle group. (F–H) Liquid culture data representative of three separate experiments with n = 3–5 per group. (F) Experimental design for MPP3 liquid culture. (G) Time course of Mac1⁺Gr1⁺ absolute numbers. (H) Time course of MPP3 absolute numbers. (I–K) CFU assay representative of two experiments with n = 3 or 6 per group. (I) Experimental design for MPP3 CFU. (J) CFU counts per plate and total cell counts per plate from initial plating. (K) CFU counts per plate upon replating 10⁴ cells and calculated cumulative CFU potential from second plating. FDR, false discovery rate; NES, normalized enrichment score. Data are presented as mean ± SD and analyzed by two-way ANOVA with Tukey’s multiple comparisons test. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001, except in G and H, in which symbols for different comparisons are indicated.

Figure S4.

CEBPA regulates expression of self-renewal and myeloid genes and cell competition in culture. (A and B) MPP3 liquid culture (data are representative of two experiments with n = 3 per group). (A) Representative flow cytometry plots for MPP3 cell culture at day 4. (B) Relative expression of self-renewal genes (Bmi1, Foxo3, Mpl, and Mycn) calculated by first normalizing to Gusb within each group, then normalizing to Cebpa^+/+ vehicle group from MPP3 cell culture at 12 h. (C) MPP3 CFU assay (data are representative of two experiments with n = 3 or 6 per group): third and fourth plating CFU counts per plate upon replating 10⁴ cells. (D and E) Cell culture of AML cell lines MOLM-13, MOLM-14, EOL-1, and K562 (representative of two experiments with n = 3 per group). (D) Cell competition dynamics. (E) Gene expression analysis of CEBPA target genes from sorted GFP⁺ MOLM-13 cells at day 6. EV, empty vector. Data are presented as mean ± SD and analyzed by two-way ANOVA with Tukey’s multiple comparisons test (B–D) or unpaired t test (E). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

Figure 8.

IL-1β-Cebpa–dependent genes are highly enriched for C/EBPα and PU.1 binding sites. (A) Table summarizing C/EBPα-, PU.1-, and dual-bound regions at genes that are up- or down-regulated by chronic IL-1β in a Cebpa-dependent manner in LSK, preGM, GMP, and granulocytes. (B) Table summarizing C/EBPα binding for IL-1β-Cebpa–dependent gene within indicated gene sets in LSK, preGM, GMP, and granulocytes.

Figure 9.

The IL-1β-Cebpa–dependent signature is associated with AML subtype. (A) Heatmap of IL-1β-Cebpa–dependent gene score for AML samples from TCGA. (B) Graph of IL-1β-Cebpa–dependent gene score for AML samples from TCGA by FAB subtype. (C) Graph of IL-1β-Cebpa–dependent gene score for de novo, relapse, or secondary to MDS or MPN AML samples from Beat AML. Data are presented as mean ± SD and analyzed by one-way ANOVA with Tukey’s multiple comparisons test. *, P < 0.05; ***, P < 0.001; ****, P < 0.0001.

Figure 10.

Ectopic CEBPA expression induces differentiation and impairs fitness in AML cells. (A) Cell competition dynamics of primary AML sample AML0626 in cell culture. EV, empty vector. (B) Cell expansion of primary AML sample AML0626 in cell culture. (C) Western blot of sorted GFP⁺ cells at day 6. (D) Flow cytometric analysis of differentiation markers on GFP⁺ cells at day 6. (E) Flow cytometric analysis of primitive markers on GFP⁺ cells at day 6. (F) Gene expression analysis of CEBPA target genes from sorted GFP⁺ cells at day 6. (G) Model of inflammation-driven HSPC differentiation that selects for phenotypes such as with Cebpa LOF that prevent HSPC differentiation and/or promote self-renewal. For A–F, n = 3 per group, presented as mean ± SD, and analyzed by two-way ANOVA with Tukey’s multiple comparisons test (A and B, D and E) and unpaired t test (F). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. Data are representative of three experiments.