CMML HSPCs show a decrease in inflammatory response pathways
To explore the characteristics of pathological aged hematopoiesis in CMML patients versus healthy aging, we assembled a cohort of untreated CMML patients, at the time of diagnosis, and age-matched healthy donors (herein referred to as controls) (Supplementary Table 1). Bulk RNA-sequencing (RNA-seq) analysis was performed on CD34+ hematopoietic stem and progenitor cells (HSPCs) isolated from the bone marrow (BM) of 19 patients (mean age 70.6, range 49–84) and 12 age-matched controls (mean age 68, range 54–91). Principal component analysis (PCA) showed separation of control and patient transcriptomes (Fig. 1a). Of 2664 differentially expressed genes (DEGs) (adjusted p value < 0.1), 54% were upregulated (Fig. 1b and Supplementary Data 1). Gene set enrichment analysis (GSEA) examining HALLMARK and KEGG gene sets indicated that control cell transcriptomes were significantly enriched in various inflammatory, innate immune response, cytokine signaling, as well as cell cycle, P53, and apoptosis pathways (Fig. 1c and Supplementary Fig. 1a and Data 2). Gene Ontology process analysis unveiled that, beyond immune response, terms associated with chromatin remodeling and DNA packaging were enriched in controls (Fig. 1d and Supplementary Fig. 1b and Data 2). In contrast, patient cells exhibited enrichment in only a few terms related to ribosomes, vascular system development, and adhesion (Fig. 1d and Supplementary Fig. 1a).
a Principal component analysis (PCA) plot of BM CD34+ cells isolated from 19 CMML patients at diagnosis and 12 controls, based on RNA-seq regularized log transformed expression values. b MA-plots showing differentially expressed genes (p adj <0.1), upregulated (blue dots) or downregulated (black dots) in CMML cells. c–e Dot plots showing selected enriched HALLMARK (total 36), GO (total 1330) and senescence gene sets upregulated (positive NES, red dots) and downregulated (negative NES, blue dots) in CMML cells. Gene sets are ranked by their NES and gene ratio scores. f, g Enrichment plots for aging published gene sets. FDR false discover rate, NES normalized enrichment score. *FDR < 0.05.
Increased expression of inflammatory genes, P53 signaling and chromatin deregulation are indicative of senescence and aging8,18,19,20,21,22. The transcriptome of patient HSPCs therefore suggests a younger state compared to controls. Supporting this possibility, senescence and aging signatures were more pronounced in control cells (Fig. 1e, f and Supplementary Fig. 1c). Furthermore, a signature composed of genes upregulated in aged versus young human BM HSCs22 was depleted in patient cells, while genes downregulated with age were marginally enriched (Fig. 1g).
Chromatin is remodeled in CMML HSPCs
We have previously shown that murine and human HSC aging is associated with a loss of H3K9me3 heterochromatin mark9,11. Decreased expression of the heterochromatin mark H3K9me2, assessed by immunofluorescence, was also detected in HSCs from aged mice and in CD34+ BM cells from aged individuals compared with umbilical cord blood (Supplementary Fig. 2a, b). These results prompted us to analyze H3K9me3 and H3K9me2 expression in HSPCs from patients and controls. Surprisingly, immunofluorescence analysis suggested a significant decrease in H3K9me3 expression in patient cells (Fig. 2a), which was confirmed by immunoblot analysis in five patients (Supplementary Fig. 2c). As H3K9me3 is a repressive mark, this suggests that this epigenetic change is not responsible for the decreased expression of aging and senescence genes observed CMML cells, compared to age healthy cells (Fig. 1f, g). In contrast, a significant increase in H3K9me2 expression was detected by immunofluorescence in the CD34+ cells of 28/29 patients (Fig. 2b), and validated by immunoblot analysis in five patients (Supplementary Fig. 2d). This correlated with heightened expression of the H3K9-dimethyltransferases G9A and GLP, particularly at the protein level (Fig. 2c, d and Supplementary Fig. 2e, f). Increased expression of H3K9me2, G9A and GLP were also observed in patient CD34+CD38–CD90+ HSC-enriched populations (Supplementary Fig. 2g–i). No correlation was found between the level of H3K9me2 in CD34+ cells and the presence of TET2, RAS, ASXL1 or SRSF2 mutations, WBC counts, the percent of BM blasts or age (Supplementary Fig. 2j–m).
a H3K9me3, b H3K9me2, c G9A and d GLP immunostaining in CD34+ cells from CMML patients and controls. Representative images and quantification of mean global immunofluorescence (IF) intensity using ImageJ software are shown. Means ± SEM from 2–4 independent experiments normalized to the mean intensity of controls. Each dot represents a single individual, with at least 50 cells counted per sample. Bars, 3 µm. Mann–Whitney test, **p < 0.01; ****p < 0.0001. e Heat map of the differentially chromatin accessible regions in CMML patient (n = 4) and control (n = 3) CD34+ cells ±2.5 kb from the center of the peak (CoP). f Venn diagrams depicting the overlap of DEGs in CMML HSPCs with genes assigned to gained or lost ATAC peaks (−100/+25 kb from TSS). Fisher’s exact test. g Motifs and p values for enrichment motifs of TF involved in IFN/NF-κB signaling in ATAC-seq peaks unique to patients (gained) and controls (lost) using HOMER. ND non detected. h KEGG gene sets (FDR < 0.25) of deregulated genes that also exhibit gained (red) or loss chromatin accessibility in CMML patient cells (blue).
To explore the impact of these opposite heterochromatin modifications on chromatin opening genome-wide, we conducted Assay for Transposase-Accessible Chromatin-sequencing (ATAC-seq) experiments in CD34+ cells from 4 patients and 3 controls. We detected 40,335 differential peaks, with 31,110 (77%) gained and 9245 (23%) lost in CMML cells (Fig. 2e and Supplementary Data 3). Altered peaks were significantly enriched in intergenic and intronic regions, while common peaks were predominantly located at the transcription start sites (Supplementary Fig. 3a). Assigning differential ATAC-seq peaks to genes15 demonstrated a substantial overlap between DEGs and ATAC-seq peaks (Fig. 2f). Analysis of transcription factor (TF) motifs using HOMER demonstrated specific or stronger enrichment of motifs for TF involved in hematopoietic differentiation (FLI1, RUNX1, GATA1, GATA2, NF-E2, EKLF, MAFB, MYB), TGF-β signaling (SMAD2, SMAD3, SMAD4) and inflammation (NFκB, IRF1, IRF3, RFX, ISRE), in ATAC-seq peaks with reduced compared with gained chromatin accessibility (Fig. 2g, Supplementary Fig. 3b and Supplementary Data 4). This is consistent the lower enrichment of these pathways in CMML patient cells (Fig. 1c, d and Supplementary Data 2). In addition, numerous processes related to immune/inflammation/NFκB signaling were associated with genes exhibiting loss of chromatin accessibility (Fig. 2h and Supplementary Fig. 3c). This suggests that the attenuated expression of certain immune/inflammatory response genes in patient cells might be related to an altered chromatin accessibility.
Together, these results highlight a profound chromatin remodeling that may contribute to repressing inflammatory genes in CMML compared to healthy CD34+ cells.
H3K9me2 is enriched at TEs in CMML HSPCs
H3K9me2 is recognized as a suppressor of innate immune genes, notably exerting direct control over the expression of IFNB1 gene, encoding IFN-β, and certain IFN-stimulated genes (ISGs)23,24. Thus, increased H3K9me2 in CMML cells could contribute to the observed decreased chromatin accessibility at immune/inflammatory genes and in their expression. We therefore focused on this mark, performing H3K9me2 CUT&Tag analysis in CD34+ cells, comparing 4 patients with 3 controls. As expected from immunofluorescence and western blot experiments, patient cells exhibited a greater number of recovered peaks (15,406 ± 1484) compared to control cells (4831 ± 1600) (Supplementary Fig. 4a). Focusing on peaks shared by all 4 patients or 3 controls, we identified 1396 gained peaks exclusive to patients and only 88 peaks unique to controls (Fig. 3a and Supplementary Data 5). H3K9me2 peaks spread mainly across intergenic and intronic regions in both patient and control cells (Fig. 3b). However, when compared to the genome using Genome Association Test, only a small significant enrichment of the mark at promoters and 1–5 kb regions was found in patient cells (Supplementary Fig. 4b). Biological processes associated with the nearest promoters gaining H3K9me2 in patient cells did not show enrichment in immune pathway genes or IRF/NFκB transcription factors (Supplementary Data 6). Moreover, there was no significant difference between patients and controls in the expression of H3K9me2-linked genes (Supplementary Fig. 4c), and no correlation was identified between H3K9me2 concentration at the promoter level and gene expression (Supplementary Fig. 4d). Finally, there was no H3K9me2 read enrichment at peaks showing either decreased or increased accessibility (supplementary Fig. 4e), suggesting that H3K9me2 increase in CMML patients is not directly linked to chromatin accessibility and gene expression.
a Venn diagram of peak retrieved from the calling from H3K9me2 CUT&Tag on CD34+ from 4 patients (P) and 3 controls (CTA). b Repartition of the CUT&Tag peaks found exclusively in patients and controls. c Numbers of common peaks found exclusively in the 4 patients (red) and 3 controls (blue) and numbers of TEs annotated in these peaks. d Enrichment or depletion of the different classes of TEs in gained or lost H3K9me2-CUT&Tag peaks. The Y-axis representing the enrichment score was calculated as the log2 fold change of the number of specific peaks overlapping with TEs found in patient gained or lost peaks over the median number of TEs found in 1000 times the same number of randomly selected peaks overlapping with TEs. Positive log2 fold change = enrichment, and negative log2 fold change = depletion. e Repartition of the different TE classes in CUT&Tag peaks found exclusively in patients and controls.
Since H3K9me2 is also known to repress TEs25,26, we analyzed CUT&Tag data by considering all mapping reads, either unique and multiple, that mapped without mismatch, and we randomly assigned them at one of their best possible positions in the genome, as described11. This analysis identified a pronounced H3K9me2 enrichment at TEs relative to genes in patients, with 13,364 TEs among H3K9me2-bound peaks in CMML cells, compared to 255 in control cells (Fig. 3c and Supplementary Fig. 4f). TE enrichment in patient and control peaks was performed using a permutation test, counting peaks that intersected with any TE belonging to a given TE class in CMML unique (gained) and control unique (lost) peaks and in 1000 times an equal number of peaks randomly chosen. This revealed that patient gained H3K9me2 peaks were significantly enriched for all TE classes (Fig. 3d and Supplementary Fig. 4g). In contrast, ERVs and SINEs were under-represented in lost peaks. The distribution of H3K9me2 among TE classes showed that the proportion of ERVs was greater in peaks gained than in peaks lost, while LINEs were overrepresented among TE lost (Fig. 3e). Overall, these results highlight that the profound chromatin remodeling detected in CMML CD34+ cells involves an enrichment of H3K9me2 at TEs.
The HMA and G9A/GLP inhibitor combination reduces CMML HSPC clonogenicity
Recent data have shown that HMAs, when used in various pathological contexts, can act through the reactivation of TEs16,17, ultimately triggering the activation of IFN-I and NF-κB pathways. Our initial results led us to speculate that deregulated G9A/GLP methyltransferases and histone marks could interfere with CMML cell response to HMAs. To test this hypothesis, CMML and healthy donor CD34+ cells were treated ex vivo with the G9A/GLP inhibitor UNC0638, the HMA decitabine (DAC) and their combination, then seeded in methylcellulose (Fig. 4a). Since H3K9me2 has been shown to bind to demethylated regions where it can then reinstall DNA methylation26,27, we added UNC0638 2 days after DAC. Dose-response experiments demonstrated that each compound alone had a modest impact on colony formation by patient cells. In contrast, the combination of DAC and UNC0638, even at low doses, significantly reduced the clonogenicity of these cells (Fig. 4b). Using the Chou-Talalay method28, a synergistic effect was observed under all conditions (Fig. 4c, d). Consistent with the low expression of G9A/GLP in control cells, no synergy between DAC and UNC0638 on their clonogenicity was detected (Supplementary Fig. 5a). Although the highest dose of DAC showed some toxicity on healthy cells, CMML leukemic cells were much more sensitive to the combination, with the highest doses decreasing by 80% and 20% the number of colonies formed by CD34+ cells from patients and control cells, respectively.
a Treatment protocol of CD34+ cells. DAC decitabine, AZA 5-azacytidine, UNC0638 and UNC0642 G9A/GLP inhibitors, CM-272 dual DNMT1 and G9A/GLP inhibitor. b Dose-response effect of DAC (X-axis) and UNC0638 (color scale) on CMML CD34+ colony formation. Mean ± SEM from 3 patients. Two-way ANOVA Bonferroni’s multiple comparisons. c, d Chou-Talalay model of the effects of combining different doses of DAC and UNC0638. The fraction affected (fa) corresponds to the proportion of colonies eliminated by the treatments. The combination index (CI) is calculated by CompuSyn software (ComboSyn. Inc.) where CI < 1, CI = 1, CI > 1 indicates a synergistic, additive and antagonistic effect respectively. Mean ± SEM from 3 patients. e Number of colonies formed from CMML (n = 28) and control (n = 12) CD34+ cells in the absence of treatment. One dot represents a single individual. t-test. f, g Number of colonies formed by CD34+ cells from patients (f) or controls (g) after treatment with 10 nM DAC and 1 μM UNC0638 alone or in combination. NT non-treated. One dot represents a single individual; controls, n = 12; patients, n = 28. Results are normalized to the number of colonies in the NT condition. Means ± SEM. One-way ANOVA Bonferroni’s multiple comparison. h, i Number of colonies formed by CD34+ cells from patients, n = 5 (h) or controls, n = 4 (i) after treatment with or without (NT) 200 nM CM-272. Results are normalized to the number of colonies in the NT condition. One dot represents a single individual. Means ± SEM. t-test. **p < 0.01; ***p < 0.001; ****p < 0.0001.
Subsequent experiments were performed with 10 nM DAC and 1 µM UNC0638. A significant reduction in global DNA methylation level was detected by ELISA after 2 days of DAC, which was maintained at day 4, either alone or combined with UNC0638, while UNC0638 alone had no effect on DNA methylation (Supplementary Fig. 5b, c). The level of H3K9me2, measured by immunofluorescence, remained unchanged after 2 days of culture in the presence of DAC alone (Supplementary Fig. 5d), while it was markedly reduced by UNC0638 (Supplementary Fig. 5e). These experiments validated the proper functioning of the tested drugs.
In the absence of treatment, the numbers of colonies formed by CD34+ cells were comparable between control and patient cells (Fig. 4e). Treatment with DAC + UNC0638 inhibited the clonogenicity of 26 out of 28 tested CMML CD34+ cells and reduced the colony size while each inhibitor alone had a weaker (DAC) or no (UNC0638) effect (Fig. 4f and Supplementary Fig. 6a, b). None of these treatments affected the growth of control CD34+ cells (Fig. 4g and Supplementary Fig. 6a). Similar results were obtained with the combination of another HMA, 5-Azacytidine (AZA), combined with UNC0638, and with another G9A/GLP inhibitor, UNC0642, combined with DAC (Supplementary Fig. 6c–f). Finally, CM-272, a dual inhibitor of DNMT1 and G9A/GLP29, specifically reduced the clonogenicity of CMML but not control cells (Fig. 4h, i).
To more precisely identify the cell population targeted by the combination, CD34+ cells were enriched in CD34+CD38−CD90+ (HSC-enriched, referred to as stem cells) and CD34+CD38−CD90− (progenitor-enriched, referred to as progenitors) cells. We functionally assessed how the inhibitors affected the cell clonogenic potential by testing their capacity to serially replate in methylcellulose over 3 passages after treatment (Fig. 5a). In the absence of treatment, the number of colonies formed by control and patient stem cells was not significantly different (Supplementary Fig. 7a, b). The DAC/UNC0638 combination triggered a drastic reduction in the number and size of colonies formed by both CMML stem cells and CMML progenitors (Fig. 5b and Supplementary Fig. 7b, c). DAC alone slightly decreased the size of the colonies generated by CMML progenitors (Supplementary Fig. 7b) and, starting from P2, significantly reduced their number, while having no effect on the stem cell-enriched population (Fig. 5b). Measuring the cumulative clonogenic potential at P2, which considers both the number of colonies and their size30, confirmed the strong effect of the combination on both stem cells and progenitors while DAC affects in priority the latter populations (Fig. 5c). None of the treatments affected colony formation by stem cells or progenitors from controls (Supplementary Fig. 7c, d).
a Protocol for treatments and serial replating assays in methylcellulose using stem cell- (CD34+CD38−CD90+) or progenitor- (CD34+CD38−CD90−)-enriched populations. P passage. b Number of colonies formed from CMML patient stem and progenitor cells (n = 3) after the different passages in the presence or absence of DAC ± UNC0638. Numbers are reported to 5000 cells. Mean ± SEM. One-way ANOVA. c Effects of DAC and/or UNC0638 treatments on the cumulative clonogenic potential ([number of colonies at P2/number of cells planted at baseline] × number cells retrieved at P1) of stem and progenitor cells from patients, n = 3. Mean ± SEM. One-way ANOVA Bonferroni’s multiple comparison. d Protocol for treatments and single cell liquid culture assays using stem cell- (CD34+CD38−CD90+) or progenitor- (CD34+CD38−CD90−)-enriched populations. e–g Single cell liquid cultures. Viability (e), proliferation index (f) and cell number distribution per well at day 8 of the culture (g) of CMML patient stem cells (left panel) or progenitors (right panel) treated with either DAC (green), UNC0638 (blue) or both (red), or left non-treated (NT, black). n = 3. Mean ± SEM. Two-way ANOVA Bonferroni’s multiple comparison. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.
We further explored drug effects in single-cell liquid cultures (Fig. 5d), measuring cell viability (number of wells with at least one cell) and proliferation (total number of cells in wells with at least one cell). In the absence of treatment, viability and expansion of both stem cells and progenitors were similar in control and patient samples (Supplementary Fig. 8a, b). However, the colony size formed by CMML cells was larger than those of controls (Supplementary Fig. 8c). The combination reduced the viability and expansion of both patient stem cells and progenitors (Fig. 5e–g). DAC treatment alone targeted patient progenitors only, UNC0638 alone had no effect, and none of the treatments impaired the viability and proliferation of control stem cells and progenitors (Supplementary Fig. 8d–f).
We subsequently interrogated the ability of the drug combination to selectively eliminate leukemic cells by performing Sanger sequencing of pre-identified mutated genes (Supplementary Table 2) in colonies grown from CD34+ cells in methylcellulose and from CD34+CD38−CD90+ cells cultured at one cell per well for 14 days, focusing on somatic mutations with a variant allele frequency (VAF) of 30% or more. Detecting mutations with the highest VAF likely captures the primary events and major clones, as previous studies demonstrated that mutations accumulate almost linearly in CMML stem and progenitor cells, with limited branching events and early clonal dominance2. In line with these previous findings2, a minority of wild-type cells (ranging from 0 to 40%) were found in untreated conditions (Fig. 6). The lack of detection of wild-type cells in patient #3564 could be due to an overrepresentation of mutated clones in methylcellulose2 and the limited number of clones analyzed. While DAC and UNC0638 showed limited effects when tested alone, the combination drastically reduced the proportion of mutated clones in all patients (Fig. 6). In patients #3459 and #3562, with mutations in TET2 and KRAS, respectively, the major clones specifically and completely disappeared. Patients #3480 (harboring clones with 0, 1, or 2 mutations) and #3564 (harboring clones with 1, 2, or 3 mutations), showed increased proportions of non-mutated cells, along with reduction in the most mutated clones carrying 2 or 3 mutations. UNC0638 alone slightly increased the proportion of clones or colonies without any mutation (patients #3459 and #3562) or harboring 1 vs. 2 mutations (patient #3480). DAC alone tended to favor the growth of clones harboring mutations (patients #3459 and #3562) or the most mutated clones (increased size of clones with 3 mutations from 59 to 78% in patient #3564). Altogether, these results show that DAC and UNC0638 demonstrate a synergistic and specific impact on leukemic cells while preserving wild-type cells.
Evaluation of the variant allelic frequency of identified mutated genes with VAF > 30%, after 14 days of culture of CD34+ cells in methylcellulose (left panel) or CD34+CD38−CD90+ stem cells in liquid cultures (right panel), in the 4 conditions, as indicated. Percentage of cells with 0 (blue), 1 (light green and white), 2 (dark and light gray), or 3 (red) mutations. Mutation VAF are indicated over each panel.
The HMA and G9A/GLP inhibitor combination increases TE expression in CMML CD34+ HSPCs
To assess the impact of DAC and UNC0638 on TE expression, we performed RNA-seq analysis on CMML CD34+ cells (n = 4 patients) treated in liquid culture (Fig. 7a). Cells were harvested at day 4. At that time, the number of cells was not significantly different between treated and non-treated conditions (Supplementary Fig. 9a). Multimapping analysis of RNA-seq data revealed 340 differentially expressed TE families (p < 0.05), all exhibiting increased expression after treatment with the combination compared to untreated cells (Fig. 7b and Supplementary Data 7). In contrast, only two differential TE families were identified after 4 days of treatment with either DAC or UNC alone (Supplementary Fig. 9b, c). Upon DAC/UNC0638 combination, ERVs and DNA transposons accounted for 43% and 32% of differentially expressed TEs, respectively (Fig. 7c). Notably, ERV retrotransposons showed significant enrichment compared to LINEs and DNA transposons (Fig. 7d). Comparative analysis of these deregulated TEs across all culture conditions revealed that DAC and UNC0638 alone elevated ERV and DNA transposon expression compared to untreated cells, with the combination synergistically increasing the expression of ERVs, DNA and LINEs (Fig. 7e and Supplementary Fig. 9d). None of the treatments affected SINE expression.
a–e TE expression in RNA-seq analysis from CD34+ cells from 4 patients, after treatments in liquid culture with either DAC, UNC0638 or DAC + UNC0368, or left untreated (NT). a Protocol for treatments in liquid culture. b Volcano plots showing differential TE expression (p val < 0.05) in the DAC + UNC0638 condition compared to NT cells. c TE family repartition in differentially expressed TEs. Numbers indicate the percentage represented by each family. d Log2 Fold-change increase of differentially expressed TE classes in the DAC + UNC0638 condition vs. NT cells. One-way ANOVA Bonferroni’s multiple comparison. e Expression levels of TEs differentially expressed in the DAC + UNC0638 vs. NT condition in each of the treatment conditions, sorted by TE class. f–h Differential analysis of ERV loci in RNA-seq data from 7 patients after treatments with DAC, UNC0638 or both compared to the untreated condition (NT). Venn diagrams of the differentially expressed ERV transcripts (p val < 0.05, FC 1.5), up- (f) and down-regulated (g) in each of the treated condition vs. NT, as indicated. h Heat map representation of the median expression level of differentially expressed ERVs in DAC + UNC0638 in the different conditions. Clusters with fewer than 20 nodes were excluded from the analysis. i RT-qPCR analysis of mRNA expression of chosen ERV families in the different conditions. Ct were normalized to HPRT, Tubulin, Gus, PPIA and/or RPL32 and reported to the NT condition. One line represents a single patient. Means ± SEM. One-way ANOVA Tukey’s multiple comparison. *p < 0.05; **p < 0.01.
Focusing on ERVs that displayed the most significant differential expression upon DAC/UNC0638 treatment, we conducted a loci-based quantification, as described in our previous work31, incorporating 4 additional patient samples. We identified 2120 differentially expressed ERV loci (p < 0.05, FC 1.5) between untreated and DAC/UNC0638 conditions, most of them (97%) upregulated (Fig. 7e, f and Supplementary Data 8). Confirming the results above, the impact of DAC or UNC0638 treatment alone was notably weaker, resulting in 120 and 122 differentially regulated ERV loci, respectively, compared to non-treated condition (Fig. 7f, g). A majority of the ERVs induced by the combination (1991/2056) were specific to this condition, whereas either treatment alone upregulated very few specific ERVs (10% and 20% for UNC0638 and DAC, respectively). Conversely, differentially downregulated loci were largely specific to each condition (48/58 and 43/43 of the ERVs downregulated by UNC0638 or DAC alone). Focusing on ERVs differentially expressed in all conditions compared with untreated cells, the vast majority of loci exhibited a synergistically higher expression level in cells treated with the combination than in DAC or UNC0638 treatment alone (Fig. 7h). RT-qPCR experiments targeting ERV family members deregulated by the combination further validated their greater or synergistic induction after 4 days of treatment with DAC/UNC0648 compared to either inhibitor alone (Fig. 7i). Together, these results indicate that the HMA and G9A/GLP inhibitor combination, but not each inhibitor alone, induces a significant and rapid derepression of TEs, particularly ERVs, in CMML CD34+ cells.
The DAC/UNC0638 combination reactivates viral and inflammatory pathways in CMML cells
ERVs can generate double-stranded RNAs (dsRNAs) that are recognized by antiviral pattern sensors, leading to IFN-I production and activation of the IFN/NFκB pathway—a process known as viral mimicry, which exhibits an anti-tumoral effect13,16,17. Analysis of coding gene expression revealed 3227 DEGs (p < 0.05, FC 1.2), of which 2914 (90%) are positively and 313 (10%) are negatively expressed in DAC/UNC0638 treated compared with untreated CD34+ cells (Fig. 8a, b and Supplementary Data 9). Treatment with DAC or UNC0638 alone induced only 187 and 158 DEGs, respectively, with 56% and 53% being overexpressed, and 44% and 47% being downregulated. GSEA revealed that genes upregulated by the DAC/UNC0638 combination were enriched for IFN, NFκB, and other inflammatory pathways, TP53, and apoptosis. In contrast, downregulated genes included those associated with DNA and histone methylation, transcription, and cell proliferation pathways (Fig. 8c, d and Supplementary Fig. 10a–d). No specific gene sets were found to be enriched in cells treated with DAC or UNC0638 alone. Gene Set Variation Analysis (GSVA) revealed that the majority of IFN signaling and IFN production signatures were positively enriched by the combination as compared with any individual treatment (Fig. 8e). RT-qPCR experiments showed that the combination significantly increased the expression of IFNB1 mRNA, encoding IFN-β, and TFs such as IRF9 and IRF7 involved in IFN signaling (Fig. 8f), confirming RNA-seq results. These data demonstrate that TE derepression induced by the combined treatment correlates with the reactivation of viral and inflammatory pathways in CD34+ cells from CMML patients.
a–e RNA-seq-analysis of coding genes from CD34+ cells of 7 patients after 4 days of treatment or not with DAC, UNC0638 or both. Each condition is compared to NT cells. a Venn diagram showing the number of common or unique DEGs in each condition. b Distribution of DEGs overexpressed (red) and downregulated (blue). GSE analysis of pathways enriched in upregulated (c) and downregulated (d) genes in DAC + UNC0638 vs. NT. e Enrichment analysis of different IFN/antiviral signatures by single sample gene-set variation analysis (ssGSVA). f mRNA expression level of IFNB1, IRF7 and IRF9 measured by RT-qPCR. Ct were normalized by custom housekeeping genes (HPRT, Tubulin, Gus, PPIA and/or RPL32) and reported to the NT condition. Each line represents a single patient. Means ± SEM. One-way ANOVA Dunnett’s multiple comparison *p < 0.05.
The induction of IFN signaling by the combination is essential for eliminating CMML HSPCs
We further examined whether IFN signaling is dysregulated at the protein level. Immunofluorescence analysis demonstrated increased levels of key proteins involved in IFN-I production (IRF3 and IRF7) and IFN signaling (STAT1) in CD34+ cells from CMML patients after 4 days of culture with DAC/UNC0638, compared to untreated cells (Fig. 9a–c). While HMA treatment alone significantly increased IRF7 and STAT1 protein levels, the combination induced a much stronger response. Notably, only the combination led to a substantial increase in the phosphorylated form of STAT1 (pSTAT1) (98-fold compared to untreated), indicating the activation of IFN signaling after 4 days of culture (Fig. 9d). In control cells, only a modest increase in IRF3 was observed upon treatment with the combination (1.5-fold), and this increase was notably lower compared to that observed in patients (68-fold) (Supplementary Fig. 11a–d). These findings further underscore the specific and potent activation of IFN signaling achieved by the combination treatment in CMML CD34+ cells.
Representative images and quantification of the mean overall IF intensity of a IRF3, b IRF7, c STAT1, d pSTAT1 and e dsRNAs in patient CD34+ cells after 4 days of culture. Results are reported to the mean IF intensity in the NT condition. N = 2 patients. Bars, 3 µm. Quantifications were performed using ImageJ software. Violin plots representing the mean IF intensity of each cell. At least 45 cells counted per sample. Dotted lines: median and 25th and 75th percentiles. One-way ANOVA Bonferroni’s multiple comparison. **p < 0.01; ****p < 0.0001.
To investigate the potential involvement of ERVs in activating IFN signaling, we assessed dsRNA formation using J2 antibody that specifically recognizes dsRNAs. The combination treatment markedly increased dsRNA expression in patient cells, while having no significant effect on control cells (Fig. 9e and Supplementary Fig. 11e). Consistent with its modest impact on IRF7 and STAT1 expression, DAC alone showed a slight increase in dsRNA expression, whereas UNC0638 alone had no observable effect (Fig. 9e).
Blocking IFNAR2 (IFN-I receptor) with a blocking antibody (Fig. 10a) partially restored the clonogenic capacity of CMML CD34+ cells in the presence of DAC/UNC0638 (Fig. 10b, c). This finding highlights the contribution of the antiviral response and IFN signaling in CMML cell death induced by the DAC/UNC0638 combination.
a Protocol scheme for the treatments with DAC ± UNC0638 and blocking IFN receptor (IFNAR2) antibodies. The anti-IFNAR2 antibody (1 µg/ml) was added on days 2 and 4 and the cells were seeded in methylcellulose on day 4. b Number of colonies at passages 1 and 2, reported to the non-treated condition. c Cumulative potential at passage 2. Results are reported to those obtained in the NT condition. Mean ± SEM; n = 6 patients. One-way ANOVA Bonferroni’s multiple comparison. *p < 0.05; ***p < 0.001; ****p < 0.0001. d Model illustrating the increase in H3K9me2 at TEs and repression of immune-associated transcripts in CMML HSPCs compared with age-matched healthy HSPCs (left). The mechanism repressing inflammatory gene is unknown but independent of H3K9me2. TEs are repressed by both H3K9me2 and DNA methylation in CMML cells, as shown by their reexpression only upon treatment with a combination of HMA and G9A/GLP inhibitors (right). Reexpression of TEs results in dsRNA formation, induction of IFN signaling and reactivation of the innate immune response in CMML HSCs, selectively targeting mutated cells while preserving residual wild-type HSCs. Left: Dark-blue cell, healthy donor HSC; red cells, CMML HSC. CMML mutated cells enter in apoptosis upon treatment with the combination. Right: red cell with a yellow star, CMML mutated HSC; light-blue cell, non-mutated HSC in CMML patients. The figure was created by AP and FP. Pictures from the cells are from Servier medical Art (https://smart.servier.com/).
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