Specific molecular signatures predict decitabine response in chronic myelomonocytic leukemia

Abstract

Myelodysplastic syndromes and chronic myelomonocytic leukemia (CMML) are characterized by mutations in genes encoding epigenetic modifiers and aberrant DNA methylation. DNA methyltransferase inhibitors (DMTis) are used to treat these disorders, but response is highly variable, with few means to predict which patients will benefit. Here, we examined baseline differences in mutations, DNA methylation, and gene expression in 40 CMML patients who were responsive or resistant to decitabine (DAC) in order to develop a molecular means of predicting response at diagnosis. While somatic mutations did not differentiate responders from nonresponders, we identified 167 differentially methylated regions (DMRs) of DNA at baseline that distinguished responders from nonresponders using next-generation sequencing. These DMRs were primarily localized to nonpromoter regions and overlapped with distal regulatory enhancers. Using the methylation profiles, we developed an epigenetic classifier that accurately predicted DAC response at the time of diagnosis. Transcriptional analysis revealed differences in gene expression at diagnosis between responders and nonresponders. In responders, the upregulated genes included those that are associated with the cell cycle, potentially contributing to effective DAC incorporation. Treatment with CXCL4 and CXCL7, which were overexpressed in nonresponders, blocked DAC effects in isolated normal CD34+ and primary CMML cells, suggesting that their upregulation contributes to primary DAC resistance.

Figures

Figure 8. CXCL4 and CXCL7 promote resistance to DAC in CD34+ and primary CMML specimens.

(A) Colony formation was inhibited by DAC but restored with the combination of CXCL4 and CXCL7. CD34+ cells were treated with 1 dose of CXCL4, CXCL7, or both (50 ng/ml each) or with vehicle (PBS containing 0.1% BSA) and daily 10-nM doses of DAC for 3 days. After 3 days of in vitro treatment with DAC, cells were plated in methylcellulose and incubated for 12 to 15 days before colonies were counted. Data represent the mean ± SD. Treatment with 10 nM DAC significantly decreased colony formation but failed to do so in the presence of CXCL7 and CXCL4 together. Shown in the 3 panels are the results of 3 independent experiments. Error bars represent the SD. (B) CXCL4 and CXCL7 abrogated the effect of DAC on the viability of primary CMML MNCs. CMML MNCs were treated in vitro for 72 hours with 10 nM DAC alone or in the presence of 50 ng/ml CXCL4, CXCL7, or both. Data represent the mean ± SD. Treatment with DAC alone significantly reduced the viability of these cells, but this effect was lost when CXCL4 or CXCL7 was added to the culture. All data represent independent experiments performed in 3 different CMML patients. Error bars represent the SD. *P < 0.05 and **P < 0.01 by unpaired 2-tailed Student’s t test.

Figure 7. CXCL4 and CXCL7 are upregulated in the BM of nonresponders.

(A) qRT-PCR showing validation of overexpression of CXCL4, CXCL7, and ITGB3 in nonresponders; each point represents the mean of triplicate wells for each patient sample; the line and error bars indicate the group mean and SD, respectively. (B) Pearson’s correlation analysis of expression levels of CXCL7 and CXCL4 by RNA-seq and qRT-PCR. (C and D) Representative IHC images for CXCL4 (C) and CXCL7 (D) in diagnostic BM biopsies in DAC responders and nonresponders. Original magnification, ×40 (C and D, left panels), ×63 (C and D, right panels). Representative images from duplicate experiments are shown.

Figure 6. A specific transcriptional program is associated with response to DAC.

(A) Heatmap illustrates gene expression differences between 8 DAC-sensitive (indicated by the red bar) and 6 DAC-resistant patients (indicated by the blue bar). Genes represented in the heatmap were identified by a GLM likelihood ratio test (P < 0.05 and absolute log2 fold change >1). (B) Enrichment plots for GSEA using the expression difference–ranked gene list showing enrichment for cell cycle–related gene sets. NES, normalized enrichment score. (C) Box plots showing gene expression differences for CXCL4, CXCL7, and ITGB3 (red box plots denote responders; blue box plots denote nonresponders). P values were obtained from a GLM likelihood ratio test.

Figure 5. Methylation profiles can be harnessed to classify patients according to DAC response at diagnosis.

(A) Heatmap of 21 CpG tiles selected as the SVM classifier predictors. DAC-sensitive patients are indicated with the red bar and nonresponders with the blue bar. (B) Correspondence analysis (COA) using only the 21 CpG tiles included in the classifier could segregate the majority of the CMML cohort according to DAC response (responders are represented by red dots and nonresponders by blue dots).

Figure 4. DMRs are enriched at distal intergenic regions and enhancers.

(A) Pie charts illustrate the relative proportion of CpG tiles and DMRs annotated to RefSeq promoter, exonic, intronic, and intergenic regions. (B) Pie charts illustrate the relative proportion of CpG tiles and DMRs annotated to CpG islands, CpG shores, and regions beyond CpG shores. (C) Pie charts illustrate the relative proportion of CpG tiles and DMRs annotated to enhancers within gene bodies, enhancers within intergenic regions, and nonenhancer regions.

Figure 3. Baseline DNA methylation differences distinguish DAC responders and nonresponders at the time of diagnosis.

(A) Volcano plot illustrating methylation differences between 20 DAC-sensitive and 19 DAC-resistant patients. Mean methylation difference between the 2 groups is represented on the x axis and statistical significance (–log10P value) on the y axis. Beta-binomial test identified 167 DMRs, which are indicated by red dots (FDR <0.1 and absolute methylation difference ≥25%). (B) Hiearchical clustering of the patients using the 167 DMRs illustrates the power of these genomic regions in segregating the patients into nonresponder (blue) and responder (red) groups.

Figure 2. Distinct DNA methylation profiles are associated with recurrent somatic mutations in DNMT3A, TET2, ASXL1, and SRSF2.

Volcano plots illustrating the methylation differences between DNMT3A-mutant (n = 5) (A), TET2-mutant (n = 17) (B), ASXL1-mutant (n = 15) (C), or SRSF2-mutant (n = 21) (D) samples versus WT patients (n = 39 for the number of mutated samples). DMRs are indicated by red dots (beta-binomial test, FDR <0.1 and absolute methylation different ≥25%). Pie charts illustrate the relative proportion of CpG tiles and DMRs annotated to the RefSeq promoter, exonic, intronic, and intergenic regions.

Figure 1. Somatic mutations in CMML do not correlate with DAC response or specific epigenetic clusters.

Mutational status of a panel of 15 genes frequently mutated in CMML according to (A) therapeutic response to DAC or (B) DNA methylation hierarchical clustering.