Specific molecular signatures predict decitabine response in chronic myelomonocytic leukemia. Academic Article uri icon

Overview

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.

publication date

  • March 30, 2015

Research

keywords

  • Antimetabolites, Antineoplastic
  • Azacitidine
  • Drug Resistance, Neoplasm
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Genes, Neoplasm
  • Leukemia, Myelomonocytic, Chronic

Identity

PubMed Central ID

  • PMC4611703

Scopus Document Identifier

  • 84928982643

Digital Object Identifier (DOI)

  • 10.1093/bioinformatics/btp616

PubMed ID

  • 25822018

Additional Document Info

volume

  • 125

issue

  • 5