Contrasting requirements during disease evolution identify EZH2 as a therapeutic target in AML.
Faisal BasheerGeorge GiotopoulosEshwar MeduriHaiyang YunMilena MazanDaniel SascaPaolo GallipoliLudovica MarandoMalgorzata GozdeckaRyan J AsbyOlivia SheppardMonika DudekLars BullingerHartmut DöhnerRichard DillonSylvie FreemanOliver OttmannAlan BurnettNigel RussellElli PapaemmanuilRobert HillsPeter CampbellGeorge S VassiliouBrian James Patrick HuntlyPublished in: The Journal of experimental medicine (2019)
Epigenetic regulators, such as EZH2, are frequently mutated in cancer, and loss-of-function EZH2 mutations are common in myeloid malignancies. We have examined the importance of cellular context for Ezh2 loss during the evolution of acute myeloid leukemia (AML), where we observed stage-specific and diametrically opposite functions for Ezh2 at the early and late stages of disease. During disease maintenance, WT Ezh2 exerts an oncogenic function that may be therapeutically targeted. In contrast, Ezh2 acts as a tumor suppressor during AML induction. Transcriptional analysis explains this apparent paradox, demonstrating that loss of Ezh2 derepresses different expression programs during disease induction and maintenance. During disease induction, Ezh2 loss derepresses a subset of bivalent promoters that resolve toward gene activation, inducing a feto-oncogenic program that includes genes such as Plag1, whose overexpression phenocopies Ezh2 loss to accelerate AML induction in mouse models. Our data highlight the importance of cellular context and disease phase for the function of Ezh2 and its potential therapeutic implications.
Keyphrases
- acute myeloid leukemia
- long noncoding rna
- long non coding rna
- transcription factor
- allogeneic hematopoietic stem cell transplantation
- poor prognosis
- gene expression
- cell proliferation
- immune response
- mouse model
- magnetic resonance
- bone marrow
- dna methylation
- computed tomography
- copy number
- dendritic cells
- quality improvement
- young adults
- electronic health record
- cancer therapy
- binding protein
- artificial intelligence