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Optimizing hypomethylating agents in myelodysplastic syndromes

Authors: Raphael, Itzykson; Pierre, Fenaux;

Optimizing hypomethylating agents in myelodysplastic syndromes

Abstract

Hypomethylating agents (HMAs) improve the outcome of higher-risk myelodysplastic syndromes (MDS) and provide multilineage response in lower-risk patients but their results must be optimized, especially as the poor outcome of patients after HMA failure is now established.Current efforts include evaluation of novel outpatient administration schedules and routes, improving compliance and drug exposure to reach continuous hypomethylation. Novel combination strategies are emerging, with histone deacetylase inhibitors or immunomodulatory compounds, but none has proven superior to HMA single-agent therapy so far. Improved understanding of the epigenetic deregulation of MDS and of HMA's mode of action has allowed putative biomarkers to emerge, including multiple gene methylation patterns, and gene mutations, notably TET2 mutations. As HMAs may elicit antileukemic immune responses, they are also being evaluated in patients eligible for allogeneic stem cell transplantation.The indication and practical use of HMAs in MDS so far remain those of phase III registration studies, but will hopefully be modified with future results of ongoing clinical and translational research.

Keywords

Antimetabolites, Antineoplastic, DNA Methylation, Decitabine, Drug Administration Schedule, Epigenesis, Genetic, Histone Deacetylase Inhibitors, Immunomodulation, Myelodysplastic Syndromes, Antineoplastic Combined Chemotherapy Protocols, Azacitidine, Humans, Patient Compliance, Treatment Failure

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Average
Top 10%
Top 10%
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