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Although CEBPA double-mutated (CEBPADM) acute myeloid leukemia is considered to be a favorable-risk disease, relapse remains a major cause of treatment failure. Most CEBPADM patients have a classic biallelic mutant combination with an N-terminal mutation leading to production of p30 protein plus a C-terminal loss-of-function in-frame indel mutation (CEBPAClassic-DM), but approximately one-third of cases have one or more non-classic mutations, with diverse combinations reported, and there is little information on the consequences of such mutants. We evaluated outcome in a cohort of 104 CEBPADM patients, 79 CEBPAClassic-DM and 25 with non-classic mutants, and found that the latter may have poorer survival (5-year overall survival 64% vs. 46%; P=0.05), particularly post relapse (41% vs. 0%; P=0.02). However, for this analysis, all non-classic cases were grouped together, irrespective of mutant combination. As CEBPADM cases have been reported to be hypermethylated, we used methylation profiling to assess whether this could segregate the different mutants. We developed a CEBPAClassic-DM methylation signature from a preliminary cohort of 10 CEBPADM (including 8 CEBPAClassic-DM) and 30 CEBPA wild-type (CEBPAWT) samples, and independently validated the signature in 17 CEBPAClassic-DM cases. Assessment of the signature in 16 CEBPADM cases with different non-classic mutant combinations showed that only 31% had a methylation profile equivalent to CEBPAClassic-DM whereas for 69% the profile was either intermediate between CEBPAClassic-DM and CEBPAWT or equivalent to CEBPAWT These results suggest that CEBPADM cases with non-classic mutants may be functionally different from those with CEBPAClassic-DM mutants, and should not automatically be included in the same prognostic group. (AML12 is registered under ISRCTN17833622 and AML15 under ISRCTN17161961).

Original publication




Journal article



Publication Date





91 - 100


Adult, Biomarkers, Tumor, CCAAT-Enhancer-Binding Proteins, DNA Methylation, Follow-Up Studies, Gene Expression Profiling, Humans, Leukemia, Myeloid, Acute, Middle Aged, Mutation, Prognosis, Survival Analysis, Transcriptome