Impact of TP53 mutations in acute myeloid leukemia patients treated with azacitidine.
Pierre BoriesNaïs PradeStéphanie LagardeBastien CabarrouLaetitia LargeaudJulien PlenecassagnesIsabelle LuquetVéronique De MasThomas FilleronManon CassouAudrey SarryLuc-Matthieu ForneckerCélestine SimandSarah BertoliChristian RecherEric DelabessePublished in: PloS one (2020)
Hypomethylating agents are a classical frontline low-intensity therapy for older patients with acute myeloid leukemia. Recently, TP53 gene mutations have been described as a potential predictive biomarker of better outcome in patients treated with a ten-day decitabine regimen., However, functional characteristics of TP53 mutant are heterogeneous, as reflected in multiple functional TP53 classifications and their impact in patients treated with azacitidine is less clear. We analyzed the therapeutic course and outcome of 279 patients treated with azacitidine between 2007 and 2016, prospectively enrolled in our regional healthcare network. By screening 224 of them, we detected TP53 mutations in 55 patients (24.6%), including 53 patients (96.4%) harboring high-risk cytogenetics. The identification of any TP53 mutation was associated with worse overall survival but not with response to azacitidine in the whole cohort and in the subgroup of patients with adverse karyotype. Stratification of patients according to three recent validated functional classifications did not allow the identification of TP53 mutated patients who could benefit from azacitidine. Systematic TP53 mutant classification will deserve further exploration in the setting of patients treated with conventional therapy and in the emerging field of therapies targeting TP53 pathway.
Keyphrases
- acute myeloid leukemia
- end stage renal disease
- healthcare
- ejection fraction
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- emergency department
- clinical trial
- physical activity
- randomized controlled trial
- risk assessment
- acute lymphoblastic leukemia
- bone marrow
- cell therapy
- bioinformatics analysis
- middle aged
- phase iii