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Acute myeloid leukemia with biallelic mutation of CEBPA (CEBPA-dm AML) is a distinct good prognosis entity recognized by WHO 2016 classification. However, testing for CEBPA mutation is challenging, due to the intrinsic characteristics of the mutation itself. Indeed, molecular analysis cannot be performed with NGS technique and requires Sanger sequencing. The association of recurrent mutations or translocations with specific immunophenotypic patterns has been already reported in other AML subtypes. The aim of this study was the development of a specific cytofluorimetric score (CEBPA-dm score), in order to distinguish patients who are unlikely to harbor the mutation. To this end, the correlation of CEBPA-dm score with the presence of the mutation was analyzed in 50 consecutive AML patients with normal karyotype and without NPM1 mutation (that is mutually exclusive with CEBPA mutation). One point each was assigned for expression of HLA DR, CD7, CD13, CD15, CD33, CD34 and one point for lack of expression of CD14. OS was not influenced by sex, age and CEBPA-dm score. Multivariate OS analysis showed that CEBPA-dm (p 0.02) and FLT3-ITD (p 0.01) were the strongest independent predictors of OS. With a high negative predictive value (100%), CEBPA-dm score6 was able to identify patients who are unlikely to have the mutation. Therefore, the application of this simple score might optimize the use of expensive and time-consuming diagnostic and prognostic assessment in the baseline work up of AML patients.

Acute myeloid leukemia (AML) is the most common form of acute leukemia affecting adults. Although it is a complex disease driven by numerous genetic and epigenetic abnormalities, nearly 50% of patients exhibit a normal karyotype (CN-AML) with an intermediate cytogenetic risk. However, a widespread genomic analysis has recently shown the recurrence of genomic aberrations in this category (mutations of FLT3, CEBPA, NPM1, RUNX1, TET2, IDH1/2, DNMT3A, ASXL1, MLL and WT1) thus revealing its marked genomic heterogeneity. In this perspective, a global gene expression analysis of AML patients provides an independent prognostic marker to categorize each patient into clinic-pathologic subgroups based on its molecular genetic defects. Consistently such classification, taking into account the uniqueness of each AML patient, furnishes an individualized treatment approach leading a step closer to personalized medicine. Overall the genome-wide analysis of AML patients, by providing novel insights into biology of this tumor, furnishes accurate prognostic markers as well as useful tools for selecting the most appropriate treatment option. Moreover it provides novel therapeutic targets useful to enhance efficacy of the current anti-AML therapeutics. Here we describe the prognostic relevance of such new genetic data and discuss how this approach can be used to improve survival and treatment of AML patients.

Background Myelodysplastic syndromes (MDS) are a heterogeneous group of clonal disorders, with very different prognosis in given individuals; age and comorbidities are emerging as relevant patient-related factors influencing clinical outcome in MDS. Our aim was to evaluate the impact of age, comorbidities and disease severity (IPSS and IPSS-R prognostic scores) in a “real-life” series of MDS patients. Methods 318 patients with available assessment of comorbidities at diagnosis and consecutively registered into the Registro Ligure delle Mielodisplasie were analyzed. Comorbidities were evaluated according to HCT-CI and MDS-CI comorbidity indexes. Overall survival (OS) and the probability of death among patients who did not develop acute myeloid leukemia (NLD cumulative incidence) were analyzed. Results Comorbidities were seen in 177 (55.7%) patients. An older age (>75 y) had a significant negative impact on OS (p = 0.008). HCT-CI was not associated with OS. MDS-CI was of prognostic significance (p = 0.001), but the association was limited to pts with IPSS or IPSS-R “lower-risk”. In multivariate analysis, MDS-CI remained an independent factor associated with OS and with an increased risk of NLD both when controlling for IPSS (p = 0.019 and p = 0.001, respectively) and for IPSS-R (p = 0.048 and p = 0.002, respectively). Conclusions Evaluation of age and comorbidities according to a tailored tool such is MDS-CI helps to predict survival in patients with MDS and should be incorporated to current prognostic scores.

Several genes with relevant pathogenetic and prognostic value have been identified in patients with myelodysplastic syndromes. Overexpression of WT1 at diagnosis has been associated with increased progression to acute myeloid leukemia and reduced leukemia free survival. Conversely, few data are available on the prognostic value of BAALC gene overexpression in AML and MDS patients. We evaluated the prognostic value of the combined expression of WT1 and BAALC genes at diagnosis in 86 MDS patients who had been stratified according to IPSS and R-IPSS scoring systems. Our results suggest that in the whole group of patients, low levels of both WT1 and BAALC were associated with a favorable outcome (3-year LFS 74.5%, median not reached), whereas patients presenting high expression levels of both genes had the worst prognosis (3-year LFS 0%, median 12 months, p0.001). More specifically, molecular profiling was especially useful for intermediate 1 and intermediate-2/high risk groups. This study suggests that evaluating WT1 and BAALC gene expression at diagnosis may improve standard risk stratification and possibly refine the therapeutic approach for MDS patients.