Relationship between comorbidities, mutational profile, and outcome after intensive chemotherapy in patients older than 60 years with acute myeloid leukemia: Assessment of different risk scores.

The aim of this study was to evaluate how comorbidities and molecular landscape relate to outcome in patients with acute myeloid leukemia (AML) aged 60 years or older who received intensive induction therapy. In 91 patients, 323 mutations were identified in 77 genes by next-generation sequencing, with a median of four mutations per patient, with NPM1, FLT3, TET2, and DNMT3A being the most frequently mutated genes. A multistate model identified FLT3, IDH2, RUNX1, and TET2 mutations as associated with a higher likelihood of achieving complete remission while STAG2 mutations were associated with primary refractory disease, and DNMT3A, FLT3, IDH2, and TP53 mutations with mortality after relapse. Ferrara unfitness criteria and performance status were the best predictors of short-term outcome (area under the curve = 82 for 2-month survival for both parameters), whereas genomic classifications better predicted long-term outcome, with the Patel risk stratification performing the best over the 5-year follow-up period (C-index = 0.63 for event-free and overall survival). We show that most genomic prognostic classifications, mainly used in younger patients, are useful for classifying older patients, but to a lesser extent, because of different mutational profiles. Specific prognostic classifications, incorporating performance status, comorbidities, and cytogenetic/molecular data, should be specifically designed for patients over 60 years.

WT1 gene is overexpressed in myeloproliferative neoplasms, especially in myelofibrosis.

Classical Philadelphia-negative myeloproliferative neoplasms include Polycythemia Vera (PV), Essential Thrombocythemia (ET) and Primary Myelofibrosis (PMF). They are characterized by the presence of driver mutations of JAK2, CALR or MPL genes. Overexpression of WT1 is used as a marker of minimal residual disease in acute myeloid leukemia, especially after allogeneic stem cell transplantation (SCT). We investigated WT1 expression at diagnosis in 152 MPN patients and showed that the WT1 transcript was overexpressed in PMFs and PVs compared to controls. In particular, WT1 transcript levels were higher in PMF than in ET and PV. WT1 transcript levels were significantly increased during myelofibrotic transformation of ET or PV. Using multivariate linear regression, high WT1 transcript levels in PMF were associated with age over 65, splenomegaly and thrombocytopenia. The ROC curve analysis showed that a level of WT1 transcript >10 WT1 copies/104ABL1 enabled the diagnosis of PMF with a specificity of 95.8% (PMF vs ET; ROC AUC = 0.91). In myelofibrosis, studying follow-ups of WT1 transcript showed that this marker is of interest after allogeneic SCT. These results demonstrate that WT1 overexpression is a simple marker of myelofibrosis in MPN and could be used during patient follow-up.

Donor cell-derived acute promyelocytic leukemia after allogeneic hematopoietic stem cell transplantation.

Donor cell leukemia (DCL) is an infrequent complication after allogeneic hematopoietic stem cell transplantation (HSCT). Its true incidence is difficult to assess, although improvements in chimerism studies contributed to a better diagnosis of DCL. We report two rare cases of donor cell-derived acute promyelocytic leukemia (APL). To our knowledge, only two cases have been described in the literature. Here, we report one male and one female patients with acute myeloid leukemia (AML), who developed an APL in donor cells after HSCT. The latency between HSCT and DCL was 279 and 43 months, respectively. Fluorescent in situ hybridation and chimerism monitoring analysis proved the donor origin of APL. Surprisingly, donor lymphocyte infusion provided a hematological response during 19 months in the female patient. The mechanisms associated with pathogenesis of DCL are unclear and seem to be multifactorial. Increasing worldwide allogeneic hematopoietic stem cell transplantation activity and potentially the age of donor could explain the increasing incidence of DCL in the future. It is highlighted that long-term follow up of recipients will allow to report all cases of DCL, to clarify the genetic landscape and factors which contribute to DCL, to understand the response to DLI.

Distinction between clonal and paraclonal cutaneous involvements in VEXAS syndrome.

VEXAS (vacuoles, E1 enzyme, X-linked, auto-inflammatory, somatic) syndrome is an inflammatory disorder with hematological and systemic features. A recent study demonstrated that the dermal infiltrate in neutrophilic dermatosis from VEXAS patients is derived from the pathological UBA1-mutated myeloid clone. Neutrophilic dermatosis is, however, only one of the various skin involvements observed in VEXAS syndrome. We analyzed 10 formalin-fixed paraffin-embedded skin biopsies from genetically confirmed VEXAS syndrome. UBA1 mutation was found in the biopsies related to neutrophilic dermatitis but in none of the other histological patterns (leukocytoclastic vasculitis and septal panniculitis). This could lead to a distinction between clonal and paraclonal cutaneous involvements in VEXAS syndrome, which could in turn improve therapeutic outcomes.

Quantitative chimerism in CD3-negative mononuclear cells predicts prognosis in acute myeloid leukemia patients after hematopoietic stem cell transplantation.

Relapse is a major complication of acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation (SCT). The objective of our study was to evaluate chimerism monitoring on the CD3-negative mononuclear cells by RQ-PCR to predict relapse of patients allografted for AML and to compare its performance with WT1 quantification. A cohort of 100 patients undergoing allogenic SCT for AML was retrospectively analyzed in a single institution. Patients without complete chimerism, defined as less than 0.01% of recipient's DNA in CD3-negative cells, had a significantly higher risk of relapse and a lower overall survival (p < 0.001). An increase in the percentage of recipient DNA in CD3-negative cells was associated with an increased risk of relapse (p < 0.001) but not with overall survival. Comparable performances between monitoring of CD3-negative cell chimerism and WT1 expression to predict relapse was observed up to more than 90 days before hematological relapse, with sensitivity of 82% and 78%, respectively, and specificity of 100% for both approaches. Quantitative specific chimerism of the CD3-negative mononuclear fraction, enriched in blastic cells, is a new and powerful tool for monitoring measurable residual disease and could be used for AML patients without available molecular markers.

Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples.

BACKGROUND: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. METHODS: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n = 101) and/or poor quality control criteria (n = 10) (test set). RESULTS: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. CONCLUSION: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion.