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Background Gene fusions define leukemia subtypes, predicting prognosis and guiding treatment. The classical t(8;21)(q22;q22) translocation results in the RUNX1::RUNX1T1 fusion, characteristic of favorable risk acute myeloid leukemia (AML). To date, more than 21 genes have been identified as partners of RUNX1 , each associated with a distinct impact on behavior and outcome. Traditional cytogenetic and molecular techniques often fail to detect cryptic or complex rearrangements, resulting in suboptimal risk assessment. This is a relapsed case of t(8;21) AML involving the rare partner gene PLAG1 , identified by optical genome mapping. A review of published cases highlights the distinct prognosis of this fusion.  Case presentation A 71-year-old female previously diagnosed with AML, developed a cytogenetic clone with t(8;21)(q?12–13;q22) at relapse. FISH showed RUNX1 rearrangement, without RUNX1T1 involvement. RT-MLPA and Next Generation Sequencing showed KMT2A partial tandem duplication and pathogenic variants in ASXL1 , PHF6 , RUNX1 and SF3B1 . Customized FISH probes identified the breakpoint within the region spanning PLAG1 , confirmed as a translocation partner by OGM. The patient showed disease refractoriness despite multiple lines of chemotherapy and died 17 months after diagnosis. Discussion and conclusions PLAG1 is a rare translocation partner of RUNX1 in AML, mistaken for classical t(8;21) on conventional karyotyping. The rare reported cases of PLAG1::RUNX1 suggest a distinctly poor prognosis, highlighting the importance of accurate diagnosis and the role of OGM in our practice.

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.

Classifications of acute myeloid leukemia (AML) patients rely on morphologic, cytogenetic, and molecular features. Here we have established a novel flow cytometry-based immunophenotypic stratification showing that AML blasts are blocked at specific stages of differentiation where features of normal myelopoiesis are preserved. Six stages of leukemia differentiation-arrest categories based on CD34, CD117, CD13, CD33, MPO, and HLA-DR expression were identified in two independent cohorts of 2087 and 1209 AML patients. Hematopoietic stem cell/multipotent progenitor-like AMLs display low proliferation rate, inv(3) or RUNX1 mutations, and high leukemic stem cell frequency as well as poor outcome, whereas granulocyte–monocyte progenitor-like AMLs have CEBPA mutations, RUNX1-RUNX1T1 or CBFB-MYH11 translocations, lower leukemic stem cell frequency, higher chemosensitivity, and better outcome. NPM1 mutations correlate with most mature stages of leukemia arrest together with TET2 or IDH mutations in granulocyte progenitors-like AML or with DNMT3A mutations in monocyte progenitors-like AML. Overall, we demonstrate that AML is arrested at specific stages of myeloid differentiation (SLA classification) that significantly correlate with AML genetic lesions, clinical presentation, stem cell properties, chemosensitivity, response to therapy, and outcome.

Acute myeloid leukemia (AML) with t(9;22) (q34.1; q11.2)/ BCR::ABL1 , a distinct entity within the group of AML with defining genetic abnormalities, belong to the adverse-risk group of the 2022 ELN classification. However, there is little data on outcome since the era of tyrosine kinase inhibitors. Among 5819 AML cases included in the DATAML registry, 20 patients with de novo BCR::ABL1 + AML (0.3%) were identified. Eighteen patients treated with standard induction chemotherapy were analyzed in this study. Imatinib was added to chemotherapy in 16 patients. The female-to-male ratio was 1.25 and median age was 54 years. The t(9;22) translocation was the sole chromosomal abnormality in 12 patients. Main gene mutations detected by NGS were ASXL1 , RUNX1 and NPM1 . Compared with patients with myeloid blast phase of chronic myeloid leukemia (CML-BP), de novo BCR::ABL1 + AML had higher WBC, fewer additional chromosomal abnormalities, lower CD36 or CD7 expression and no ABL1 mutations. Seventeen patients (94.4%) achieved complete remission (CR) or CR with incomplete hematologic recovery. Twelve patients were allografted in first remission. With a median follow-up of 6.3 years, the median OS was not reached and 2-year OS was 77% (95% CI: 50–91). Four out of five patients who were not transplanted did not relapse. Comparison of BCR::ABL1 + AML, CML-BP, 2017 ELN intermediate ( n  = 643) and adverse-risk patients ( n  = 863) showed that patients with BCR::ABL1 + AML had a significant better outcome than intermediate and adverse-risk patients. BCR::ABL1 + AML patients treated with imatinib and intensive chemotherapy should not be included in the adverse-risk group of current AML classifications.

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.

A recent phase 3 trial showed that outcome of older patients with secondary acute myeloid leukemia (AML) may be improved by a liposomal encapsulation of cytarabine and daunorubicin (CPX‐351). This phase 3 study represents a unique example of prospective data in this rare subgroup providing basis for comparison with real life data. Here, we retrospectively assessed characteristics and outcome of patients aged 60‐75 years with secondary or therapy‐related AML in real life. Out of 218 patients that fulfilled CPX‐351 study criteria, 181 patients (83.0%) received antileukemic treatment either intensive chemotherapy (n = 121) or hypomethylating agents (HMA, n = 60). As compared with patients treated by chemotherapy, HMA‐treated patients were older, had lower WBC, more often AML with antecedent myelodysplastic syndrome and adverse cytogenetic risk. In chemotherapy‐treated patients, the complete response rate was 69%, median overall survival (OS) was 11 months whereas 3‐year and 5‐year OS was 21% and 17%, respectively. In HMA‐treated patients, the complete response rate was 15%, median OS was 11 months whereas 3‐year and 5‐year OS was 15% and 2%, respectively. In conclusion, although outcome of older patients with high‐risk AML is very poor, a significant proportion of patients treated by standard intensive chemotherapy but not HMA are long‐term survivors. A recent phase 3 trial showed that outcome of older patients with secondary AML may be improved by CPX‐351. Here, we assessed characteristics and outcome of patients aged 60‐75 years with secondary or therapy‐related AML in real life. In chemotherapy‐treated patients, the complete response rate was 69%, median OS was 11 months whereas 3‐year and 5‐year OS was 21% and 17%, respectively. These results compared favorably with the control arm of the CPX‐351 trial.

Background Acute myeloid leukemia (AML) with myelodysplasia‐related characteristics is a heterogeneous subset of AML that has been challenged throughout the history of myeloid malignancies classifications, considered to have similar outcomes as intermediate‐ or adverse‐risk AML depending on the subgroup. However, little is known about the fate of these patients in refractory or relapsed situation (R/R) after first line therapy. Methods A large series of R/R AML patients, recorded in the French DATAML registry, have received either intensive chemotherapy (ICT), azacitidine (AZA) as single agent, or best supportive care (BSC). A cohort of 183 patients (median age 63‐year‐old) with what was called at the time AML‐MRC has been explored, and data are reported here. Results Patient status was refractory for 93, while 90 had relapsed. Respectively, 88, 34, and 61 were included in the three treatment arms. The median OS of the whole cohort was 4.2 months (95%CI: 3.1–5.6) with a mean 1‐year overall survival of 24% ± 3.2%. There was no significant survival difference between refractory and relapsed patients. The BSC group had overall a significantly worse outcome (p = 0.0001), and this remained true in both refractory (p = 0.01) and relapsed (p = 0.002) patients. Similar survivals were observed in both groups comparing ICT and AZA. Conclusions These data, reporting about an ill‐explored population, indicate the poor prognosis of this condition where both ICT and AZA can be proposed. The latter, which was demonstrated here to be a feasible option, should be added to new targeted therapies.

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.