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Diffuse paediatric-type high-grade glioma, H3-wildtype and IDH-wildtype (H3/IDH-wt-pHGG) is a newly defined entity amongst brain tumours, primarily reported in children. It is a rare, ill-defined type of tumour and the only method to diagnose it is DNA methylation profiling. The case we report here carries new knowledge about this tumour which may, in fact, occur in elderly patients, be devoid of evocative genomic abnormalities reported in children and harbour a misleading mutation.
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Neoplasias Encefálicas , Glioma , Substância Branca , Idoso , Feminino , Humanos , Criança , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Genômica , Lobo Occipital/diagnóstico por imagemRESUMO
AIMS: The distinction between the benign subungual melanocytic lesions and an early lesion of subungual melanoma (SUM) remains a diagnostic challenge. We evaluated the routine diagnostic utility of array Comparative Genomic Hybridization (aCGH) to detect whole-genome copy number variations (CNV) as well as targeted next-generation sequencing (NGS) in SUM. METHODS AND RESULTS: This retrospective study included 20 cases of in situ SUM and 11 cases of invasive SUM. Analysis by aCGH detected common oncogene amplifications in all but one case of invasive SUM (n = 10) and in all cases of in situ SUM with a melanocyte count (MC) >45/mm (n = 4 true positive) and the average number of CNV was 8.5. Thirteen remaining cases of in situ SUM gave false negative results (n = 13), owing to a lack of sufficient melanocytes to analyse (median MC of 35.35; range: 10.16-39.5). Molecular analysis failed in four cases (three in situ SUM and one invasive SUM) due to insufficient amounts of DNA. Across the whole cohort, the sensitivity of aCGH was 52%, but when adjusting the cutoff to MC >45/mm, the sensitivity was 93%. Targeted NGS was less informative than aCGH analyses in our series of SUM. CONCLUSION: To distinguish malignant from benign lesions, especially in situ SUM versus atypical lentiginous melanocytic proliferations, aCGH analysis should be performed when the MC is above 45 melanocytes per linear millimetre. This pangenomic method can detect oncogene amplifications, as well as a number of CNV >3, which strongly support the diagnosis of malignancy.
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BACKGROUND OF THE STUDY: AML classification tools have been developed to stratify the risk at AML diagnosis. There is a need to evaluate these tools in the current therapeutic era. COHORT CHARACTERISTICS: In this retrospective study, we compared five classifiers: ELN 2017, ELN 2022, ALFA classifier, Papaemmanuil et al. classifier, and Lindsley et al. classifier, in a real-life cohort of 281 patients newly diagnosed for AML in Nice University Hospital. In our cohort median age was 68 years old, sex ratio was M/F 56%/44%, performance status was lower than 2 in 73.1% of patients, AML subtype was "De novo" in 71.5%, "secondary" in 22.4%, and "therapy-related" in 6.0% of patients. Intensive chemotherapy was used in 53.0% of patients, and non-intensive chemotherapy in 40.6% of patients. Molecular analysis was available in a large majority of patients and the main mutations found were NPM1 (22.7%), DNMT3A (17.4%), TP53 (13.1%), TET2 (12.4%), and FLT3-ITD (12.4%). RESULTS: In our findings, the comparison of overall survival between the three prognostic groups in the global cohort was statistically significant in all classifiers: ELN 2017 p < 0.0001, ELN 2022 p < 0.0001, ALFA classifier p < 0.0001, Papaemmanuil classifier p < 0.0001, Lindsley classifier p = 0.001. ELN 2017, ELN 2022, ALFA classifier, Papaemmanuil classifier, and Lindsley classifier were calculated respectively in 99%, 99%, 89%, 90%, and 89% of patients. CONCLUSIONS: Using Akaike's information criteria (AIC) to compare all five classifiers, ELN 2022 is the best classifier into younger and older patients and for prognosis.
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Leucemia Mieloide Aguda , Humanos , Idoso , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Nucleofosmina , Estudos Retrospectivos , Prognóstico , Mutação , Medição de RiscoRESUMO
Patients with Core-Binding Factor (CBF) and NPM1-mutated acute myeloid leukemia (AML) can be monitored by quantitative PCR after having achieved first complete remission (CR) to detect morphologic relapse and drive preemptive therapy. How to best manage these patients is unknown. We retrospectively analyzed 303 patients with CBF and NPM1-mutated AML, aged 18-60 years, without allogeneic hematopoietic cell transplantation (HCT) in first CR, with molecular monitoring after first-line intensive therapy. Among these patients, 153 (51%) never relapsed, 95 (31%) had molecular relapse (53 received preemptive therapy and 42 progressed to morphologic relapse at salvage therapy), and 55 (18%) had upfront morphologic relapse. Patients who received preemptive therapy had higher OS than those who received salvage therapy after having progressed from molecular to morphologic relapse and those with upfront morphologic relapse (three-year OS: 78% vs. 51% vs. 51%, respectively, P = 0.01). Preemptive therapy included upfront allogeneic HCT (n = 19), intensive chemotherapy (n = 21), and non-intensive therapy (n = 13; three-year OS: 92% vs. 79% vs. 58%, respectively, P = 0.09). Although not definitive due to the non-randomized allocation of patients to different treatment strategies at relapse, our study suggests that molecular monitoring should be considered during follow-up to start preemptive therapy before overt morphologic relapse.
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Mutations in spliceosome genes (SRSF2, SF3B1, U2AF1, ZRSR2) correlate with inferior outcomes in patients treated with intensive chemotherapy for Acute Myeloid Leukemia. However, their prognostic impact in patients treated with less intensive protocols is not well known. This study aimed to evaluate the impact of Spliceosome mutations in patients treated with Venetoclax and Azacitidine for newly diagnosed AML. 117 patients treated in 3 different hospitals were included in the analysis. 34 harbored a mutation in at least one of the spliceosome genes (splice-mut cohort). K/NRAS mutations were more frequent in the splice-mut cohort (47% vs 19%, p=0.0022). Response rates did not differ between splice-mut and splice-wt cohorts. With a median follow-up of 15 months, splice mutations were associated with a lower 18-month LFS (p=0.0045). When analyzing splice mutations separately, we found SRSF2 mutations to be associated with poorer outcomes (p=0.034 and p=0.037 for OS and LFS respectively). This negative prognostic impact remained true in our multivariate analysis. We believe this finding should warrant further studies aimed at overcoming this negative impact.