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Enregistrement W4404637258 · doi:10.1002/jha2.1055

Impact of secondary‐type mutations in acute myeloid leukemia with CEBPA mutation

2024· article· en· W4404637258 sur OpenAlexaff
Davidson Zhao, Musani Rumina, Mojgan Zarif, Cuihong Wei, Hong Chang

Notice bibliographique

RevueeJHaem · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity of TorontoUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésCEBPANPM1Myeloid leukemiaMutationOncologyCancer researchMedicineLeukemiaGene mutationBiologyGeneticsInternal medicineGeneKaryotype

Résumé

récupéré en direct d'OpenAlex

To the Editor, Secondary-type mutations (STM: ASXL1, BCOR, EZH2, SF3B1, SRSF2, STAG2, U2AF1, and ZRSR2) in acute myeloid leukemia (AML) were reported to be highly specific for secondary disease and associated with inferior event-free survival (EFS) [1, 2]. In light of these findings, the newly-revised 5th edition of the WHO Classification of Haematolymphoid Tumours (WHO-HAEM5) includes STM in the criteria defining AML, myelodysplasia-related (AML-MR) [3]. In the newly-published International Consensus of Classification of myeloid neoplasms and acute leukemia (ICC), RUNX1 mutation together with STM as described by WHO-HAEM5 define the entity of AML with myelodysplasia-related gene mutations [4]. To date, several studies have examined the impact of STM in other molecularly defined entities of AML such as NPM1+ AML [5-9]. However, the impact of STM in AML with CEBPA mutation has not been studied extensively and remains unclear. Thus, we sought to investigate the clinical impact of STM in AML with CEBPA mutation. We conducted a retrospective analysis with a single center cohort of 38 cases of AML with CEBPA mutation diagnosed at our institution from 2015 to 2024. Patients were included if they met WHO-HAEM5 criteria of blasts ≥ 20% and either biallelic CEBPA mutation or single CEBPA mutation in the basic leucine zipper (bZIP) domain. Cytogenetic testing, molecular genetic testing, and variant calling in next-generation sequencing were performed according to previously described procedures [10]. Gene panel for targeted sequencing and exon coverage for hotspot genes are listed in Tables S1 and S2. The baseline clinicopathological characteristics and co-mutation landscape of the study cohort are summarized in Table 1 and Figure 1A. Of the 38 patients with AML with CEBPA mutation, 11 (29%) had STM. SRSF2 and STAG2 were the most common STMs (both 8/38, 21%), followed by ASXL1 (6/38, 16%), BCOR (2/38, 5%), and U2AF1 (1/38, 3%). RUNX1 mutations were found in two (5%) patients, both of whom had concurrent WHO-HAEM5-defined STMs. EZH2, ZRSR2, and SF3B1 mutations were not detected. The most common recurrent (>10%) co-mutated genes in the cohort were TET2 (10/38; 26%), GATA2 (9/38, 24%), WT1 (8/38, 21%), NRAS (6/38, 16%) and FLT3-ITD (4/38, 11%). Compared to patients without STM, patients with STM were older, had less proliferative disease, had lower hemoglobin levels, and had significantly lower variant allele frequency of mutant CEBPA and infrequent in-frame bZIP CEBPA mutation. Consistent with the older age of the STM+ group, only five (46%) patients received intensive chemotherapy compared to all 27 (100%) patients in the STM-ve group. Of note, complete remission rates after intensive induction therapy in patients with or without STM did not significantly differ. The transplant rate was higher in patients without STM but did not reach statistical significance. In the overall cohort, patients with STM had inferior 2-year overall survival (OS) (18% vs. 96%; p < 0.001) and EFS (18% vs. 88%; p < 0.001) (Figure 1B,C). In the intensively treated subgroup, STM remained a predictor for inferior 2-year OS (40% vs. 96%, p < 0.001) and EFS (40% vs. 88%; p = 0.013) (data not shown). We previously reported that STM had limited prognostic value in patients with NPM1+ AML [6]. Here, we show using a single-center cohort that AML with CEBPA mutations with concurrent STM is associated with distinct clinicopathological features and inferior outcome. To the best of our knowledge, this is the first study to evaluate the implications of concurrent STM and CEBPA mutations in disease classification. In 2022, the new WHO-HAEM5 classification revised the definition of AML with CEBPA mutation to include biallelic as well as single mutations located in the bZIP domain [3]. In contrast, the ICC only recognizes a subset of those mutations (i.e. in-frame bZIP mutation) to be disease defining [4]. In our cohort, 12 (32%) patients did not meet diagnostic criteria to be included in the ICC group of AML with in-frame bZIP CEBPA mutations. Importantly, STM was enriched in patients who were excluded from the ICC group (10/12, 83% vs. 1/26, 4%; p < 0.001). This suggests that the ICC is superior to WHO-HAEM5 at excluding CEBPA-mut AML patients who have distinct clinicopathological features and who may be more appropriately classified otherwise as AML-MR. Our data indicates an adverse prognostic impact of STM in CEBPA-mut AML patients. However, this finding may be confounded by the negative association between STM and in-frame bZIP CEBPA mutations which have been shown to confer favorable outcomes and which have been included in ELN classification of AML as a favorable genetic factor [11-13]. The current study is a single-center study with a limited sample size, and it was not powered to perform multivariable analysis to identify whether STM remained an independent predictor of inferior outcomes. Future prospective studies with larger cohorts are needed to confirm whether STM or in-frame bZIP mutations confer prognostic significance in AML patients with concurrent STM and CEBPA mutations. In conclusion, our data indicates that patients in the WHO-HAEM5 defined group of AML with CEBPA mutation with concurrent STM may be more appropriately classified as AML-MR. Classification according to ICC, which only selects for in-frame bZIP CEBPA mutations, identifies a homogenous cohort without STM and is effective at excluding patients who may be otherwise better classified as AML-MR. Davidson Zhao collected and analyzed the data and wrote the manuscript. Musani Rumina collected data and wrote the manuscript. Mojgan Zarif and Cuihong Wei collected data. Hong Chang designed the study and analyzed the data. All authors read, critically reviewed, and approved the manuscript. The authors thank the clinicians, nurses, and allied health professionals for their dedication to patients with leukemia at the University Health Network/Princess Margaret Cancer Centre. The authors declare no conflict of interest. The authors have confirmed ethical approval statement is not needed for this submission. The authors have confirmed patient consent statement is not needed for this submission. The authors have confirmed clinical trial registration is not needed for this submission. Data is available upon reasonable request. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,770
Score d'incertitude au seuil0,783

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,335
Écart entre enseignants0,318 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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