Genomic Landscape of Pediatric Mixed Phenotype Acute Leukemia
Notice bibliographique
Résumé
Abstract Background: Mixed phenotype acute leukemia (MPAL) is a high risk leukemia with features of acute myeloid (AML) and acute lymphoblastic leukemia (ALL), either due to co-expression of antigens of multiple lineages, or the presence of multiple immunophenotypically distinct populations. WHO 2008 classifies MPAL as T/myeloid (T/M), B/myeloid (B/M), MLL rearranged (MLL) MPAL, BCR-ABL1 (Ph+) MPAL, and MPAL not otherwise specified (NOS). Patients are managed with divergent chemotherapeutic approaches with survival estimates of 50-70%. Apart from Ph+ and MLL rearrangement, the genetic basis of MPAL is poorly defined. Our goal was to define the molecular basis of MPAL, and to compare with potentially related forms of leukemia (AML, T-ALL and early T-cell precursor (ETP) ALL) as a rational foundation for future trials. Furthermore, we examined whether multi-lineal cases harbor genetically distinct subclones, or arise from the acquisition of founding alterations in a multi-lineage hematopoietic progenitor. Methods: 155 cases of pediatric leukemia initially diagnosed as MPAL were studied by central pathology review and/or central flow cytometry (134 cases), confirming the diagnosis according to WHO criteria in 115 cases (fig. 1). Median age was 7 years (0-18) with 52 T/M, 37 B/M, 15 MLL, 8 NOS, and 2 Ph+ (fig. 2). Samples were studied by whole genome and/or exome, RNA sequencing, and SNP array analysis. 44 multi-lineal samples were flow sorted into 2-4 lymphoid, myeloid, and ambiguous subpopulations (15 T/M, 19 B/M, 7 MLL, 1 Ph+, 2 NOS) and subjected to exome sequencing and SNP array. Mutational data were compared to data from 196 AML, 39 ETP-ALL, and 245 T-ALL cases. Results: We identified 35 recurrently mutated genes, the most common of which were WT1 (21%), FLT3 (18%), NRAS (16%), JAK3 (11%), RUNX1 (11%), KMT2D (9%), PTPN11 (9%), ASXL1 (7%), and CREBBP (7%). T/M and B/M subtypes are characterized by distinct patterns of genomic alteration. 48% of T/M cases harbored in-frame chimeric fusion, several of which are described in T-ALL, including ETV6-NCOA2 and ZEB2-BCL11B, NUP214-ABL1 and PICALM-MLLT10, and novel fusions involving hematopoietic regulators (e.g. ETV6-MAML and MNX1-IKZF1). 42% of B/M cases had in-frame fusions of ZNF384 with CREBBP, EP300, and TCF3, while we also identified isolated fusions involving ERG and NF1. Mutations of Ras signaling genes were present in 50% of B/M cases, in contrast to 10% of T/M cases. Epigenetic modifying genes, including CREBBP, SETD2, KMT2D, EZH2 and SUZ12 were mutated in 45% of the combined T/M and B/M cohorts. Cases with MLL gene rearrangements had few sequence alterations. In comparison to other subtypes of leukemia, the mutational spectrum of T/M MPAL, with alterations in transcription factors (60% cases), epigenetic genes (50%) and JAK-STAT signaling (35%) was more similar to ETP-ALL (64%, 72%, 44%) and T-ALL (49%, 60%, 21%) than to AML (19%, 21%, 11%). Similarly, B/M cases have increased alterations in these pathways (42%, 42%, 25%) compared to AML. Sequencing of MPAL subpopulations revealed that 27% of cases had the same SNVs/indels in each subpopulation, and 47% of cases had at least two-thirds of mutations present in each subpopulation. All multi-lineal cases with alterations of regulators WT1 and RUNX1 showed similar allele frequencies of these mutations in all populations. Alternatively, cases with mutations in signaling (FLT3, NRAS, KRAS, PTPN11) or epigenetic regulatory genes (CREBBP, KMT2D, SETD2) only showed consistent presence of alterations across each subpopulation in 60% of the cases. Conclusions: Our analysis has shown that T/M and B/M MPAL are distinct subtypes of leukemia. B/M MPAL is characterized by frequent RAS pathway mutations and ZNF384 fusions with multiple different fusion partners, suggesting that this gene plays a critical role in hematopoietic development for progenitor cells with B lymphoid and myeloid potential. The findings of mutational similarity to ETP ALL, and sharing of genomic lesions between subclones in the majority of cases strongly suggests that MPAL represents part of a spectrum of immature leukemias that arise in a hematopoietic progenitors that may propagate multiple immunophenotypic populations. These results will guide the design of therapeutic strategies for each subtype of MPAL and ETP ALL, and xenografts representative of each subtype are being used to examine sensitivity to therapeutic agents. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Loh: Abbvie: Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Zwaan:Pfizer: Research Funding; Pfizer: Consultancy. Reinhardt:Pfizer: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Other: Travel Accomodation. Inaba:Arog: Research Funding. Mullighan:Loxo Oncology: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees; Amgen: Speakers Bureau.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».