Kinase-Activating Fusions in Pediatric High-Risk B-Lineage Acute Lymphoblastic Leukemia (ALL): a Report from the Dana-Farber Cancer Institute (DFCI) ALL Consortium
Notice bibliographique
Résumé
Abstract Background. Recurrent chromosomal rearrangements carry prognostic significance in pediatric B-lineage acute lymphoblastic leukemia (B-ALL). Recent genome-wide analyses identified a diverse spectrum of chromosomal rearrangements resulting in novel chimeric fusions associated with poor prognosis when treated with conventional chemotherapy. These fusions are observed more frequently in NCI High-Risk (HR) B-ALL compared with NCI Standard Risk (SR) patients. They often activate ABL and JAK-STAT signaling pathways and have demonstrated sensitivity to the relevant tyrosine kinase inhibitors (TKIs) in in vitro assays and ex vivomodels. The objective of this study was to determine the frequency of NCI HR B-ALL patients enrolled on DFCI ALL Consortium Protocol 05-001 with a kinase-activating fusion that would be amenable to TKI therapy and to describe their associated clinical characteristics and outcomes. Methods. Between 2005-2011, 219 NCI HR, Philadelphia chromosome (Ph)-negative, B-ALL patients were enrolled on DFCI ALL Consortium Protocol 05-001, 105 of whom had sufficient material to undergo kinase fusion testing by validated multiplex reverse transcription polymerase chain reaction (RT-PCR) assays. A total of 35 kinase fusions of ABL-class (ABL1, ABL2, PDGFRB, CSF1R), JAK2 and CRLF2 rearrangements were examined. IGH@-CRLF2 and EPOR rearrangements were not assessed. Fusion products were predicted by NCBI BLAST algorithms, confirmed by singleplex PCR and Sanger sequencing and aligned using CLC Main Workbench Version 7.6.1. IKZF1 deletion (del) status had previously been assessed by multiplex ligation-dependent probe amplification (MLPA). Fisher's exact test and the Wilcoxon rank sum test were used to compare patient characteristics to those with and without any identified fusion for categorical and continuous variables respectively. Event-free survival (EFS) and overall survival (OS) were estimated with the Kaplan-Meier method and compared using a log rank test. Univariate and multivariable Cox proportional hazards models of EFS were constructed. Results. Among 105 NCI HR, Ph-negative, B-ALL patients, 16 (15%) were found to harbor an ABL-class fusion (ETV6-ABL1: n=1; FOXP1-ABL1: n=1; SFPQ-ABL1: n=1; ZC3HAV1-ABL2: n=1) or a fusion activating the JAK-STAT pathway (P2RY8-CRLF2: n=8; PAX5-JAK2: n=4). Sixty-nine percent of patients with an identified fusion (Fusion +) had a concomitant IKZF1 del (n=11). Features associated with fusion-positivity were age of 10 years or older (p=0.003), male sex (p=0.03), Hispanic ethnicity (p=0.01) and IKZF1 del (p=0.0005) (Table 1). Fifty percent of Fusion+ patients experienced an event (induction death (n=1); induction failure (n=1); or relapse (n=6)) compared to 24% of patients without a fusion. The 5-year EFS and OS were 48% (95% CI 22-70%) and 68% (95% CI 39-85%) for Fusion+ patients compared to 78% (95% CI 67-85%) and 88% (95% CI 79-93%) for those without fusions (Figure 1). In univariate analysis, fusion-positivity (HR: 2.66, p=0.02) and IKZF1 del (HR: 3.21; p=0.0018) were each significantly associated with inferior EFS, while age and presenting leukocyte count were not. In multivariable analysis, IKZF1 del, but not fusion-positivity, retained statistical significance (HR: 2.64, p=0.02). Conclusion. Fifteen percent of NCI HR, Ph-negative, B-ALL patients enrolled on DFCI ALL Consortium 05-001 were found to have a kinase-activating fusion. Fusion+ patients frequently harbored concomitant IKZF1 deletion and had an inferior outcome. Future studies should focus on developing clinical strategies to rapidly identify these patients at diagnosis and to test whether the addition of the relevant TKIs to their treatment will improve their outcome. Disclosures Asselin: Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Sigma Tau Pharamceuticals: Consultancy. Loh:Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding.
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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».