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Enregistrement W3094788775 · doi:10.1182/blood-2020-136999

Venetoclax Alone or in Combination with Chemotherapy: Responses in Pediatric Patients with Relapsed/Refractory Acute Myeloid Leukemia with Heterogeneous Genomic Profiles

2020· article· en· W3094788775 sur OpenAlexaff
Seth E. Karol, Henrique Bittencourt, Daniel A. Morgenstern, Margaret E. Macy, Seong Lin Khaw, Todd M. Cooper, Arnaud Petit, Giridharan Ramsingh, Bo Tong, Kristina Unnebrink, Deeksha Vishwamitra, Fengjiao Dunbar, Betty Prine, Tammy L. Palenski, Andrew E. Place

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensHospital for Sick ChildrenCentre Hospitalier Universitaire Sainte-Justine
Organismes subventionnairesnon disponible
Mots-clésVenetoclaxMedicineInternal medicineOncologyVenChemotherapy regimenInduction chemotherapyRegimenChemotherapyLeukemiaGastroenterologyChronic lymphocytic leukemia

Résumé

récupéré en direct d'OpenAlex

Introduction: Pediatric acute myeloid leukemia (AML) is a molecularly heterogeneous group of diseases lacking therapy options that would improve overall survival. Venetoclax (VEN) is an oral inhibitor for selective targeting of B-cell lymphoma 2 (BCL2), which is highly expressed in most patients (pts) with AML and has demonstrated promising efficacy in pediatric pts with AML when combined with chemotherapy (CTx) (Karol SE, et al. Lancet Oncol. 2020;21:551-560). Here, we present safety, efficacy, and preliminary genomic results from pediatric pts with relapsed/refractory (R/R) AML receiving VEN + CTx. Methods: This phase 1 open-label, 2-part, multicenter study (NCT03236857) enrolled pts <25 years with R/R malignancies; here we report on R/R AML. During VEN monotherapy (monoTx), 10 pts received a weight- or age-adjusted adult-equivalent oral daily dose of 800 mg VEN after a 3-day ramp-up to mitigate tumor lysis syndrome risk. Standard of care CTx could be added after 21 days of VEN monoTx at the discretion of the treating physicians. In cohort expansion, 26 pts were enrolled with standard of care CTx allowed after VEN ramp-up. Primary and secondary endpoints included safety and preliminary efficacy of VEN monoTx and VEN + CTx. In addition, exploratory biomarker analyses were performed. For genomic analyses, whole exome sequencing was performed on pretreatment blood or bone marrow samples, and highly recurrent genetic alterations across various functional classifications in AML were analyzed. Previously documented gene fusion data were acquired through site-reported cytogenetic entries at screening. RNA sequencing was performed on pretreatment blood or bone marrow samples and BCL2 family expression was assessed. Results: As of June 2020, 36 pts with R/R AML were enrolled and received VEN monoTx (n=3) and VEN + CTx (n=33: VEN + decitabine [VEN-DEC, n=5], azacitidine [VEN-AZA, n=19], or low- [VEN-LDAC, n=1] or high-dose cytarabine [VEN-HDAC, n=8]) (Table). The primary reason for VEN discontinuation was progressive disease (n=19); median duration of VEN therapy was 3.1 months (range 0.2-9.3). All pts experienced adverse events (AEs); 3 pts (n=1 VEN-DEC, n=2 VEN-AZA) had fatal AEs considered unrelated to VEN. The most common grade 3/4 AEs were febrile neutropenia (58%) and hypokalemia (33%). The overall objective response rate (ORR) was 25% (9/36); median duration of response was 0.8 month (95% CI, 0.5, 3.6). The best ORR was seen with VEN-HDAC (4/8, 50%) with 1 complete response (CR), 1 CR without platelet recovery, 1 CR with incomplete marrow recovery (CRi), and 1 partial response (PR); 2 pts achieved minimal residual disease negativity and 2 pts proceeded to transplant. The ORR with VEN-AZA was 26% (5/19), with 3 CR/CRi and 2 PR. No responses were seen with VEN monoTx or VEN + other CTx. The genomic landscape of biomarker-evaluable pts was highly heterogeneous (Figure A). Mutations of genes involved in epigenetic modification (MYH11, IDH2, ASXL1, SETBP1, TET2, and NSD1) and transcription regulation (GATA1, WT1, RUNX1, and CEBPA) were the most common, in 58% and 48% of pts, respectively. Analysis of the recurring mutations found in ≥2 pts revealed that responses to VEN-AZA were seen in pts with IDH2 (1/4), MYH11 (2/6), RUNX1 (1/3), or FLT3 (1/3) mutations, and responses to VEN-HDAC were seen in pts with JAK2 (1/4) or GATA1 (1/3) mutations. Pts with WT1 (3/6) and PTPN11 (3/4) mutations responded to both regimens. Pts with TP53 (n=2) or ETV6 (n=3) mutations and PML-RARA (n=2) or KMT2A rearrangements (n=8) did not respond to any treatment. Gene expression profiling revealed that BCL-xL expression was significantly higher compared with BCL2;MCL1 levels were the highest (Figure B). There was no association between expression of these genes and response. Mutations were seen in BCL2 and MCL1 (n=1 each), but not in BCL-xL. Conclusions: VEN + CTx was well tolerated in pediatric pts with R/R AML, with no unexpected toxicities. Preliminary efficacy was seen in pts receiving VEN-AZA or VEN-HDAC: ORR 26% and 50%, respectively. VEN + CTx resulted in responses in pts harboring mutations across a range of functional classifications; however, some alterations may confer resistance. Due to the limited number of pts harboring each mutation and the overall heterogeneity of the genomic landscape, these findings need to be evaluated in a larger population, and warrant further investigation. Disclosures Karol: AbbVie Inc.: Other: Unrelated to this study, St. Jude has received a charitable contribution from AbbVie, Inc. The charitable contribution is not being used for clinical or research activities, including any activities related to this study. . Bittencourt:Jazz Pharmaceuticals: Consultancy, Other: travel, accommodations, expenses; Novartis: Consultancy. Morgenstern:EUSA Pharma: Consultancy, Other: travel support; Bayer: Consultancy; Clarity Pharmaceuticals: Consultancy; BMS: Other: Institutional Research Funding; Boehringer Ingelheim: Consultancy; Roche: Consultancy. Macy:Merck: Other: Institutional Research Funding; Pfizer: Other: Institutional Research Funding; Bayer: Other: Institutional Research Funding; AbbVie Inc.: Other: Institutional Research Funding; Roche: Other: Institutional Research Funding; Johnson & Johnson: Current equity holder in publicly-traded company. Khaw:Amgen: Other: Institutional Research Funding; Bristol-Myers Squibb: Other: Institutional Research Funding; AbbVie Inc.: Other: Institutional Research Funding; Novartis: Other: travel, accommodation, expenses; Walter and Eliza Hall Institute of Medical Research.: Patents & Royalties: Recipient of a share in royalty payments . Cooper:Celgene: Other: Spouse was an employee of Celgene (through August 2019). Ramsingh:Genentech: Current Employment, Current equity holder in publicly-traded company; Roche: Current equity holder in publicly-traded company, Ended employment in the past 24 months. Tong:AbbVie, Inc.: Current Employment, Other: may hold stock or other options. Unnebrink:AbbVie: Current Employment, Other: may hold stock or other options. Vishwamitra:AbbVie, Inc.: Current Employment, Other: may hold stock or other options. Dunbar:Abbvie: Current Employment, Current equity holder in publicly-traded company. Prine:AbbVie: Current Employment, Other: may hold stock or other options. Palenski:AbbVie: Current Employment, Other: may hold stock or other options. Place:Novartis: Consultancy, Other: Institutional Research Funding; AbbVie: Consultancy. OffLabel Disclosure: Venetoclax is a BCL-2 inhibitor that is FDA approved for some indications. Venetoclax for treatment of pediatric AML is not an approved indication.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
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 Opus0,012
Tête enseignante GPT0,243
Écart entre enseignants0,231 · 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 source (Gemma direct ou Codex distillé), 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

Citations9
Publié2020
Routes d'admission1
Résumé présentoui

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