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Enregistrement W2987021886 · doi:10.1182/blood-2019-122890

High Interpatient Variability in Molecular MRD Response to Consolidation Chemotherapy in Acute Myeloid Leukemia

2019· article· en· W2987021886 sur OpenAlexaffabout
Tracy Murphy, Jinfeng Zou, Ting Ting Wang, Yangqiao Zheng, Zhen Zhao, Roman M. Shapiro, Vikas Gupta, Dawn Maze, Caroline McNamara, Mark D. Minden, Aaron D. Schimmer, Andre C. Schuh, Hassan Sibai, Karen Yee, Tracy Stockley, Philip C. Zuzarte, Carolina Bocanegra, Lawrence E. Heisler, Paul M. Krzyzanowski, Trevor J. Pugh, Scott V. Bratman, Steven M. Chan

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchUniversity of TorontoUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMinimal residual diseaseMedicineInternal medicineChemotherapyOncologyInduction chemotherapyMyeloid leukemiaLeukemiaBone marrowChemotherapy regimen

Résumé

récupéré en direct d'OpenAlex

Introduction: Although induction chemotherapy results in a complete remission (CR) in ~70% of newly diagnosed AML patients, post-remission therapies are needed to eliminate minimal residual disease (MRD) and prevent relapse. Consolidation chemotherapy, either as definitive therapy or bridge to bone marrow transplantation (BMT), is currently the most common form of post-remission therapy. Yet, our understanding of its impact on MRD remains limited. In this study, we investigated the effects of consolidation chemotherapy on molecular MRD (mMRD) burden using ultra-deep next generation sequencing (NGS) and correlated treatment response with disease characteristics and survival outcomes in AML patients. Patients and Methods: 91 newly diagnosed AML patients who achieved CR following standard induction chemotherapy were evaluated. Targeted conventional NGS using a 54-gene panel was performed on whole blood (PB) or bone marrow samples collected at diagnosis. PB samples were collected during remission at two consecutive time points (T1 and T2), before and after 1 (n=79) or 2 (n=12) cycles of consolidation chemotherapy, for each patient. To detect mMRD, we used a custom 37-gene hybrid-capture panel and error-corrected NGS based on the duplex sequencing approach with a variant allele frequency (VAF) detection limit of ~1x10-4. For 10 patients, we also performed duplex sequencing analysis on their relapsed samples. Results: NGS of the diagnostic samples identified a total of 298 putative oncogenic mutations in 92% (n=84) of the 91 patients. Ninety percent of these mutations (n=267) were trackable by the custom hybrid-capture panel. Duplex sequencing detected persistence of 56% (n=149) of the trackable mutations in T1 samples; 34% (n=50) of which were clonal hematopoiesis-associated DTA mutations (those involving DNMT3A, TET2, or ASXL1), and the remaining 66% (n=99) were non-DTA mutations. Analysis of T2 samples showed that consolidation chemotherapy reduced the VAF of non-DTA mutations by a median of 73% and cleared 27% (n=27) of them at T2. In contrast, the burden of DTA mutations increased by 0.5% (P < 0.0001 by Mann-Whitney test), and only 2% (n=1) of the mutations was cleared (P = 0.0001 by Fisher's exact test). These findings are consistent with prior studies demonstrating that non-DTA mutations are more reliable markers of leukemic burden than DTA mutations. To study the impact of consolidation chemotherapy at the level of individual patients, the mean VAF of all persistent non-DTA mutations was calculated for each sample and used as a composite measure of mMRD burden (henceforth referred to as "cmMRD"). Analysis of the 10 patients with relapsed samples showed that cmMRD levels tracked well with achievement of remission and disease progression (Fig. 1). In the subset of patients with persistent non-DTA mutations at T1 (n=61), consolidation chemotherapy decreased cmMRD levels by a median of 36% at T2. However, we observed high interpatient variability (Fig. 2); 36% (n=22) of the patients experienced an increase in cmMRD burden after consolidation chemotherapy, and 36% (n=22) had less than a 1 log reduction. Only 28% (n=17) of the patients achieved a log reduction of greater than 1. The likelihood and magnitude of cmMRD response were significantly associated with cytogenetic risk (P = 0.026 by 3x3 Chi-square test; Fig. 3). The proportion of patients with favorable, intermediate, and poor-risk cytogenetics who experienced cmMRD expansion was 17%, 27%, and 71%, respectively. Consistent with these findings, a suboptimal response (defined as cmMRD ratio [T2/T1] > 0.4) was associated with inferior overall survival (HR = 3.29, P = 0.007 by log-rank test; Fig. 4). Conclusions: Our analysis showed that mMRD response to consolidation chemotherapy was highly variable among patients. Although consolidation chemotherapy was effective in deepening the remission for a subset of patients, it failed to lower MRD levels for a substantial proportion of patients, especially those with poor risk cytogenetics. These findings challenge the practice of using consolidation chemotherapy to achieve a deeper remission prior to BMT for high-risk patients and indicate that the opposite outcome may occur instead. NGS-based monitoring of mMRD can potentially be used to distinguish between patients who can remain on consolidation chemotherapy as definitive therapy and those who require a switch in post-remission therapy. Disclosures Gupta: Sierra Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Honoraria, Research Funding. Maze:Pfizer Inc: Consultancy; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. McNamara:Novartis Pharmaceutical Canada Inc.: Consultancy. Minden:Trillium Therapetuics: Other: licensing agreement. Schimmer:Medivir Pharmaceuticals: Research Funding; Jazz Pharmaceuticals: Consultancy; Novartis Pharmaceuticals: Consultancy; Otsuka Pharmaceuticals: Consultancy. Schuh:Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees; Agios: Honoraria; Astellas: Honoraria, Membership on an entity's Board of Directors or advisory committees; Teva Canada Innovation: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Yee:Novartis, Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas, Celgene, Otsuka, Shire, Takeda: Membership on an entity's Board of Directors or advisory committees; Agensys, Astex, Hoffman La Roche, MedImmune, Merck, Millenium, Roche/Genentech: Research Funding. Bratman:SVB: Other: is co-inventor of a patent relating to circulating tumor DNA detection technology, which has been licensed to Roche Molecular Diagnostics.. Chan:Agios: Honoraria; AbbVie Pharmaceuticals: Research Funding; Celgene: Honoraria, 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 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)0,001
score de la tête « metaresearch » (Gemma)0,001
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: Observationnel
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
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,007
Tête enseignante GPT0,272
Écart entre enseignants0,265 · 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

Citations0
Publié2019
Routes d'admission2
Résumé présentoui

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