MétaCan
Menu
Retour à la cohorte
Enregistrement W3212160764 · doi:10.1182/blood-2021-152369

Performance of Next Generation Sequencing for Minimal Residual Disease Detection for Pediatric Patients with Acute Lymphoblastic Leukemia: Results from the Prospective Clinical Trial DFCI 16-001

2021· article· en· W3212160764 sur OpenAlexaffabout
Jonathan Paolino, Marian H. Harris, Kristen E. Stevenson, Victoria Koch, Peter D. Cole, Lisa Gennarini, Justine M. Kahn, Kara M. Kelly, IIan Kirsch, Bruno Michon, Andrew E. Place, Thai Hoa Tran, Jennifer Welch, Lewis B. Silverman

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Lymphoblastic Leukemia research
Établissements canadiensCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalCentre hospitalier universitaire de Québec
Organismes subventionnairesnon disponible
Mots-clésMinimal residual diseaseMedicineImmunophenotypingInternal medicineOncologyLeukemiaAcute lymphocytic leukemiaPediatricsImmunologyLymphoblastic LeukemiaFlow cytometry

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Assessment of minimal residual disease (MRD) in a sensitive and timely manner is an essential component of risk stratification in childhood acute lymphoblastic leukemia (ALL). Next generation sequencing (NGS) assays utilize unique genetic sequences created by VDJ rearrangements in leukemia cells to detect MRD at the level of 1 leukemic cell in 1 million cells (Wood et al., 2018). Here we report our experience using NGS MRD for risk group assignment of children and adolescents with newly diagnosed ALL enrolled on the Dana Farber Cancer Institute (DFCI) ALL Consortium Protocol 16-001. Methods: Patients (pts) ages 1-21 years with B- or T-ALL were eligible for enrollment from 8 centers across the US and Canada. Initial risk status was assigned based on age, presenting leukocyte count, central nervous system (CNS) leukemia status, immunophenotype, and disease biology (Table 1). All patients underwent bone marrow evaluation at diagnosis and again upon completion of remission induction approximately four weeks later (Induction 1a, timepoint 1 (TP1)), with samples evaluated by flow cytometry (FCM) and NGS. NGS was primarily used for MRD-based risk determination, with FCM as a back-up test. Patients with high TP1 MRD (≥10 -4) received intensified therapy and underwent additional MRD assessments at 10 and 20 weeks of therapy. Multiparametric FCM was conducted locally for 7 of 8 sites in accordance with local CLIA certified lab practices. One site used centralized FCM. NGS MRD was assessed at Adaptive Biotechnologies Corporation, Seattle, WA using the commercially available assay ClonoSEQ ®. Clonality was evaluated at the immunoglobulin (Ig) heavy and light chain (IgH and IgL) and T cell receptor beta and gamma (TCR-B and TCR-G) loci with the maximal sequence used for MRD determination. Results: NGS evaluation of MRD is feasible A total of 317 patients enrolled on 16-001 between 2017 and 2020 were included in this analysis. Among this cohort, NGS identified unique trackable sequences in 98% of pts (N=310). Of the 7 pts without trackable sequences, 57% were pts with early T precursor (ETP) T-ALL (36% of all ETP pts tested). NGS detected trackable sequences in all non-ETP T-ALL pts (N=40), and 99% of B-ALL pts (N=263). Locus used for MRD determination Patients with B-ALL had a median of 5 trackable sequences (range 0-14) with 92% having at least one IgH and 64% having at least one TCR-G. For B-ALL, the highest MRD value at TP1 was determined by IGH locus in 44% (N=115) of pts and by TCR-G in 41% (N=109). The IgL or TCR-B locus yielded the highest TP1 MRD value in 15% (N=39). In contrast, pts with T-ALL had fewer trackable sequences with a median of 3 (range 0-8). While 28% (N=13) had at least one Ig sequence, the TCR locus was used for MRD determination in nearly all (98%, N=46) with 94% using TCR-G. Comparison of NGS and FCM MRD results NGS and FCM MRD values for 309 pts with results from both assays at TP1 are displayed in Figures 1a-d. Correlation was high between the two modalities for patients with detectable disease by both NGS and FCM (Pearson r=0.87, p<0.0001). NGS additionally detected MRD in the range of 10 -6 to <10 -4 for 160 patients with FCM undetectable disease at TP1, representing 50% of our cohort. Fifty one pts (17%) had high NGS MRD (≥10 -4) but low (8%) or undetectable (92%) FCM MRD (<10 -4), representing 50% of pts classified as high MRD at TP1. For B-ALL pts with high MRD (N=70), 43% (N=30) were high by NGS (≥10 -4) when FCM was low (<10 -4, N=4) or undetectable (N=26) with 90% of discrepancies at the NGS level of 10 -4 (Figure 1a-b). In contrast, for T-ALL pts with high TP1 MRD (N=28), 75% (N=21) were high by NGS alone, all with undetectable FCM. Sixty seven percent of these pts (N=14) had NGS MRD at the level of 10 -4 and the remaining 33% (N=7) were in the range of 10 -3 to <10 -1 (Figure 1c-d). Eight pts, all with B-ALL, had low NGS MRD when FCM was above the threshold of 10 -4. One patient had undetectable NGS MRD and the remaining 7 had NGS MRD in the range of 10 -6 to <10 -4. Conclusions: Delivery of risk adapted therapy for newly diagnosed pediatric pts with ALL utilizing an NGS MRD assay is feasible with evaluable MRD for 98% of patients in our cohort. Importantly, NGS identified more cases as having high MRD than FCM, with the majority of discrepant cases just above the FCM limit of detection (10 -4). NGS provided improved resolution in the range of 10 -6 to <10 -4 for both B-ALL and T-ALL. The prognostic relevance of these low MRD levels awaits longer follow-up. Figure 1 Figure 1. Disclosures Kirsch: Adaptive Biotechnologies: Current Employment, Current holder of stock options in a privately-held company. Silverman: Takeda, Servier, Syndax, Jazz Pharmaceuticals: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees.

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)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,097
Score d'incertitude au seuil0,832

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,004
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 Opus0,051
Tête enseignante GPT0,300
Écart entre enseignants0,249 · 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'étudeEssai randomisé
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

Citations6
Publié2021
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueBloodMême sujetAcute Lymphoblastic Leukemia researchTravaux en français237 207