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Record 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 on 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

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMinimal residual diseaseMedicineImmunophenotypingInternal medicineOncologyLeukemiaAcute lymphocytic leukemiaPediatricsImmunologyLymphoblastic LeukemiaFlow cytometry

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.300
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations6
Published2021
Admission routes2
Has abstractyes

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