MRD Xenotransplantation Prospectively Identifies Treatment-Selected Acute Lymphoblastic Leukemia Subpopulations with Relapse-Initiating Potential
Bibliographic record
Abstract
Despite complete remissions being achieved in most newly diagnosed acute lymphoblastic leukemia (ALL) patients, relapse remains a significant clinical challenge. Interrogation of matched ALL samples has provided insights into the cellular characteristics and evolutionary trajectory of relapse-fated clones, but requires blasts obtained at time of relapse to provide a reference point for the retrospective analysis. Despite the strong prognostic value of minimal residual disease (MRD), MRD-positive samples have been under-utilized for investigating disease progression as the low leukemia burden presents significant challenges to the evaluation of the residual blasts. To overcome this limitation, we performed patient-derived xenografting (PDX) with MRD samples to enable deeper characterization of residual blasts, including functional assessment of their leukemia propagating ability. In marked contrast to a previous study in adult ALL, we achieved engraftment of MRD blasts from 5 of 7 pediatric ALL patient samples, obtained at the end of induction (EOI) therapy, by intravenous injection into non-conditioned NSG mice. MRD blasts expanded with patient-specific kinetics, reaching overt leukemia in recipients of three of the samples and remaining at MRD levels in recipients of the remaining two. The absence of normal human hematopoiesis in the MRD-engrafted mice (termed EOI-PDX), combined with the expansion of residual blast numbers, enabled clear phenotypic definition of therapy-selected, leukemia-propagating subpopulations, including those present at <1%. Subsequent reanalysis of diagnosis (DX) and EOI clinical samples for the identified subpopulations exposed a treatment response-mediated disruption of the established population hierarchy that explained the phenotypic shifts observed during disease progression. The relevance of the subpopulations identified as potential leukemia drivers was confirmed by their dominance in subsequent clinical relapses. Furthermore, phenotype-based sorting of viable blast subpopulations enabled the identification and comparison of metabolic characteristics of treatment sensitive and resistant blasts. This immunophenotypic study recapitulates the enrichment of minor clones during ALL progression described by retrospective sequencing studies, but it does so prospectively. By expanding on the quantitative and qualitative information that can be gathered from MRD samples, EOI-PDX identify the blast populations that are most likely to drive relapse, prior to clinical disease progression. By providing a platform to achieve early identification and ongoing monitoring of therapy-resistant subpopulations with strong leukemia-propagating capacity, this approach could refine treatment-response assessment and relapse-risk stratification. Further, by expanding the numbers of viable treatment-selected MRD blasts available for interrogation, EOI-PDX could enable early identification of vulnerabilities in chemotherapy-resistant blasts. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".