Uncovering Therapeutic Vulnerabilities in Adverse-Risk Pediatric Acute Myeloid Leukemia
Bibliographic record
Abstract
High fatality pediatric acute myeloid leukemia (AML) remains a therapeutic challenge due to the lack of tailored treatments adapted to the genetic and cellular heterogeneity of the disease and the long-term toxicity of standard therapies (Hara, 2023; Mercher, 2019). Our group has previously developed synthetic and patient-derived xenograft (PDX) models of high-fatality acute megakaryoblastic leukemia (AMKL) and demonstrated that BCL-XL is a therapeutic vulnerability of NUP98-rearranged (NUP98r) and CBFA2T3::GLIS2 subgroups using in vitro and in vivo pharmacological inhibition approaches (e.g. BH3 mimetic navitoclax targeting pro-survival proteins BCL-XL/BCL-2/BCL-W and BCL-XL proteolysis targeting chimera DT2216) (Cardin 2019; Gress, 2024). Navitoclax or DT2216 combined with the standard of care drug cytarabine further reduced leukemic burden in xenograft models of AMKL (Gress, 2024). Using high throughput pharmacological screening, we delineated subtype-specific sensitivities to BH3 mimetics (navitoclax, venetoclax targeting BCL-2) in other types of adverse-risk leukemia, including a Down syndrome (DS)-AMKL PDX model (trisomy 21/T21), NUP98r AML and KMT2A-rearranged (KMT2Ar) AML (Safa-Tahar-Henni, 2024, in press). To build on these discoveries, we are now investigating additional adverse-risk AML subgroups, including those with TP53 gene alterations (TP53-AML). While TP53 alterations are common in hematological diseases and are recognized as a distinct entity in various risk classification systems for adult AML, this stratification remains neglected in pediatric populations (Döhner, 2022; Arber, 2022). Further research is needed to fully understand the implications of TP53 alterations in pediatric AML and to develop targeted therapeutic strategies for this subgroup. Among 122 pediatric AML patients in our provincial cohort (2012-2024), 10 (8%) harbored a TP53 alteration at diagnosis or at relapse. Four TP53-AML PDX models harboring different TP53 alterations alongside various genomic alterations (T21, KMT2Ar (n=2), PICALM::MLLT10) were successfully generated with SGM3 immunodeficient mice. Leukemia can sustain serial rounds of transplantation in recipient mice (up to four rounds tested) with latencies ranging from 2.9 to 38.1 weeks. Leukemic blasts infiltrated bone marrow (hCD45 = 11.5-99.7%) and spleen (hCD45 = 4-95%) as assessed by flow cytometry, along with spleen weights measurements (73-506 mg). Furthermore, we confirmed that leukemic blasts immunophenotypically recapitulate AML, demonstrating expression of primitive and myeloid lineage markers such as hCD45+, CD34+/-, CD117+ and CD33+. Phenotypic and molecular characterization using exome and transcriptome sequencing alongside comparative genomic hybridization (CGH) of blasts confirmed that our models accurately recapitulate the disease. To identify potential therapeutic vulnerabilities, we validated compounds of interest (e.g. BH-3 mimetics) using dose-response curve analyses where IC50 values were determined using a CellTiterGlo viability assay. We identified navitoclax, an inducer of apoptosis with broad affinity to BCL-2, BCL-XL and BCL-W (IC50 = 0.016-0.202μM) to be a promising therapeutic agent in all 4 PDX models. BCL-2 inhibition using venetoclax was also identified as a therapeutic vulnerability in 3 of the models (IC50 = 0.009-0.083 μM), excluding T21 (IC50 > 10μM), despite detectable intracellular BCL-2 protein levels. In vivo validation studies to confirm anti-leukemic activity are in progress. In line with these findings, a salvage therapeutic regimen including venetoclax was used as a bridge-to-transplant strategy in a case of primary refractory PICALM::MLLT10 AML. Overall, these results underscore the importance of assessing susceptibility to BH3 mimetics in adverse-risk pediatric AML, including those with TP53 alterations, in the context of functional precision medicine strategies.
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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 | 0.000 | 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".