Abstract B29: Validation of a model of pediatric leukemia based on pluripotent stem cells using mass cytometry
Bibliographic record
Abstract
Abstract Pediatric acute myeloid leukemia (AML) is a rare disease characterized by an accumulation of immature white blood cells in the bone marrow and/or peripheral blood. In some cases, it is thought that the predisposition to leukemia begins in utero. Often, leukemogenesis in children is caused by recurrent chromosomal translocations that result in fusion proteins that do not occur in AML in adults. In particular, NUP98-JARID1A is a recurrent fusion that occurs in an aggressive AML characterized by malignant megakaryoblasts. The prognosis for these patients is poor and there are few novel therapies on the horizon. Using human pluripotent stem cells, we can model this disease by recapitulating the events of leukemogenesis with the goal to better understand the pathogenesis of this disease and to identify better treatments for children. To this end, we generated human pluripotent cell lines that express the NUP98-JARID1A (NJ) fusion protein through a lentiviral expression system. These cells have been characterized in the pluripotent state by RNAseq and molecular and cell culture methods. The cell lines can be differentiated to the three germ layers, and we can focus on the myeloid lineage. Here we are using mass cytometry to analyze the differentiation phenotypes of these cells in comparison to both normal bone marrow stem and progenitor populations as well as primary patient samples. Induced pluripotent cells carrying the NJ fusion maintain their pluripotent state by the presence of surface markers and expression of pluripotent genes despite a higher sensitivity to stress and difficulties to culture them. These cells display abnormal mitosis showing multiple poles and bad segregation of chromosomes, which results in aberrant karyotypes. Interestingly, as NJ iPS cells differentiate to the three germ layers, NJ iPS demonstrate a substantial increase in specific mesodermal markers as CD34 and KDR, but without differences in ectoderm or endoderm specific markers. We will discuss comparisons between myeloid developmental populations from NJ iPS cells, wild-type iPS cells differentiated to the myeloid lineage and normal bone marrow. Finally, we compare differentiated NJ iPS leukemic cells to primary patient samples based on their phenotypic and signaling features as determined by CyTOF. In conclusion, we demonstrate an early model of NUP98-JARID1A fusion AML that recapitulates the genomic instability of this leukemia and demonstrates a deregulation of mesodermal development and further myeloid differentiation. NUP98 has been described with 30 other fusion partners, all related to leukemia, and this model may be used as a basis for understanding its role in leukemogenesis. Citation Format: Joan Domingo-Reines, Samuel Kimmey, Kausalia Vijayaragavan, Marc Bosse, Sean Bendall, Kara Davis, Veronica Ramos-Mejía. Validation of a model of pediatric leukemia based on pluripotent stem cells using mass cytometry [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B29.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".