Single Cell Profiling of Hematopoietic Stem and Progenitor Cells in Pediatric Acquired Aplastic Anemia
Bibliographic record
Abstract
Acquired severe aplastic anemia (AA) is a bone marrow failure disorder featuring a paucity of blood cells that significantly predisposes affected individuals to life threatening infections and/or bleeding, evolution to myelodysplastic syndrome/leukemia, risk of treatment relapse and/or death. The latest successful addition of Eltrombopag, a unique thrombopoietin receptor agonist, to frontline immunosuppressive therapy among adult patients with acquired AA has provided proof-of-principle that there may be additional ways to recover hematopoiesis in this setting. To examine the causes of and to identify novel strategies to rescue haematopoiesis in pediatric AA, we employed single cell profiling using cellular indexing of transcriptomes and epitopes (CITE-seq) on lineage-negative and treatment-naïve diagnostic severe paediatric AA (n = 5) and age-approximated healthy donor (n = 4) primary bone marrow samples and obtained transcriptomes of 2,009 and 13,861 single cells respectively. This profiling uncovered a widespread loss of primitive hematopoietic stem and progenitor cells (HSPCs) in pediatric AA with significant enrichment for IFN-γ, IL6/JAK/STAT, unfolded protein response and PI3K/AKT/MTOR pathways. Residual HSCs in pediatric AA showed enrichment of a recently described HSC inflammatory memory transcriptional signature. Granzymes were distinctly upregulated in residual HSPCs within pediatric AA. Further profiling of additional samples is required to capture additional events among rare HSPC populations. Altogether, these results demonstrate significant underlying inflammation and rationalize testing of Ruxolitinib, Sirolimus and granzyme blockade in pediatric AA. Future work will involve establishing a bone marrow organoid model of pediatric AA for therapeutic screening and drug discovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".