Challenges in Cell Fate Acquisition to Scid-Repopulating Activity from Hemogenic Endothelium of hiPSCs Derived from AML Patients Using Forced Transcription Factor Expression
Bibliographic record
Abstract
The generation of human hematopoietic stem cells (HSCs) from human pluripotent stem cells (hPSCs) represents a major goal in regenerative medicine and is believed would follow principles of early development. HSCs arise from a type of endothelial cell called a “hemogenic endothelium” (HE), and human HSCs are experimentally detected by transplantation into SCID or other immune-deficient mouse recipients, termed SCID-Repopulating Cells (SRC). Recently, SRCs were detected by forced expression of seven transcription factors (TF) (ERG, HOXA5, HOXA9, HOXA10, LCOR, RUNX1, and SPI1) in hPSC-derived HE, suggesting these factors are deficient in hPSC differentiation to HEs required to generate HSCs. Here we derived PECAM-1-, Flk-1-, and VE-cadherin-positive endothelial cells that also lack CD45 expression (PFVCD45−) which are solely responsible for hematopoietic output from iPSC lines reprogrammed from AML patients. Using HEs derived from AML patient iPSCs devoid of somatic leukemic aberrations, we sought to generate putative SRCs by the forced expression of 7TFs to model autologous HSC transplantation. The expression of 7TFs in hPSC-derived HE cells from an enhanced hematopoietic progenitor capacity was present in vitro, but failed to acquire SRC activity in vivo. Our findings emphasize the benefits of forced TF expression, along with the continued challenges in developing HSCs for autologous-based therapies from hPSC sources.
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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 | 0.001 | 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".