Teratoma-free cartilage regeneration using <i>p21</i> −/− iPSCs engineered with iCasp9
Bibliographic record
Abstract
OBJECTIVE: Articular cartilage has limited regenerative capacity due to its lack of innervation, vascularization, and lymphatic vessels. As cartilage is devoid of nerves, injuries often go unnoticed until degeneration leads to pain, reduced function, and ultimately osteoarthritis (OA). Treatment options for cartilage injury, both surgical and nonsurgical, depend on factors like defect size, shape, depth, location, and patient age. Stem cells, particularly their ability to differentiate into chondrocytes, hold promise for cartilage repair, but no therapies have yet gained clinical approval. Recently, induced pluripotent stem cells (iPSCs) have emerged as a potential solution for cartilage regeneration. However, post-transplantation tumorigenesis remains a significant concern. To mitigate this risk, robust quality and safety protocols are needed, alongside safety mechanisms to control iPSC behavior after transplantation. DESIGN: The iCaspase9 (iCasp9) cell suicide system offers a promising solution, enabling selective elimination of genetically modified cells via apoptosis. We previously demonstrated that the efficiency of iCasp9-mediated killing increases in a p21 mutant background. Since p21 mutations also enhance cartilage repair, we investigated iCasp9-engineered p21-/- and wildtype (p21+/+) iPSCs in a mouse cartilage injury model. RESULTS: Without iCasp9 activation, both p21-/- and p21+/+ iPSCs formed tumors post-transplantation. In contrast, mice treated with the iCasp9 activator AP20187 showed no tumors. Both p21-/- and p21+/+ iPSCs demonstrated similar cartilage regeneration. CONCLUSIONS: These findings suggest that iCasp9-mediated elimination of iPSCs can effectively mitigate tumor risks while preserving their therapeutic potential for cartilage repair.
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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".