The Microenvironment-Specific Transformation of Adult Stem Cells Models Malignant Triton Tumors
Bibliographic record
Abstract
Here, we demonstrated the differentiation potential of murine muscle-derived stem/progenitor cells (MDSPCs) toward myogenic, neuronal, and glial lineages. MDSPCs, following transplantation into a critical-sized sciatic nerve defect in mice, showed full regeneration with complete functional recovery of the injured peripheral nerve at 6 weeks post-implantation. However, several weeks after regeneration of the sciatic nerve, neoplastic growths were observed. The resulting tumors were malignant peripheral nerve sheath tumors (MPNSTs) with rhabdomyoblastic differentiation, expressing myogenic, neurogenic, and glial markers, common markers of human malignant triton tumors (MTTs). No signs of tumorigenesis were observed 17 weeks post-implantation of MDSPCs into the gastrocnemius muscles of dystrophic/mdx mice, or 1 year following subcutaneous or intravenous injection. While MDSPCs were not oncogenic in nature, the neoplasias were composed almost entirely of donor cells. Furthermore, cells isolated from the tumors were serially transplantable, generating tumors when reimplanted into mice. However, this transformation could be abrogated by differentiation of the cells toward the neurogenic lineage prior to implantation. These results establish that MDSPCs participated in the regeneration of the injured peripheral nerve but transformed in a microenvironment- and time-dependent manner, when they likely received concomitant neurogenic and myogenic differentiation signals. This microenvironment-specific transformation provides a useful mouse model for human MTTs and potentially some insight into the origins of this disease.
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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 | 0.000 |
| 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".