Reprogramming Malignant Cancer Cells toward a Benign Phenotype following Exposure to Human Embryonic Stem Cell Microenvironment
Bibliographic record
Abstract
The embryonic microenvironment is well known to be non-permissive for tumor development because early developmental signals naturally suppress the expression of proto-oncogenes. In an analogous manner, mimicking an early embryonic environment during embryonic stem cell culture has been shown to suppress oncogenic phenotypes of cancer cells. Exosomes derived from human embryonic stem cells harbor substances that mirror the content of the cells of origin and have been reported to reprogram hematopoietic stem/progenitor cells via horizontal transfer of mRNA and proteins. However, the possibility that these embryonic stem cells-derived exosomes might be the main effectors of the anti-tumor effect mediated by the embryonic stem cells has not been explored yet. The present study aims to investigate whether exosomes derived from human embryonic stem cells can reprogram malignant cancer cells to a benign stage and reduce their tumorigenicity. We show that the embryonic stem cell-conditioned medium contains factors that inhibit cancer cell growth and tumorigenicity in vitro and in vivo. Moreover, we demonstrate that exosomes derived from human embryonic stem cells display anti-proliferation and pro-apoptotic effects, and decrease tumor size in a xenograft model. These exosomes are also able to transfer their cargo into target cancer cells, inducing a dose-dependent increase in SOX2, OCT4 and Nanog proteins, leading to a dose-dependent decrease of cancer cell growth and tumorigenicity. This study shows for the first time that human embryonic stem cell-derived exosomes play an important role in the tumor suppressive activity displayed by human embryonic stem cells.
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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 | 0.001 | 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".