Human embryonic stem cells secrete soluble factors that inhibit cancer cell growth
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to determine whether normal human embryonic stem cells (hESC) would secrete factors that arrest growth of human epithelial cancer cell lines. MATERIALS AND METHODS: Cell proliferation was examined using the MTT assay then haemocytometer cell counts. Staining with propidium iodide followed by flow cytometry was used to detect cell cycle stages. Heat denaturation and molecular fractionation experiments were also performed. RESULTS: We found that hESC conditioned medium (hESC CM) inhibited SKOV-3 and HEY cell proliferation. Similar results were also obtained when we used breast and prostate cancer cell lines, whereas little or no inhibitory effect was observed when human fibroblasts were tested. Moreover, a co-culture model confirmed that inhibition of cancer cell proliferation is mediated by soluble factors produced by hESCs. We also determined that the proportion of cancer cells in G(1) phase was increased by hESC CM treatment, accompanied by decrease in cells in S and G(2)/M phases, suggesting that the factors slow progression of cancer cells by cell cycle inhibition. Heat denaturation and molecular fractionation experiments indicated a low molecular weight thermostable factor was responsible for these properties. CONCLUSIONS: Our findings provide evidence that the human embryonic microenvironment contains soluble factor(s) that are capable of inhibiting growth of cancer cells, and that exposure to such factors may represent a new cancer treatment strategy.
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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".