Carcinoma-Associated Fibroblast–Like Differentiation of Human Mesenchymal Stem Cells
Bibliographic record
Abstract
Carcinoma-associated fibroblasts (CAF) have recently been implicated in important aspects of epithelial solid tumor biology, such as neoplastic progression, tumor growth, angiogenesis, and metastasis. However, neither the source of CAFs nor the differences between CAFs and fibroblasts from nonneoplastic tissue have been well defined. In this study, we show that human bone marrow-derived mesenchymal stem cells (hMSCs) exposed to tumor-conditioned medium (TCM) over a prolonged period of time assume a CAF-like myofibroblastic phenotype. More importantly, these cells exhibit functional properties of CAFs, including sustained expression of stromal-derived factor-1 (SDF-1) and the ability to promote tumor cell growth both in vitro and in an in vivo coimplantation model, and expression of myofibroblast markers, including alpha-smooth muscle actin and fibroblast surface protein. hMSCs induced to differentiate to a myofibroblast-like phenotype using 5-azacytidine do not promote tumor cell growth as efficiently as hMSCs cultured in TCM nor do they show increased SDF-1 expression. Furthermore, gene expression profiling revealed similarities between TCM-exposed hMSCs and CAFs. Taken together, these data suggest that hMSCs are a source of CAFs and can be used in the modeling of tumor-stroma interactions. To our knowledge, this is the first report showing that hMSCs become activated and resemble carcinoma-associated myofibroblasts on prolonged exposure to conditioned medium from MDAMB231 human breast cancer cells.
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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) | 0.002 | 0.001 |
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".