Vascular progenitors derived from murine bone marrow stromal cells are regulated by fibroblast growth factor and are avidly recruited by vascularizing tumors
Bibliographic record
Abstract
Bone marrow-derived stromal cells (BMSC) possess a population of vascular progenitor cells that enable them to acquire a histology and immunophenotype coherent with endothelial cells (EC). Recent evidence indicates that a hypoxic environment such as that encountered in tumor masses regulates BMSC angiogenic properties by pathways that remain to be defined. It is also unclear as to what extent these marrow-derived precursor cells could contribute to the growth of endothelium-lined vessels at the vicinity of tumor masses. In this study, we found that BMSC exhibited the ability to generate three-dimensional capillary-like networks on Matrigel, and that this property was up-regulated by growth factors-enriched conditioned media isolated from several tumor-derived cell lines. In particular, basic fibroblast growth factor, a key mediator of angiogenesis, was found to be the most potent growth factor for inducing BMSC proliferation, migration, and tubulogenesis. The setup of a new two-dimensional in vitro co-culture assay further showed that BMSC were massively recruited when cultured in the presence of either cancerous or differentiated EC lines. In vivo, subcutaneous co-injection of BMSC with U-87 glioma cells in nude mice resulted in the formation of highly vascularized tumors, where BMSC differentiated into CD31-positive cells and localized at the lumen of vascular structures. Our data suggest that BMSC could be recruited at the sites of active tumor neovascularization through paracrine regulation of their angiogenic properties. These observations may have crucial implications in the development of novel therapies using BMSC engineered to secrete anti-cancerous agents and to antagonize tumor progression.
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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".