Endothelial Progenitor Cells as Shuttle of Anticancer Agents
Bibliographic record
Abstract
Cell therapies are treatments in which stem or progenitor cells are stimulated to differentiate into specialized cells able to home to and repair damaged tissues. After their discovery, endothelial progenitor cells (EPCs) stimulated worldwide interest as possible vehicles to perform autologous cell therapy of tumors. Taking into account the tumor-homing properties of EPCs, two different approaches to control cancer progression have been pursued by combining cell-based therapy with gene therapy or with nanomedicine. The first approach is based on the possibility of engineering EPCs to express different transgenes, and the second is based on the capacity of EPCs to take up nanomaterials. Here we review the most important progress covering the following issues: the characterization of bona fide endothelial progenitor cells, their role in tumor vascularization and metastasis, and preclinical data about their use in cell-based tumor therapy, considering antiangiogenic, suicide, immune-stimulating, and oncolytic virus gene therapy. The mixed approach of EPC cell therapy and nanomedicine is discussed in terms of plasmonic-dependent thermoablation and molecular imaging.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".