Targeting of Tumor Cells by Cell Surface Urokinase Plasminogen Activator-dependent Anthrax Toxin
Bibliographic record
Abstract
Urokinase plasminogen activator receptor (uPAR) binds pro-urokinase plasminogen activator (pro-uPA) and thereby localizes it near plasminogen, causing the generation of active uPA and plasmin on the cell surface. uPAR and uPA are overexpressed in a variety of human tumors and tumor cell lines, and expression of uPAR and uPA is highly correlated to tumor invasion and metastasis. To exploit these characteristics in the design of tumor cell-selective cytotoxins, we constructed mutated anthrax toxin-protective antigen (PrAg) proteins in which the furin cleavage site is replaced by sequences cleaved specifically by uPA. These uPA-targeted PrAg proteins were activated selectively on the surface of uPAR-expressing tumor cells in the presence of pro-uPA and plasminogen. The activated PrAg proteins caused internalization of a recombinant cytotoxin, FP59, consisting of anthrax toxin lethal factor residues 1-254 fused to the ADP-ribosylation domain of Pseudomonas exotoxin A, thereby killing the uPAR-expressing tumor cells. The activation and cytotoxicity of these uPA-targeted PrAg proteins were strictly dependent on the integrity of the tumor cell surface-associated plasminogen activation system. We also constructed a mutated PrAg protein that selectively killed tissue plasminogen activator-expressing cells. These mutated PrAg proteins may be useful as new therapeutic agents for cancer treatment.
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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 | 0.000 | 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".