Plasminogen Kringle 5 blocks tumor progression by antiangiogenic and proinflammatory pathways
Bibliographic record
Abstract
Proteolytic processing of human plasminogen generates potent antiangiogenic peptides such as angiostatin. The plasminogen kringle 5 (K5) domain, which is distinct from angiostatin, possesses potent antiangiogenic properties on its own, which can be exploited in cancer therapy. It has been recently observed that antiangiogenic agents promote leukocyte-vessel wall interaction as part of their antitumor effect. Although we have previously shown that K5 suppresses cancer growth in tumor xenograft models, its modulation of inflammation in experimental mice with intact immune systems is unknown. To determine whether K5 possesses immune proinflammatory properties, we investigated the effects of K5 in an immune competent model of breast cancer and observed that tumor rejection is substantially reduced in nonobese diabetic/severe combined immunodeficient and BALB/c nude when compared with wild-type BALB/c mice, suggesting an important role for T-lymphoid cells in the antitumor effect of K5. Tumor explant analysis shows that K5 enhances tumor recruitment of CD3(+) lymphoid cells, in particular, the NKT phenotype. We also observed a significant decrease in tumor-associated microvessel length and density consistent with antiangiogenic activity. Histologic analysis of K5 tumors also revealed a robust neutrophilic infiltrate, which may be explained by the neutrophil chemotactic activity of K5 as well as its ability to promote CD64 up-regulation within the CD11b(+) adhesive neutrophil population. In sum, our findings confirm that the K5 protein acts as a potent angiostatic agent and possesses a novel proinflammatory role via its ability to recruit tumor-associated neutrophils and NKT lymphocytes, leading to a potent antitumor response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".