CD200fc enhances anti-tumoral immune response and inhibits visceral metastasis of breast carcinoma
Bibliographic record
Abstract
// Nuray Erin 1 , Gamze Tanrıöver 2 , Anna Curry 3 , Muhlis Akman 1 , Özlem Duymuş 1 and Reg Gorczynski 3 1 Department of Medical Pharmacology, Akdeniz University, School of Medicine, Antalya, Turkey 2 Histology and Embryology, Akdeniz University, School of Medicine, Antalya, Turkey 3 University Health Network, Toronto General Hospital, Toronto, Canada Correspondence to: Nuray Erin, email: nerin@akdeniz.edu.tr Keywords: CD200fc; lung metastasis; liver metastasis; breast cancer Received: August 21, 2017 Accepted: February 28, 2018 Published: April 10, 2018 ABSTRACT CD200 is a widely expressed cell surface glycoprotein that inhibits excessive inflammation in autoimmunity, transplantation, and viral infections. We previously observed that visceral metastasis of highly aggressive and inflammatory 4THM breast carcinoma cells was markedly decreased in CD200 transgenic mice. The goal of this study was to determine whether exogenous exposure to CD200fc mimics the effects of endogenously over expressed CD200. Female BALB/c mice were injected with CD200fc two times a week for five times. Injection was started two days after orthotopic injection of 4THM cells. Tumor infiltrating Gr1+Cd11b+ cells were decreased while CD8+ cells were increased in CD200fc-treated animals. CD200fc injection significantly decreased lung and liver metastasis and the growth of primary tumors. CD200fc injection enhanced the tumor-induced IFN-g response while suppressing the IL-10 response. We observed excessive basal IL-6 secretion in MLC which was significantly decreased in CD200fc treated mice 12 days after injection of 4TM cells. These results are in accord with previous data from CD200 transgenic mice, and demonstrate for the first time that CD200 analogues might have therapeutic potential in the treatment of aggressive breast carcinoma which induces excessive systemic inflammation.
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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".