Importance of CD200 expression by tumor or host cells to regulation of immunotherapy in a mouse breast cancer model
Bibliographic record
Abstract
Cell-surface CD200 expression by mouse EMT6 breast tumor cells increased primary tumor growth and metastasis to the draining lymph nodes (DLN) in normal (WT) BALB/c female recipients, while lack of CD200R1 expression in a CD200R1-/- host negated this effect. Silencing CD200 expression in EMT6siCD200 tumor cells also reduced their ability to grow and metastasize in WT animals. The cellular mechanisms responsible for these effects have not been studied in detail. We report characterization of tumor infiltrating (TILs) and draining lymph node (DLN) cells in WT and CD200-/- BALB/c mice, receiving WT tumor cells, or EMT6 lacking CD200 expression (EMT6siCD200 cells). Our data show an important correlation with augmented CD8+ cytotoxic T cells and resistance to tumor growth in mice lacking exposure (on either host cells or tumor) to the immunoregulatory molecule CD200. Confirmation of the importance of such CD8+ cells came from monitoring tumor growth and characterization of the TILs and DLN cells in WT mice challenged with EMT6 and EMT6siCD200 tumors and treated with CD8 and CD4 depleting antibodies. Finally, we have assessed the mechanisms(s) whereby addition of metformin as an augmenting chemotherapeutic agent in CD200-/- animals given EMT6 tumors and treated with a previously established immunotherapy regime can increase host resistance. Our data support the hypothesis that increased autophagy in the presence of metformin increases CD8+ responses and tumor resistance, an effect attenuated by the autophagy inhibitor verteporfin.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".