A novel NOD.SCID mouse model suggests CD200-mediated regulation may be important for both growth and therapy of CLL (165.36)
Bibliographic record
Abstract
Abstract Chronic lymphocytic leukemia is characterized by the accumulation of malignant CD5+CD19+ B cells that, like anergic B cells, typically fail to engraft in immunocompromised murine hosts. CD200, a type I transmembrane molecule with potent immunoregulatory functions, is known to be overexpressed on CLL cells. Using a CD200 sandwich-ELISA, we have identified a soluble form of CD200 (sCD200), whose expression is increased by >5-fold in the serum of CLL patients compared to healthy controls. Further analysis of sCD200 levels in CLL patient serum showed a correlation between sCD200 levels and Rai disease stage. Infusion of sCD200hi CLL serum into NOD.SCIDIL-2γ-/- mice receiving 1x108 CLL splenocytes enhanced engraftment of CLL cells, which were detectable in both the spleen and peritoneum of animals, in comparison to mice receiving sCD200lo normal serum. Enhanced engraftment using CLL serum was abrogated by depletion of sCD200 from the serum. When given at 21 days post-CLL splenocyte infusion, anti-CD200mAb was as effective as Rituximab in eliminating engrafted CLL. In vivo T cell depletion with anti-CD3mAb also suppressed CLL engraftment, despite ongoing CLL serum infusion, suggesting that T cells are important to maintain CLL survival and growth. Our studies show that infusion of sCD200hi CLL serum into NOD.SCID mice allows development of a novel xenograft model for CLL, and further suggest that anti-CD200 mAb may have value in treatment of disease.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".