Immunodeficient Mouse Strains Display Marked Variability in Growth of Human Melanoma Lung Metastases
Bibliographic record
Abstract
PURPOSE: Immunodeficient mice serve as critical hosts for transplantation of xenogeneic cells for in vivo analysis of various biological processes. Because investigators typically select one or two immunodeficient mouse strains as recipients, no comprehensive study has been published documenting differences in human tumor engraftment. Taking advantage of the increased metastatic potential of RhoC-expressing human (A375) melanoma cells, we evaluate four immunodeficient mouse strains: severe combined immunodeficiency (scid), nonobese diabetic (NOD)-scid, NOD-scid beta2m(null), and NOD-scid IL2Rgamma(null) as xenograft tumor recipients. EXPERIMENTAL DESIGN: Bioluminescence, magnetic resonance imaging, and histopathology were used to monitor serial tumor growth. Natural killer (NK) cell function was examined in each mouse strain using standard (51)Chromium release assays. RESULTS: Melanoma metastases growth is delayed and variable in scid and NOD-scid mice. In contrast, NOD-scid beta2m(null) and NOD-scid IL2Rgamma(null) mice show rapid tumor engraftment, although tumor growth is variable in NOD-scid beta2m(null) mice. NK cells were detected in all strains except NOD-scid IL2Rgamma(null), and in vitro activated scid, NOD-scid, and NOD-scid beta2m(null) NK cells kill human melanoma lines and primary melanoma cells. Expression of human NKG2D ligands MHC class I chain-related A and B molecules renders melanoma susceptible to murine NK cell-mediated cytotoxicity and killing is inhibited by antibody blockade of murine NKG2D. CONCLUSIONS: Murine NKG2D recognition of MICA/B is an important receptor-ligand interaction used by NK cells in immunodeficient strains to limit engraftment of human tumors. The absolute NK deficiency in NOD-scid IL2Rgamma(null) animals makes this strain an excellent recipient of melanoma and potentially other human malignancies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".