The KrasG12D;Trp53fl/fl murine model of undifferentiated pleomorphic sarcoma is macrophage dense, lymphocyte poor, and resistant to immune checkpoint blockade
Bibliographic record
Abstract
Sarcomas are rare, difficult to treat, mesenchymal lineage tumours that affect children and adults. Immunologically-based therapies have improved outcomes for numerous adult cancers, however, these therapeutic strategies have been minimally effective in sarcoma so far. Clinically relevant, immunologically-competent, and transplantable pre-clinical sarcoma models are essential to advance sarcoma immunology research. Herein we show that Cre-mediated activation of KrasG12D, and deletion of Trp53, in the hindlimb muscles of C57Bl/6 mice results in the highly penetrant, rapid onset undifferentiated pleomorphic sarcomas (UPS), one of the most common human sarcoma subtypes. Cell lines derived from spontaneous UPS tumours can be reproducibly transplanted into the hindlimbs or lungs of naïve, immune competent syngeneic mice. Immunological characterization of both spontaneous and transplanted UPS tumours demonstrates an immunologically-'quiescent' microenvironment, characterized by a paucity of lymphocytes, limited spontaneous adaptive immune pathways, and dense macrophage infiltrates. Macrophages are the dominant immune population in both spontaneous and transplanted UPS tumours, although compared to spontaneous tumours, transplanted tumours demonstrate increased spontaneous lymphocytic infiltrates. The growth of transplanted UPS tumours is unaffected by host lymphocyte deficiency, and despite strong expression of PD-1 on tumour infiltrating lymphocytes, tumours are resistant to immunological checkpoint blockade. This spontaneous and transplantable immune competent UPS model will be an important experimental tool in the pre-clinical development and evaluation of novel immunotherapeutic approaches for immunologically cold soft tissue sarcomas.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".