CD73-Deficient Mice Are Resistant to Carcinogenesis
Bibliographic record
Abstract
CD73 is a cell surface 5'-nucleotidase that converts AMP to adenosine, an immune suppressive molecule. CD73 may promote immune escape in cancer by contributing to the degradation of extracellular ATP released by dying cancer cells in hypoxic tumors or following chemotherapy. However, whether CD73 exerts a critical oncogenic function during tumorigenesis is unknown. In this study, we used genetically deficient mice to investigate its contribution to autochthonous tumor formation. CD73 deficiency suppressed the development of 3-methylcholanthrene (MCA)-induced fibrosarcomas through a mechanism relying upon IFN-γ, natural killer (NK) cells, and CD8(+) T cells. Similarly, CD73 deficiency also suppressed prostate tumorigenesis in TRAMP transgenic mice. Importantly, treatment with an anti-CD73 monoclonal antibody effectively suppressed growth of established MCA-induced tumors or TRAMP-C1 prostate tumors and inhibited the development of TRAMP-C1 lung metastases. The therapeutic activity of anti-CD73 monoclonal antibody against primary tumors was dependent on CD8(+) T cells, whereas its antimetastatic activity was dependent on host CD73 expression independent of T cells or NK cells. Taken together, our findings indicate that CD73 is a critical factor in tumorigenesis and that anti-CD73 antibodies may offer a novel generalized strategy to blunt immune escape and treat cancer.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".