CD73 Promotes Chronic Lymphocytic Leukemia
Bibliographic record
Abstract
The ecto-nucleotidase CD73 is an important immune checkpoint in tumor immunity that cooperates with CD39 to hydrolyze pro-inflammatory extracellular ATP into immunosuppressive adenosine. While the role of CD73 in immune evasion of solid cancers is well established, its role in leukemia remains unclear. To investigate the role of CD73 in the pathogenesis of chronic lymphocytic leukemia (CLL), Eµ-TCL1 transgenic mice that spontaneously develop CLL were crossed with CD73−/− mice. Disease progression in peripheral blood and spleen, and CLL markers were evaluated by flow cytometry and survival was compared to CD73-proficient Eµ-TCL1 transgenic mice. We observed that CD73 deficiency significantly delayed CLL progression and prolonged survival in Eµ-TCL1 transgenic mice, and was associated with increased accumulation of IFN-γ+ T cells and effector-memory CD8+ T cells. Neutralizing IFN-γ abrogated the survival advantage of CD73-deficient Eµ-TCL1 mice. Intriguingly, the beneficial effects of CD73 deletion were restricted to male mice. In females, CD73 deficiency was uniquely associated with the upregulation of CD39 in normal lymphocytes and sustained high PD-L1 expression on CLL cells. In vitro studies revealed that adenosine signaling via the A2a receptor enhanced PD-L1 expression on Eµ-TCL1-derived CLL cells, and a genomic analysis of human CLL samples found that PD-L1 correlated with adenosine signaling. Our study, thus, identified CD73 as a pro-leukemic immune checkpoint in CLL and uncovered a previously unknown sex bias for the CD73-adenosine pathway.
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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) | 0.000 | 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) | 0.004 | 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".