The interplay between the DNA damage response and ectonucleotidases modulates tumor response to therapy
Bibliographic record
Abstract
The extracellular nucleoside adenosine reduces tissue inflammation and is generated by irreversible dephosphorylation of adenosine monophosphate (AMP) mediated by the ectonucleotidase CD73. The pro-inflammatory nucleotides adenosine triphosphate, nicotinamide adenine dinucleotide, and cyclic guanosine -monophosphate-AMP (cGAMP), which are produced in the tumor microenvironment (TME) during therapy-induced immunogenic cell death and activation of innate immune signaling, can be converted into AMP by ectonucleotidases CD39, CD38, and CD203a/ENPP1. Thus, ectonucleotidases shape the TME by converting immune-activating signals into an immunosuppressive one. Ectonucleotidases also hinder the ability of therapies including radiation therapy, which enhance the release of pro-inflammatory nucleotides in the extracellular milieu, to induce immune-mediated tumor rejection. Here, we review the immunosuppressive effects of adenosine and the role of different ectonucleotidases in modulating antitumor immune responses. We discuss emerging opportunities to target adenosine generation and/or its ability to signal via adenosine receptors expressed by immune and cancer cells in the context of combination immunotherapy and radiotherapy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".