Ectonucleotidases in Tumor Cells and Tumor-Associated Immune Cells: An Overview
Bibliographic record
Abstract
Increasing evidence points out that genetic alteration does not guarantee the development of a tumor and indicates that complex interactions of tumor cells with the microenvironment are fundamental to tumorigenesis. Among the pathological alterations that give tumor cells invasive potential, disruption of inflammatory response and the purinergic signaling are emerging as an important component of cancer progression. Nucleotide/nucleoside receptor-mediated cell communication is orchestrated by ectonucleotidases, which efficiently hydrolyze ATP, ADP, and AMP to adenosine. ATP can act as danger signaling whereas adenosine, acts as a negative feedback mechanism to limit inflammation. Many tumors exhibit alterations in ATP-metabolizing enzymes, which may contribute to the pathological events observed in solid cancer. In this paper, the main changes occurring in the expression and activity of ectonucleotidases in tumor cells as well as in tumor-associated immune cells are discussed. Furthermore, we focus on the understanding of the purinergic signaling primarily as exemplified by research done by the group on gliomas.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".