Ecto-5’-Nucleotidase Overexpression Reduces Tumor Growth in a Xenograph Medulloblastoma Model
Bibliographic record
Abstract
BACKGROUND: Ecto-5'-nucleotidase/CD73 (ecto-5'-NT) participates in extracellular ATP catabolism by converting adenosine monophosphate (AMP) into adenosine. This enzyme affects the progression and invasiveness of different tumors. Furthermore, the expression of ecto-5'-NT has also been suggested as a favorable prognostic marker, attributing to this enzyme contradictory functions in cancer. Medulloblastoma (MB) is the most common brain tumor of the cerebellum and affects mainly children. MATERIALS AND METHODS: The effects of ecto-5'-NT overexpression on human MB tumor growth were studied in an in vivo model. Balb/c immunodeficient (nude) 6 to 14-week-old mice were used for dorsal subcutaneous xenograph tumor implant. Tumor development was evaluated by pathophysiological analysis. In addition, the expression patterns of adenosine receptors were verified. RESULTS: The human MB cell line D283, transfected with ecto-5'-NT (D283hCD73), revealed reduced tumor growth compared to the original cell line transfected with an empty vector. D283hCD73 generated tumors with a reduced proliferative index, lower vascularization, the presence of differentiated cells and increased active caspase-3 expression. Prominent A1 adenosine receptor expression rates were detected in MB cells overexpressing ecto-5'-NT. CONCLUSION: This work suggests that ecto-5'-NT promotes reduced tumor growth to reduce cell proliferation and vascularization, promote higher differentiation rates and initiate apoptosis, supposedly by accumulating adenosine, which then acts through A1 adenosine receptors. Therefore, ecto-5'-NT might be considered an important prognostic marker, being associated with good prognosis and used as a potential target for therapy.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".