Galectins in Glioma: Current Roles in Cancer Progression and Future Directions for Improving Treatment
Bibliographic record
Abstract
Traditional wisdom suggests that galectins play pivotal roles at different steps in cancer progression. Galectins are particularly well known for their ability to increase the invasiveness of cancer cells and their resistance to drug-induced cell death. They also contribute to the development of local and systemic immunosuppression, allowing cancer cells to escape the host's immunological defense. This is particularly true in glioma, the most common primary intracranial tumor. Abnormally high production of extracellular galectins in glioma contributes to the establishment of a strong immunosuppressive environment that favors immune escape and tumor progression. Considering the recent development and success of immunotherapy in halting cancer progression, it is logical to foresee that galectin-specific drugs may help to improve the success rate of immunotherapy for glioma. This provides a new perspective to target galectins, whose intracellular roles in cancer progression have already been investigated thoroughly. In this review, we discuss the mechanisms of action of galectins at different steps of glioma progression and the potential of galectin-specific drugs for the treatment of glioma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.003 | 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".