A Novel Function for Galectin-7: Promoting Tumorigenesis by Up-regulating<i>MMP-9</i>Gene Expression
Bibliographic record
Abstract
Metastasis is a multistep process by which cancer cells, after acquiring several capabilities, spread to distinct sites in the body. It is the major cause of death in individuals suffering from cancer. We have recently identified galectin-7 as a new gene associated with the progression of T cell lymphoma toward a metastatic phenotype, suggesting a possible causal relationship. The present study was designed to investigate the role of galectin-7 in lymphoma. We found that the development of thymic lymphoma was accelerated when induced by lymphoma cells overexpressing galectin-7. Moreover, transfection of an expression vector containing the galectin-7 gene in low metastatic lymphoma cells increased their metastatic behavior and confers these cells with the new ability to overcome the resistance of intercellular adhesion molecule-1-deficient mice to lymphoma dissemination. Finally, we provide data suggesting that galectin-7 modulates the aggressive behavior of lymphoma cells by controlling the expression of metastatic genes, such as MMP-9. This hypothesis is based on the following evidence: (a) galectin-7 transfectants have higher levels of MMP-9 expression, (b) addition of beta-lactose completely inhibits expression of MMP-9 by galectin-7 transfectants, and (c) recombinant forms of galectin-7 induces the expression of MMP-9 in both mouse and human lymphoma cells. Our results have uncovered the existence of a previously undescribed activity, the promotion of cancer cell malignancy, to galectin-7.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".