Osteopontin Induction of Hyaluronan Synthase 2 Expression Promotes Breast Cancer Malignancy
Bibliographic record
Abstract
Osteopontin (OPN) is a tumor-associated, secreted phosphoprotein that has been implicated in breast cancer progression and metastasis. Research concerning how OPN functions in tumor progression has led to the identification of a limited number of genes that contribute functionally to OPN-induced cellular behaviors. Recent microarray analysis, comparing 21NT breast cancer cells transfected to constitutively overexpress OPN with control cells, revealed hyaluronan synthase 2 (HAS2) to be a gene highly up-regulated in OPN-overexpressing cells. In this study, we further examined the relationship between OPN and HAS2. We show that 21NT OPN-transfected cells express high levels of HAS2, which is associated with increased HA production and matrix retention and is necessary for tumor cell adhesion to bone marrow endothelial cells and anchorage-independent growth. Finally, stable transfection of antisense HAS2 into 21NT cells overexpressing OPN resulted in a reduction in HAS2 expression, HA production, and pericellular retention. Antisense-mediated down-regulation of HAS2 also resulted in a significant decrease in cellular proliferation and colony growth in soft agar. To our knowledge, this is the first report of the ability of OPN to regulate HAS2 expression and HA production in breast cancer cells and further illustrates a unique functional relationship by which enhanced HA production facilitates OPN-mediated cell behaviors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".