Bone sialoprotein stimulates focal adhesion‐related signaling pathways: Role in migration and survival of breast and prostate cancer cells
Bibliographic record
Abstract
Bone sialoprotein (BSP) is a secreted glycoprotein found in mineralized tissues however, BSP is aberrantly expressed in a variety of osteotropic tumors. Elevated BSP expression in breast and prostate primary carcinomas is directly correlated with increased bone metastases and tumor progression. In this study, the intracellular signaling pathways responsible for BSP-induced migration and tumor survival were examined in breast and prostate cancer cells (MDA-MB-231, Hs578T and PC3). Additionally, the effects of exogenous TGF-beta1 and EGF, cytokines associated with tumor metastasis and present in high-levels in the bone microenvironment, were examined in BSP-expressing cancer cells. Expression of BSP but not an integrin-binding mutant (BSP-KAE) in tumor cell lines resulted in increased levels of alpha(v)-containing integrins and number of mature focal adhesions. Adhesion of cells to recombinant BSP or the expression of BSP stimulated focal adhesion kinase and ERK phosphorylation, as well as activated AP-1-family proteins. Activation of these pathways by BSP expression increased the expression of the matrix metalloproteinases MMP-2, MMP-9, and MMP-14. The BSP-mediated activation of the FAK-associated pathway resulted in increased cancer cell invasion in a Matrigel-coated Boyden-chamber assay and increased cell survival upon withdrawal of serum. Addition of EGF or TGF-beta1 to the BSP-expressing cell lines significantly increased ERK phosphorylation, AP-1 activation, MMP-2 expression, cell migration and survival compared to untreated cells expressing BSP. This study thus defines the cooperative mechanisms by which BSP can enhance specific factors associated with a metastatic phenotype in tumor cell lines, an effect that is increased by circulating TGF-beta1 and EGF.
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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) | 0.002 | 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".