Inhibition of MMP‐1 expression by antisense RNA decreases invasiveness of human chondrosarcoma
Bibliographic record
Abstract
We previously reported that an elevated level of matrix metalloproteinase-1 (MMP-1) gene expression in patients with chondrosarcoma has a strong statistical correlation with recurrence and in vitro invasion. In the present study, we used an antisense RNA strategy for MMP-1 inhibition to determine if this would affect the invasive characteristics of the cells. We transfected a human chondrosarcoma cell line with a retroviral plasmid expressing a 770 bp genomic fragment of the human MMP-1 gene in the sense or antisense orientation. The results show that cells transfected with the MMP-1 antisense fragment had a significant decrease in both MMP-1 protein and enzyme activity (p<0.05) as compared to cells transfected with an empty plasmid or the parental cells. Cells transfected with the MMP-1 antisense fragment demonstrated a significant decrease in their ability to invade the collagen I barrier (p<0.05). The gene expression for MMP-8 and MMP-13 were unaffected in cells transfected with the MMP-1 antisense fragment, MMP-1 sense fragment, or empty plasmid. These results support the hypothesis that MMP-1 facilitates tumor cell egress from chondrosarcoma tissue and demonstrate the potential of MMP-1 as a promising target for a novel biologic therapy in chondrosarcoma.
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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".