Silencing SATB1 Inhibits the Malignant Phenotype and Increases Sensitivity of Human Osteosarcoma U2OS Cells to Arsenic Trioxide
Bibliographic record
Abstract
In a previous study, we found that the global genome organizer Special AT-rich binding protein 1 (SATB1) is highly expressed in mesenchymal-derived human osteosarcoma U2OS cells and that the knock-down of SATB1 results in the inhibition of cell proliferation. The present study was aimed at investigating the effect of silencing SATB1 on cell migration, invasion, apoptosis and resistance to the chemotherapeutic drug arsenic trioxide. Cell migration and invasion were detected by wound-healing assays and trans-well invasion assays, respectively. Cell apoptosis was analyzed by an in situ Cell Death Detection POD Kit, based on terminal deoxynucleotydyl transferase mediated dUTP nick-end labeling (TUNEL) staining and mRNAs were analyzed by real time qRT-PCR. We found that cell migration and invasion were inhibited and that the proportion of apoptotic cells and sensitivities to the chemotherapeutic drug arsenic trioxide were enhanced by knockdown of SATB1 in U2OS cells. Furthermore, mRNA of ABCC1 and ABCG2 were decreased strikingly after SATB1 silencing. It was concluded that the elevated expression of SATB1 in U2OS cells contributes to maintenance of the malignant phenotype and resistance to chemotherapeutic drugs ATO, suggesting that silencing SATB1 in the cells might improve the effects of arsenic trioxides in the treatment of osteosarcoma in which SATB1 is over-expressed and that ABCC1 and ABCG2 were involved in SATB1 mediated resistance of U2OS cells to ATO.
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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".