Introduction of <i>Clusterin</i> Gene into Human Renal Cell Carcinoma Cells Enhances Their Resistance to Cytotoxic Chemotherapy through Inhibition of Apoptosis both <i>in vitro</i> and <i>in vivo</i>
Bibliographic record
Abstract
Recent studies have revealed the powerful antiapoptotic activity of clusterin in various malignant tumors; however, the significance of clusterin expression in the acquisition of a resistant phenotype against several kinds of treatment in human renal cell carcinoma (RCC) has not been well characterized. We, therefore, transfected the clusterin cDNA into RCC ACHN cells, that scarcely express clusterin protein, to examine whether overexpression of clusterin inhibits chemotherapy-induced apoptosis both in vitro and in vivo. Although no significant differences were observed in the in vitro growth rates between clusterin-transfected ACHN (ACHN/CL) and the vector only-transfected cell line (ACHN/Co), ACHN/CL exhibited high resistance to cisplatin treatment compared with ACHN/Co, with a greater than 5-fold higher IC(50) through the inhibition of apoptotic cell death, which was demonstrated by DNA fragmentation analysis and western blotting of PARP protein. Moreover, intravenous administration of cisplatin into athymic nude mice bearing ACHN/CL tumors resulted in 2- to 3-times faster tumor growth compared with ACHN/Co tumors. These findings suggest that clusterin overexpression helps confer a chemoresistant phenotype through inhibition of apoptosis in human RCC cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".