Downregulation of XIAP expression in ovarian cancer cells induces cell death <i>in vitro</i> and <i>in vivo</i>
Bibliographic record
Abstract
A hallmark of cancer cells is an ability to evade apoptosis. Overexpression and/or activating mutations of prosurvival molecules such as the X-linked inhibitor of apoptosis (XIAP) contribute to this inappropriate cell survival. Our objectives were to investigate the effects of downregulation of XIAP in ovarian cancer cells in vitro and in vivo using the clinical candidate antisense oligonucleotide against XIAP, AEG35156 (AS XIAP). Three ovarian cancer cell lines were transfected with AS XIAP in vitro, and the effects on cell survival were assessed. Downregulation of XIAP resulted in significant apoptosis. To investigate the in vivo efficacy of AS XIAP, CD-1 nude mice were xenografted intraperitoneally with A2780-cp cells, treated with intraperitoneal AS XIAP and evaluated for survival time and tumor histology. Mice treated with 10 mg/kg/day AS XIAP showed a significant improvement in survival time compared to animals treated with control oligonucleotides. Histological analysis of the tumors showed significantly fewer viable cells in the AS XIAP-treated tumors. Downregulation of XIAP expression in ovarian cancer cells resulted in apoptosis in vitro and a prolonged survival time of ovarian cancer-bearing mice, which indicate that XIAP may be a valuable therapeutic target in ovarian cancers, and supports the ongoing clinical investigation of AEG35156.
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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".