Human Ovarian Cancer and Cisplatin Resistance: Possible Role of Inhibitor of Apoptosis Proteins<sup>1</sup>
Bibliographic record
Abstract
The inhibitor of apoptosis proteins (IAPs) constitutes a family of highly conserved apoptosis suppressor proteins that were originally identified in baculoviruses. Although IAP homologs have recently been demonstrated to suppress apoptosis in mammalian cells, their expression and role in human ovarian epithelial cancer and chemotherapy resistance are unknown. In the present study we used cisplatin-sensitive and -resistant human ovarian surface epithelial (hOSE) cancer cell lines and adenoviral antisense and sense complementary DNA expression to examine the role of IAP in the regulation of apoptosis in human ovarian cancer cells and chemoresistance. Antisense down-regulation of X-linked inhibitor of apoptosis protein (Xiap), but not human inhibitor of apoptosis protein-2 (Hiap-2), induced apoptosis in cisplatin-sensitive and, to a lesser extent, in -resistant cells. Cisplatin consistently decreased Xiap content and induced apoptosis in the cisplatin-sensitive, but not cisplatin-resistant, cells. Hiap-2 expression was either unaffected or inhibited to a lesser extent. The inhibition of IAP protein expression and induction of apoptosis by cisplatin was time and concentration dependent. Infection of cisplatin-sensitive cells with adenoviral sense Xiap complementary DNA resulted in overexpression of Xiap and markedly attenuated the ability of cisplatin to induce apoptosis. Immunohistochemical localization of the IAPs in hOSE tumors demonstrated the presence of Xiap and Hiap-2, with their levels being highest in proliferative, but not apoptotic, epithelial cells. These studies indicate that Xiap is an important element in the control of ovarian tumor growth and may be a point of regulation for cisplatin in the induction of apoptosis. These results suggest that the ability of cisplatin to down-regulate Xiap content may be an important determinant of chemosensitivity in hOSE cancer.
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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".