X-Linked Inhibitor of Apoptosis Protein Levels and Protein Kinase C Activity Regulate the Sensitivity of Human Endometrial Carcinoma Cells to Tumor Necrosis Factorα-Induced Apoptosis
Bibliographic record
Abstract
Endometrial carcinomas are often chemoresistant. TNFalpha shows potent antitumor activity against various cancers, and if it demonstrates good antitumor activity against endometrial cancer, the cytokine could represent a valuable alternative therapeutic approach. We have tested the ability of TNFalpha to induce apoptosis in endometrial carcinoma cells, and examined a putative role for X-linked inhibitor of apoptosis protein (XIAP) in regulating cellular sensitivity to the cytokine. Exposure to TNFalpha triggered TNF-R1-dependent activation of caspases-8, -9, and -3, down-regulated Akt and XIAP proteins and induced dose-dependent and time-dependent apoptosis in Ishikawa cells. On the opposite, TNFalpha up-regulated XIAP in Hec-1A cells; in these cells, the cytokine induced delayed TNF-R1-dependent activation of caspase-8, and failed to activate caspases -9 and -3 and to induce apoptosis. However, XIAP small interfering RNA restored TNFalpha-induced caspase signaling and apoptosis in Hec-1A cells; XIAP small interfering RNA also increased TNFalpha-induced apoptosis in Ishikawa cells. In addition, inhibition of protein kinase C activity enhanced TNFalpha-induced down-regulation of XIAP and potentiated apoptosis induction, in both Ishikawa and Hec-1A cells. Finally, we found XIAP immunoreactivity in epithelial cells from a large number of human endometrial tumor tissue samples, indicating that XIAP is produced by endometrial tumor cells in vivo. This could allow XIAP to play a putative in vivo role in counteracting TNFalpha-induced apoptosis in endometrial tumor cells; in this case, direct or indirect targeting of XIAP should potentiate the antitumor effect of TNFalpha.
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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".