Translational Regulation of X-Linked Inhibitor of Apoptosis Protein by Interleukin-6
Bibliographic record
Abstract
Interleukin-6 (IL-6) is a pleiotropic cytokine with diverse biological effects. IL-6 has been implicated in autocrine signaling pathways promoting tumor progression and chemoresistance in some human tumors. However, the mechanisms by which IL-6 modulates these responses are unknown. Aberrant apoptosis has been implicated as a fundamental mechanism of chemotherapeutic resistance. Thus, we investigated whether IL-6 alters the expression of apoptosis regulatory proteins as a mechanism of drug resistance. We provide evidence that IL-6 rapidly phosphorylates the translation initiation factor eukaryotic initiation factor-4E and triggers antiapoptotic responses in cholangiocarcinoma cells. Reduction of cellular eukaryotic initiation factor-4E by RNA interference decreases IL-6-induced effects on cytotoxic drug-induced caspase activation and apoptosis. Furthermore, IL-6 increases expression of the endogenous X-linked inhibitor of apoptosis protein expression by translation at an internal ribosome entry site. Our findings that IL-6 translationally regulates X-linked inhibitor of apoptosis protein expression reveal a novel mechanism by which IL-6 mediates tumor cell survival that may be targeted therapeutically to decrease tumor progression and chemoresistance.
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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".