SMG1 and NIK regulate apoptosis induced by Smac mimetic compounds
Bibliographic record
Abstract
Smac mimetic compounds (SMCs) are experimental small molecules that induce tumour necrosis factor alpha (TNFα)-dependent cancer cell death by targeting the inhibitor of apoptosis proteins. However, many cancer cell lines are resistant to SMC-mediated apoptosis despite the presence of TNFα. To add insight into the mechanism of SMC-resistance, we used functional siRNA-based kinomic and focused chemical screens and identified suppressor of morphogenesis in genitalia-1 (SMG1) and NF-κB-inducing kinase (NIK) as novel protective factors. Both SMG1 and NIK prevent SMC-mediated apoptosis likely by maintaining FLICE inhibitory protein (c-FLIP) levels to suppress caspase-8 activation. In SMC-resistant cells, the accumulation of NIK upon SMC treatment enhanced the activity of both the classical and alternative nuclear factor-κB pathways, and increased c-FLIP mRNA levels. In parallel, persistent SMG1 expression in SMC-resistant cells repressed SMC-mediated TNFα-induced JNK activation and c-FLIP levels were sustained. Importantly, SMC-resistance is overcome by depleting NIK and SMG1, which appear to facilitate the downregulation of c-FLIP in response to SMC and TNFα treatment, leading to caspase-8-dependent apoptosis. Collectively, these data show that SMG1 and NIK function as critical repressors of SMC-mediated apoptosis by potentially converging on the regulation of c-FLIP metabolism.
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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 | 0.000 | 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) | 0.000 | 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".