The transcription factor SP3 drives TNF-α expression in response to Smac mimetics
Bibliographic record
Abstract
The controlled production and downstream signaling of the inflammatory cytokine tumor necrosis factor-α (TNF-α) are important for immunity and its anticancer effects. Although chronic stimulation with TNF-α is detrimental to the health of the host in several autoimmune and inflammatory disorders, TNF-α-contrary to what its name implies-leads to cancer formation by promoting cell proliferation and survival. Smac mimetic compounds (SMCs), small-molecule antagonists of inhibitor of apoptosis proteins (IAPs), switch the TNF-α signal from promoting survival to promoting death in cancer cells. Using a genome-wide siRNA screen to identify factors required for SMC-to-TNF-α-mediated cancer cell death, we identified the transcription factor SP3 as a critical molecule in both basal and SMC-induced production of TNF-α by engaging the nuclear factor κB (NF-κB) transcriptional pathway. Moreover, the promotion of TNF-α expression by SP3 activity confers differential sensitivity of cancer versus normal cells to SMC treatment. The key role of SP3 in TNF-α production and signaling will help us further understand TNF-α biology and provide insight into mechanisms relevant to cancer and inflammatory disease.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".