Defining the minimal peptide sequence of the ING1b tumour suppressor capable of efficiently inducing apoptosis
Why this work is in the frame
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Bibliographic record
Abstract
The ING1b protein is a type-II tumour suppressor and stoichiometric member of the Sin3 histone deacetylase (HDAC) protein complex in which it acts to target HDAC activity to regulate chromatin structure. Altering ING1 levels by ectopic expression of ING1b in cancer cells promotes apoptosis, whereas altering levels by knockout in normal murine fibroblasts alters sensitivity to doxorubicin-induced apoptosis. We have identified a minimal region of ING1b capable of inducing levels of apoptosis in targeted cells as effectively as full-length ING1b, using transient overexpression of ING1b fragments followed by the Annexin V assay. We observed high levels of apoptosis in 14 of 14 cancer cell lines tested. Infecting triple-negative tumorigenic MDA-MB-468 breast cancer, U2OS or Saos-2 cells at multiplicities of infection (MOIs) ranging from 10 to 20 rapidly triggered apoptosis in ~80% of infected cells within 48 h. This was not due to the effects of virus, as infection at the same MOI with a control adenovirus expressing GFP was not effective in inducing apoptosis. When used at low MOIs, the ING1b fragment showed a cell-killing efficacy that was higher than native, full-length ING1b. Using a doxycycline-regulated inducible p53 expression system demonstrated that apoptosis induced by the ING1b fragment was p53 independent. Given the growing importance of combination therapies, we evaluated whether there was synergism between the ING1b fragment and HDAC inhibitors. Combination treatments with TSA, LBH 589 and SAHA reduced cancer cell survival by 3.9-4.7-fold as compared with single-drug treatment, and resulted in ~90% reduction in cell survival. Normalized isobologram analysis confirmed strong synergism between the ING1b fragment and drugs tested. These findings provide support for using ING1b-derived therapeutics as adjuvant treatments in combination with existing epigenetic therapies.
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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 | 0.001 | 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 it