Altered subcellular localization and low frequency of mutations of ING1 in human brain tumors.
Bibliographic record
Abstract
PURPOSE: Clinical and experimental evidence suggest that the p33ING1b candidate tumor suppressor functionally cooperates with p53 in controlling biochemical and biological functions. Because p53 is frequently mutated in brain tumors and the ING1 locus maps to a site of which the loss is associated with gliomas, we analyzed the mutation and expression profiles of ING1B in human brain tumors. Here we present the first report of ING1 expression and mutation analyses in human brain tumor samples and malignant glioma cell lines. EXPERIMENTAL DESIGN: Expression and mutation analyses of ING1B together with subcellular localization studies of ING1 proteins were performed on 29 brain tumor specimens and 6 human glioma cell lines. RESULTS: A single point mutation (3.5%) was detected in the 29 brain tumor specimens analyzed. This missense mutation occurred in a sequence reported previously to confer nuclear translocation properties to p33ING1b. Interestingly, overexpression and subcellular mislocalization of p33ING1b were observed in all 29 of the brain tumor specimens and some glioma cell lines. In tumor samples, ING1 proteins aberrantly localized to the cytoplasm, and to a lesser extent, to the nucleus of glioma cells. CONCLUSIONS: Our data indicate that although mutations of ING1 seem to be infrequent in human brain tumors, deregulated expression and mislocalization of ING1 proteins, particularly the p33ING1b isoform, are common events in gliomas and glioblastomas.
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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 | 0.001 | 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".