The Inhibitor of Growth 1 (ING1) Proteins Suppress Angiogenesis and Differentially Regulate Angiopoietin Expression in Glioblastoma Cells
Bibliographic record
Abstract
The inhibitor of growth 1 (ING1) homologue ING4 has previously been implicated as a negative regulator of angiogenesis in a murine glioma and a multiple myeloma model. An association between ING1 and angiogenesis has not been reported yet. Our previous studies using tumor samples from patients have shown that ING1 levels are downregulated in glioblastoma multiforme (GBM), one of the most highly vascularized malignancies. Based on this background, the goal of this study was to test the effects of the major ING1 splicing isoforms, p47ING1a and p33ING1b, on pathological angiogenesis induced by human GBM cells. We used a chorioallantoic membrane (CAM) assay to examine whether LN229 human GBM cells can induce angiogenesis and whether alterations in ING1 expression, such as ING1 knockdown by siRNA or ectopic ING1 overexpression using ING1a and ING1b expression constructs, can affect this process. Increased ING1 protein expression significantly suppressed LN229 cell-induced angiogenesis in the CAM assay. While no effects on the proangiogenic factors VEGF or IL-8 were noted, the expression of angiopoietins (Ang) 1 and 4 were increased by the p47ING1a, but not by the p33ING1b isoform. Levels of Ang-2 were not sensitive to altered ING1 levels. Our data are the first to suggest that ING1 proteins suppress neoangiogenesis in GBM. Moreover, our results may support the idea that ING1 proteins regulate the expression of proteins that are critical for angiogenesis in GBM such as the angiopoietins.
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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".