ING1a expression increases during replicative senescence and induces a senescent phenotype
Bibliographic record
Abstract
The ING family of tumor suppressor proteins affects cell growth, apoptosis and response to DNA damage by modulating chromatin structure through association with different HAT and HDAC complexes. The major splicing isoforms of the ING1 locus are ING1a and INGlb. While INGlb plays a role in inducing apoptosis, the function of ING1a is currently unknown. Here we show that alternative splicing of the ING1 message alters the INGla:INGlb ratio by approximately 30-fold in senescent compared to low passage primary fibroblasts. INGla antagonizes INGlb function in apoptosis, induces the formation of structures resembling senescence-associated heterochromatic foci containing heterochromatin protein 1 gamma, the accumulation of senescence-associated beta-galactosidase activity and promotes senescent cell morphology and cell cycle arrest. Phenotypic effects may result from differential effects on gene expression since ING1a increases levels of both retinoblastoma and the p16 cyclin-dependent kinase inhibitor and ING1a and ING1b have opposite effects on the expression of proliferating nuclear cell antigen (PCNA), which is required for cell growth. Gene expression appears to be altered by targeting of HDAC complexes to gene promoters since INGla associates with several-fold higher levels of HDAC1 in senescent, compared to replication-competent cells and ING1 is found on the PCNA promoter by chromatin immunoprecipitation analysis. These data demonstrate a novel role for the ING1 proteins in differentially regulating senescence-associated chromatin remodeling vs. apoptosis and support the idea that altered ratios of the ING1 splicing isoforms may contribute to establishing the senescent phenotype through HDAC and HAT complex-mediated effects on chromatin structure.
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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) | 0.002 | 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".