Biological Functions of the ING Proteins
Bibliographic record
Abstract
The proteins belonging to the inhibitor of growth (ING) family of proteins serve as epigenetic readers of the H3K4Me3 histone mark of active gene transcription and target histone acetyltransferase (HAT) or histone deacetylase (HDAC) protein complexes, in order to alter local chromatin structure. These multidomain adaptor proteins interact with numerous other proteins to facilitate their localization and the regulation of numerous biochemical pathways that impinge upon biological functions. Knockout of some of the ING genes in murine models by various groups has verified their status as tumor suppressors, with ING1 knockout resulting in the formation of large clear-cell B-lymphomas and ING2 knockout increasing the frequency of ameloblastomas, among other phenotypic effects. ING4 knockout strongly affects innate immunity and angiogenesis, and INGs1, ING2, and ING4 have been reported to affect apoptosis in different cellular models. Although ING3 and ING5 knockouts have yet to be published, preliminary reports indicate that ING3 knockout results in embryonic lethality and that ING5 knockout may have postpartum effects on stem cell maintenance. In this review, we compile the known information on the domains of the INGs and the effects of altering ING protein expression, to better understand the functions of this adaptor protein family and its possible uses for targeted cancer therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".