Knockout of the ING5 epigenetic regulator confirms roles in stem cell maintenance and tumor suppression in vivo
Bibliographic record
Abstract
INhibitor of Growth (ING1-5) proteins are epigenetic readers that target histone acetyltransferase (HAT) or histone deacetylase (HDAC) complexes to the H3K4Me3 mark of active transcription. ING5 targets Moz/Morf and HBO1 HAT complexes that alter acetylation of H3 and H4 core histones, affecting gene expression. Previous experiments in vitro indicated that ING5 functions to maintain stem cell character in normal and in cancer stem cells. Here we find that CRISPR/Cas9 ING5 knockout (KO) mice are sub-fertile but show no decrease in lifespan or ability to heal wounds despite indications of depleted stem cell pools in several tissues. ING5 KO mouse embryo fibroblasts accumulate in G2 of the cell cycle, have high levels of abnormal nuclei and show high basal levels of the γH2AX indicator of DNA damage. KO animals also develop severe dermatitis at a 5-fold higher rate that wild-type littermates. Consistent with ING5 serving a tumor suppressive role, ING5 KO mice developed germinal centre diffuse large B-cell lymphomas at a rate 6-fold higher than control mice at 18 months of age. These data suggest that ING5 functions in vivo to maintain stem cell character in multiple organs, that reduction of stem cell populations is not limiting for murine lifespan and that like a subset of other ING family members, ING5 functions as a tumor suppressor in hematopoietic cells in vivo.
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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) | 0.002 | 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".