ZNF768 loss amplifies p53 action and reduces lung tumorigenesis in mice
Bibliographic record
Abstract
Abstract Cell proliferation is a fundamental process required for organismal development, growth, and maintenance. Failure to control this process leads to several diseases, including cancer. Zinc finger protein 768 (ZNF768) is an emerging transcription factor that plays key roles in driving proliferation. In addition to controlling a gene network supporting cell division, ZNF768 physically interacts and inhibits the activity of the tumor suppressor p53. Although the importance of ZNF768 in promoting cell proliferation has been well demonstrated in vitro, the physiological and pathological roles of ZNF768 in vivo are still unknown. Here, we report the generation and characterization of a ZNF768 null mouse model. ZNF768 null mice are viable but show a growth defect early in life. Mouse embryonic fibroblasts (MEFs) isolated from ZNF768 null embryos exhibit higher p53 levels, premature senescence, and higher sensitivity to genotoxic stress. In line with these findings, ZNF768 null mice showed increased radiosensitivity. This effect was associated not only with higher expression of a subset of p53 target genes, but also with alterations in genes regulating transmembrane receptor signaling, cell adhesion, and growth. Because ZNF768 levels are elevated in tumors, we tested the impact of ZNF768 loss on cancer development in mice. Here, we show that ZNF768 deletion was sufficient to repress lung tumor development in a KRAS G12D -induced cancer mouse model. Overall, our findings establish ZNF768 as an important protein controlling cell proliferation that could potentially be targeted to reduce tumorigenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".