O-GlcNAcylation of FOXK1 co-opts BAP1 to orchestrate the E2F pathway and promotes oncogenesis
Bibliographic record
Abstract
The E2F transcription factors constitute a core transcriptional network that governs cell division and oncogenesis in multi-cellular organisms, although their molecular mechanisms remain incompletely understood. Here, we show that elevated expression of the transcription factor FOXK1 promotes transcription of E2F target genes and cellular transformation. High expression of FOXK1 in patient tumors is also strongly correlated with E2F gene expression. Mechanistically, we demonstrate that FOXK1 is O-GlcNAcylated, and loss of this modification impairs FOXK1 ability to promote cell proliferation and tumor growth. We also show that expression of FOXK1 O-GlcNAcylation-defective mutants results in reduced recruitment of the H2AK119 deubiquitinase and tumor suppressor BAP1 to E2F target genes. This event is associated with a transcriptional repressive chromatin environment and reduced cell proliferation. Our results define an essential role of FOXK1 O-GlcNAcylation in co-opting the tumor suppressor BAP1 to promote cancer cell progression through orchestration of the E2F pathway. The regulation of the E2F pathway remains incompletely established. Here the authors find that the O-GlcNAcylated FOXK1 associates with the deubiquitinase BAP1 to upregulate transcription of E2F target genes and promote cancer progression.
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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".