Interaction of <scp>TFAP2A</scp> with the Ku70/80 complex is crucial for <scp>HIF</scp>‐dependent activation of hypoxia‐inducible genes
Bibliographic record
Abstract
Hypoxia can be established under pathological conditions, such as cancer, due to the imbalance between oxygen supply and consumption. Hypoxia-inducible transcription factor HIF-1 mediates the physiological response to hypoxia but also regulates multiple steps of carcinogenesis. Despite its well-defined oxygen-dependent activation, many aspects of HIF-1 transcriptional activity as well as interaction with chromatin remain elusive. We have recently shown that hypoxia triggered deSUMOylation of TFAP2A. To study the possible role of TFAP2A in the transcriptional response to hypoxia, we performed ChIP-seq analysis. Our results have now shown that TFAP2A resides together with HIF-1α on the promoters of a subset of hypoxia-regulated genes, the mRNA expression of which is downregulated by silencing of TFAP2A. Interestingly, CRISPR-mediated knockdown of TFAP2A expression under hypoxia decreased the occupancy of HIF-1α on these promoters and affected chromatin accessibility. Mechanistically, we reveal that the Ku70/Ku80 protein complex interacts with deSUMOylated TFAP2A under hypoxia and participates in HIF-dependent gene expression. Moreover, using stable expression of TFAP2A forms that either lack or constitutively carry a SUMO modification, we could show that SUMOylation affects binding of TFAP2A to chromatin. Overall, our data suggest that TFAP2A is an important co-regulator of the HIF-1-dependent transcriptional response to hypoxia and SUMOylation fine-tunes this regulation. As both TFAP2A and HIF-1 play critical roles in cancer progression, a detailed characterization of their crosstalk could lead to novel therapeutic strategies for targeting and killing cancer cells in hypoxic tumors.
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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".