DJ-1/PARK7 is an important mediator of hypoxia-induced cellular responses
Bibliographic record
Abstract
In cancer, DJ-1/PARK7 acts as an oncogene that drives Akt-mediated cell survival. Although amplification of DJ-1 has been described in several types of tumors, the mechanistic basis of DJ-1's oncogenic effect remains incompletely understood. A tumor's ability to adapt to hypoxia is absolutely critical for its survival and progression, and this adaptation is largely mediated by the transcription factor HIF1. The stabilization of HIF1 subunits during hypoxia is at least partly dependent on the PI3K/Akt/mTOR pathway. We hypothesized that DJ-1, a positive regulator of Akt when over-expressed, might be involved in regulating HIF1 transcriptional activity under hypoxic conditions. Our results show that loss of DJ-1 in human cell lines and transformed mouse fibroblasts decreases the transcription of a variety of HIF1-responsive genes during hypoxia. Moreover, DJ-1 expression is critical for the Akt and mTOR activities that sustain HIF1 stability. Surprisingly, DJ-1 also regulates the activity of the metabolic sensor AMPK, especially during hypoxia. Finally, DJ-1 appears to protect cells against hypoxia-induced cell death and is required for their adaptation to severe hypoxic stress. Our work positions DJ-1 as an upstream activator of HIF1 function in cancer cells and establishes that DJ-1's oncogenic activity stems from its ability to increase a cell's resistance to hypoxic stress through DJ-1's regulatory effects on mTOR and AMPK. The discovery of these functions of DJ-1 strengthens the case for the development of therapeutics that target DJ-1 activity in cancer cells.
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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".