DJ-1 Enhances Cell Survival through the Binding of Cezanne, a Negative Regulator of NF-κB
Bibliographic record
Abstract
Heightened DJ-1 (Park7) expression is associated with a reduction in chemotherapeutic-induced cell death and poor prognosis in several cancers, whereas the loss of DJ-1 function is found in a subgroup of Parkinson disease associated with neuronal death. This study describes a novel pathway by which DJ-1 modulates cell survival. Mass spectrometry shows that DJ-1 interacts with BBS1, CLCF1, MTREF, and Cezanne/OTUD7B/Za20d1. Among these, Cezanne is a known deubiquitination enzyme that inhibits NF-κB activity. DJ-1/Cezanne interaction is confirmed by co-immunoprecipitation of overexpressed and endogenous proteins, maps to the amino-terminal 70 residues of DJ-1, and leads to the inhibition of the deubiquitinating activity of Cezanne. Microarray profiling of shRNA-transduced cells shows that DJ-1 and Cezanne regulate IL-8 and ICAM-1 expression in opposing directions. Similarly, DJ-1 enhances NF-κB nuclear translocation and cell survival, whereas Cezanne reduces these outcomes. Analysis of mouse Park7(-/-) primary cells confirms the regulation of ICAM-1 by DJ-1 and Cezanne. As NF-κB is important in cellular survival and transformation, IL-8 functions as an angiogenic factor and pro-survival signal, and ICAM-1 has been implicated in tumor progression, invasion, and metastasis; these data provide an additional modality by which DJ-1 controls cell survival and possibly tumor progression via interaction with Cezanne.
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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".