Ubiquitin Proteasome Pathway Transcriptome in Epithelial Ovarian Cancer
Bibliographic record
Abstract
In this article, we reviewed the transcription of genes coding for components of the ubiquitin proteasome pathway in publicly available datasets of epithelial ovarian cancer (EOC). KEGG analysis was used to identify the major pathways distinguishing EOC of low malignant potential (LMP) from invasive high-grade serous ovarian carcinomas (HGSOC), and to identify the components of the ubiquitin proteasome system that contributed to these pathways. We identified elevated transcription of several genes encoding ubiquitin conjugases associated with HGSOC. Fifty-eight genes coding for ubiquitin ligases and more than 100 genes encoding ubiquitin ligase adaptors that were differentially expressed between LMP and HGSOC were also identified. Many differentially expressed genes encoding E3 ligase adaptors were Cullin Ring Ligase (CRL) adaptors, and 64 of them belonged to the Cullin 4 DCX/DWD family of CRLs. The data suggest that CRLs play a role in HGSOC and that some of these proteins may be novel therapeutic targets. Differential expression of genes encoding deubiquitinases and proteasome subunits was also noted.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".