Ubiquitin Proteasome Gene Signatures in Ependymoma Molecular Subtypes
Bibliographic record
Abstract
The ubiquitin proteasome system (UPS) is critically important for cellular homeostasis and affects virtually all key functions in normal and neoplastic cells. Currently, a comprehensive review of the role of the UPS in ependymoma (EPN) brain tumors is lacking but may provide valuable new information on cellular networks specific to different EPN subtypes and reveal future therapeutic targets. We have reviewed publicly available EPN gene transcription datasets encoding components of the UPS pathway. Reactome analysis of these data revealed genes and pathways that were able to distinguish different EPN subtypes with high significance. We identified differential transcription of several genes encoding ubiquitin E2 conjugases associated with EPN subtypes. The expression of the E2 conjugase genes UBE2C, UBE2S, and UBE2I was elevated in the ST_EPN_RELA subtype. The UBE2C and UBE2S enzymes are associated with the ubiquitin ligase anaphase promoting complex (APC/c), which regulates the degradation of substrates associated with cell cycle progression, whereas UBE2I is a Sumo-conjugating enzyme. Additionally, elevated in ST_EPN_RELA were genes for the E3 ligase and histone deacetylase HDAC4 and the F-box cullin ring ligase adaptor FBX031. Cluster analysis demonstrated several genes encoding E3 ligases and their substrate adaptors as EPN subtype specific genetic markers. The most significant Reactome Pathways associated with differentially expressed genes for E3 ligases and their adaptors included antigen presentation, neddylation, sumoylation, and the APC/c complex. Our analysis provides several UPS associated factors that may be attractive markers and future therapeutic targets for the subtype-specific treatment of EPN patients.
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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 | 0.002 | 0.002 |
| 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".