Expression and <scp>DNA</scp> methylation of <scp>20</scp> S proteasome subunits as prognostic and resistance markers in cancer
Bibliographic record
Abstract
Proteasomes are involved in the maintenance of cellular protein homeostasis and the control of numerous cellular pathways. Single proteasome genes or subunits have been identified as important players in cancer development and progression without considering the proteasome as a multisubunit protease. We here conducted a comprehensive pan-cancer analysis encompassing transcriptional, epigenetic, mutational landscapes, pathway enrichments, and survival outcomes linked to the 20S proteasome core complex. The impact of proteasome gene expression on patient survival exhibited a cancer type-dependent pattern. Increased proteasome expression correlated with elevated activation of oncogenic pathways, such as DNA repair, MYC-controlled gene networks, MTORC1 signalling, oxidative phosphorylation, as well as metabolic pathways including glycolysis and fatty acid metabolism. Accordingly, potential loss of function variants of proteasome subunit genes are associated with improved patient survival. The TCGA-derived outcomes were further supported by gene expression analysis of THP-1 cells. Our study highlighted the importance of studying the proteasome as an enzymatic functional unit rather than separated subunits.
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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 | 0.001 | 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".