Signaling network analysis of ubiquitin-mediated proteins suggests correlations between the 26S proteasome and tumor progression
Why this work is in the frame
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Bibliographic record
Abstract
We performed a comprehensive analysis of a literature-mined human signaling network by integrating data on ubiquitin-mediated protein half-lives. We found that proteins with very long half-lives are connected to form a network backbone, while proteins with short and medium half-lives preferentially attach to the network backbone and scatter throughout the network. Furthermore, proteins with short and medium half-lives are mutually exclusive in network neighbors. Short half-life proteins are enriched in the upstream portion of the network, suggesting that ubiquitination might help initiate signal processing and specificity. We also discovered that ubiquitination preferentially occurs in positive regulatory loops. Furthermore, these loops predominately induce or positively regulate apoptosis, a major component in cancer signaling. These results lead us to discover that the highly expressed genes involved in the common machinery of ubiquitination, the 26S proteasome genes, are significantly correlated with tumor progression and metastasis. Furthermore, expression of the 26S proteasome gene set predicts the clinical outcome of breast cancer patients. Our findings have implications for the development of cancer treatments and prognostic markers focused on the ubiquitination machinery.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it