Proteasome regulators in pancreatic cancer
Bibliographic record
Abstract
Pancreatic adenocarcinoma is one of the most lethal cancers with rising incidence. Despite progress in its treatment, with the introduction of more effective chemotherapy regimens in the last decade, prognosis of metastatic disease remains inferior to other cancers with long term survival being the exception. Molecular characterization of pancreatic cancer has elucidated the landscape of the disease and has revealed common lesions that contribute to pancreatic carcinogenesis. Regulation of proteostasis is critical in cancers due to increased protein turnover required to support the intense metabolism of cancer cells. The proteasome is an integral part of this regulation and is regulated, in its turn, by key transcription factors, which induce transcription of proteasome structural units. These include FOXO family transcription factors, NFE2L2, hHSF1 and hHSF2, and NF-Y. Networks that encompass proteasome regulators and transduction pathways dysregulated in pancreatic cancer such as the KRAS/ BRAF/MAPK and the Transforming growth factor beta/SMAD pathway contribute to pancreatic cancer progression. This review discusses the proteasome and its transcription factors within the pancreatic cancer cellular micro-environment. We also consider the role of stemness in carcinogenesis and the use of proteasome inhibitors as therapeutic agents.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".