CEP164 Deficiency Causes Hyperproliferation of Pancreatic Cancer Cells
Bibliographic record
Abstract
Primary cilia are hair-like projections that protrude from most mammalian cells and mediate various extracellular signaling pathways. Pancreatic ductal adenocarcinoma (PDAC) cells are known to lose their primary cilia, but the relevance of this phenomenon remains unclear. In this study, we generated PDAC-originated Panc1 cells devoid of primary cilia by mutating a centriolar protein, centrosomal protein 164 (CEP164), which is required for ciliogenesis. CEP164 depletion enhanced the clonogenicity of Panc1 cells, along with chemically induced elimination of primary cilia, suggesting that a lack of these organelles promotes PDAC cells proliferation. In addition, the loss of CEP164 altered the cell cycle progression irrespective of absence of primary cilia. We found that CEP164 was co-localized with the GLI2 transcription factor at the mother centriole and controlled its activation, thus inducing Cyclin D-CDK6 expression. Furthermore, CEP164-mutated Panc1 cells were significantly tolerant to KRAS depletion-dependent growth inhibition. This study suggests that CEP164 deficiency is advantageous for PDAC cells proliferation due to not only lack of ciliation but also cilia-independent GLI2-Cyclin D/CDK6 activation, and that CEP164 is a potential therapeutic target for PDAC.
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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 | 0.000 | 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 | 0.001 |
| 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".