Condensation of the Golgi Apparatus Activates YAP1 to Promote Gastric Cancer Progression
Bibliographic record
Abstract
Alterations in the structure of the Golgi apparatus play a pivotal role in cancer progression and invasion. A better understanding of how Golgi morphology regulates the metastatic potential of cancer cells could help identify potential treatment strategies. In this study, we investigated how specific structural variations in the Golgi, particularly fragmentation and condensation, influence the malignancy of gastric cancer using human cell lines, xenograft mouse models, and human patient tissue samples. Gastric cancer cells with condensed Golgi structures exhibited increased proliferation and migration. Mechanistic analyses indicated that Golgi condensation-associated malignancy was driven by enhanced formation of Golgi-derived microtubules, elevated vesicular trafficking, and augmented nuclear translocation of YAP1, a key transcriptional regulator of cell proliferation and tumorigenesis. Importantly, treatment with an agent that induces Golgi fragmentation significantly suppressed tumor growth in a xenograft mouse model. Furthermore, signet-ring cell carcinoma, an aggressive subtype of diffuse gastric cancer, exhibited a stronger inverse correlation between YAP1 activation and the Golgi area than both intestinal-type and non-signet ring cell carcinoma. These findings underscore the critical role of Golgi apparatus dynamics in oncogenic signaling pathways and reveal therapeutic targets in gastric cancer. SIGNIFICANCE: Golgi condensation facilitates YAP1-mediated oncogenic progression in gastric cancer, highlighting Golgi structural modulation as a promising therapeutic strategy to inhibit malignant signaling and cellular dissemination.
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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".