PLCE1 Promotes Esophageal Cancer Cell Progression by Maintaining the Transcriptional Activity of Snail
Bibliographic record
Abstract
Esophageal cancer is among the most deadly malignant diseases. However, the genetic factors contributing to its occurrence are poorly understood. Multiple studies with large clinic-based cohorts revealed that variations of the phospholipase C epsilon (PLCE1) gene were associated with esophageal cancer susceptibility. However, the causative role of PLCE1 in esophageal cancer is not clear. We inactivated the functional alleles of PLCE1 by CRISPR/Cas9 genome editing technology. The resultant PLCE1 inactivated cells were analyzed both in vitro and in vivo. Our results showed that loss of PLCE1 dramatically decreased the invasion and proliferation capacity of esophageal carcinoma cells in vitro. Moreover, such PLCE1 inactivated tumor grafts exhibited significantly decreased tumor size in mice. We found that PLCE1 was required to maintain protein level of snail a key transcription factor responsible for invasion. Our further transcriptomic data revealed that deficient cells were significantly decreased in expression of genes enriched as targets of Snail. Strikingly, recovery of Snail protein at least partially rescued the invasion and proliferation capacity in PLCE1 inactivated cells. In ESCC clinical specimens, PLCE1 was correlated with tumor stage (P<.0001). Interestingly, PLCE1 expression was positively correlated Snail by immunohistochemistry in such specimens (P<.0001). Therefore, our functional experiments showed the essential roles of PLCE1 in esophageal carcinoma cells and provided evidences that targeting PLCE1 and its downstream molecules could be effective therapies for esophageal cancer.
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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 | 0.000 |
| 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".