The role of miRNA-145 in esophageal adenocarcinoma.
Bibliographic record
Abstract
46 Background: Carcinoma of the esophagus has become one of the fastest growing solid tumors in the world over the past 20 years and the 6th most common cause of death in the world. We previously conducted a study to profile the expression of miRNAs in esophageal adenocarcinoma (EAC) pre and post induction therapy. Out of the miRNAs discovered, miR-145, a known tumor suppressor miRNA, was upregulated 8-fold upon induction therapy however its expression was associated with shorter disease-free survival. This unexpected result was explored. Methods: In order to study the role of miR-145 in EAC, miRNA-145 was overexpressed in the EAC cell line OE33 (OE33 miR145). After validation of the expression of miR-145, several hallmarks of cancer such as cell proliferation, resistance to apoptosis and cell adhesion were analyzed. Results: There was no difference in cell proliferation and resistance to radiation between OE33 miR145 and OE33 control. However, there was a significant difference in cell adhesion. OE33 miR145 cells reattach faster than the OE33 control (72.3% cells reattached against 40.5% cells reattached after 3h, n=3, p<0.05). Furthermore, OE33 miR145 cells are able to recover better than OE33 control cells after 72 hours culture in suspension (126.5 colonies against 63.5 colonies after 5 days of culture, n=2, p<0.05). Conclusions: While there was no difference between the two OE33 populations in an attached state, clear differences appeared when cells were in a detached state. Although more work is required to confirm this effect, expression of miR-145 could help EAC cells in circulation by protecting them against apoptosis and helping them to reattach faster which could in turn facilitate distant metastasis.
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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) | 0.001 | 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".