miR-183 promotes radioresistance of lung adenocarcinoma H1299 cells via epithelial-mesenchymal transition
Bibliographic record
Abstract
Lung adenocarcinomas are usually sensitive to radiation therapy, but some develop resistance. Radiation resistance can lead to poor patient prognosis. Studies have shown that lung adenocarcinoma cells (H1299 cells) can develop radioresistance through epithelial-mesenchymal transition (EMT), and this process is regulated by miRNAs. However, it is unclear which miRNAs are involved in the process of EMT. In our present study, we found that miR-183 expression was increased in a radioresistant lung adenocarcinoma cell line (H1299R cells). We then explored the regulatory mechanism of miR-183 and found that it may be involved in the regulation of zinc finger E-box-binding homeobox 1 (ZEB1) expression and mediate EMT in lung adenocarcinoma cells. qPCR results showed that miR-183, ZEB1, and vimentin were highly expressed in H1299R cells, whereas no difference was observed in E-cadherin expression. Western blot results showed that ZEB1 and vimentin were highly expressed in H1299R cells, while E-cadherin expression was decreased. When miR-183 expression was inhibited in H1299R cells, radiation resistance, proliferation, and cell migration were decreased. The expression of ZEB1 and vimentin in H1299R cells was decreased, while the expression of E-cadherin was increased. Moreover, miR-183 overexpression in H1299 cells enhanced radiation resistance, proliferative capacity, and cell migration ability. The expression of ZEB1 and vimentin in H1299 cells was increased, while that of E-cadherin was decreased. In conclusion, miR-183 may promote EMT and radioresistance in H1299 cells, and targeting the miR-183-ZEB1 signaling pathway may be a promising approach for lung cancer treatment.
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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) | 0.001 | 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".