The MicroRNA-200 Family Is Upregulated in Endometrial Carcinoma
Bibliographic record
Abstract
BACKGROUND: MicroRNAs (miRNAs, miRs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. MicroRNAs are dysregulated in cancer and may play essential roles in tumorigenesis. Additionally, miRNAs have been shown to have prognostic and diagnostic value in certain types of cancer. The objective of this study was to identify dysregulated miRNAs in endometrioid endometrial adenocarcinoma (EEC) and the precursor lesion, complex atypical hyperplasia (CAH). METHODOLOGY: We compared the expression profiles of 723 human miRNAs from 14 cases of EEC, 10 cases of CAH, and 10 normal proliferative endometria controls using Agilent Human miRNA arrays following RNA extraction from formalin-fixed paraffin-embedded (FFPE) tissues. The expression of 4 dysregulated miRNAs was validated using real time reverse transcription-PCR. RESULTS: Forty-three miRNAs were dysregulated in EEC and CAH compared to normal controls (p<0.05). The entire miR-200 family (miR-200a/b/c, miR-141, and miR-429) was up-regulated in cases of EEC. CONCLUSIONS: This information contributes to the candidate miRNA expression profile that has been generated for EEC and shows that certain miRNAs are dysregulated in the precursor lesion, CAH. These miRNAs in particular may play important roles in tumorigenesis. Examination of miRNAs that are consistently dysregulated in various studies of EEC, like the miR-200 family, will aid in the understanding of the role that miRNAs play in tumorigenesis in this tumour type.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".