Profile of differentially expressed miRNAs in high-grade serous carcinoma and clear cell ovarian carcinoma, and the expression of miR-510 in ovarian carcinoma
Bibliographic record
Abstract
Improved insight into the molecular and genetic profile of different types of epithelial ovarian cancer (EOC) is required for understanding the carcinogenesis of EOC and may potentially be exploited by future targeted therapies. The aim of the present study was to identify a unique microRNA (miRNA) patterns and key miRNAs, which may assist in predicting progression and prognosis in high‑grade serous carcinoma (HGSC) and clear cell carcinoma (CCC). To identify unique miRNA patterns associated with HGSC and CCC, a miRNA microarray was performed using Chinese tumor bank specimens of patients with HGSC or CCC in a retrospective analysis. The expression levels of four deregulated miRNAs were further validated using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) in an external cohort of 42 cases of HGSC and 36 cases of CCC. Kaplan‑Meier analysis was performed to analyze the correlation between the expression levels of the four miRNAs and patient prognosis. Among these validated miRNAs, miR‑510 was further examined in another cohort of normal ovarian tissues, as well as the HGSC, low‑grade serous carcinoma (LGSC) and CCC specimens using RT‑qPCR and in situ hybridization. The results revealed that, of the 768 miRNAs analyzed in the microarray, 33 and 50 miRNAs were significantly upregulated and downregulated, respectively, with at least a 2‑fold difference in HGSC, compared with CCC. The quantitative analysis demonstrated that miR‑510 and miR‑129‑3p were significantly downregulated, and that miR‑483‑5p and miR‑miR‑449a were significantly upregulated in CCC, compared with HGSC (P<0.05), which was consistent with the microarray results. Kaplan‑Meier analysis revealed low expression levels of miR‑510 and low expression levels of miR‑129‑3p, advanced International Federation of Gynecology and Obstetrics (FIGO) stage, lymphatic metastasis and that HGSC was significantly associated with the poorer overall survival rates (P<0.05). The expression of miR‑510 was significantly higher in the LGSC and CCC tissues, compared with the HGSC and normal ovarian tissues. The results of the present study suggested that different subtypes of EOC have specific miRNA signatures, and that miR‑510 may be involved differently in HGSC and CCC. Thus, miR‑510 and miR‑129‑3p may be considered as potential novel candidate clinical biomarkers for predicting the outcome of EOC.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".