Supression of tumor progression and metastasis in renal cell carcinoma by miR-192, miR-194, and miR-215.
Bibliographic record
Abstract
385 Background: miRNAs play a crucial rule in tumor progression and metastasis. We previously identified miR-192, miR-194 and miR-215 to be down-regulated in metastatic compared to primary clear cell renal cell carcinoma (ccRCC). In this work, we examine the role of miR-192, miR-194, and miR-215 in RCC progression and aggressiveness. Methods: We examined the role of these three miRNAs on tumor cell migration and invasion abilities using RCC cell line models. We performed target prediction analysis and experimentally validated the targets using independent approaches. In addition, we examined the clinical utility of miR-215 as a potential prognostic marker in RCC by measuring miR-215 expression using qRT-PCR in 61 formalin-fixed paraffin-embedded tissues from primary ccRCC and correlated the expression levels with clinical outcome. Results: Restoration of miR-192, miR-194, and miR-215 expression decreased cell migration and invasion in RCC cell lines. Target prediction analysis identified three potential targets of these miRNAs; MDM2, TYMS, and SIP1/ZEB2. We validated the miRNA-target interaction experimentally using three approaches. First by measuring the effect of miRNA overexpression on mRNA and protein levels of the predicted target, then by measuring the effect of miRNA overexpression on a luciferase signal of a vector containing the 3’UTR of the predicted target, and finally, by validating these interactions in vivoby examining the presence of an inverse correlation between miRNA changes and the expression levels of their targets on clinical specimens. In 61 patients with resected ccRCC tumors, we found that low miR-215 expression in the primary was associated with a significantly reduced recurrence-free survival. (26.4 vs. 49.2 months, respectively, p = 0.0320). Conclusions: Our analysis showed that miR-192, miR-194, and miR-215 are involved in RCC metastasis and that miR-215 predicts for recurrence in patients with resected RCC. Our findings pave the way to the clinical use of miRNAs as prognostic markers and potential therapeutic targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".