Pleotrophic action of renal cell carcinoma: Dysregulated microRNAs on hypoxia-related signaling pathways.
Bibliographic record
Abstract
428 Background: The von Hippel-Lindau (VHL) gene is lost in 70% of clear cell Renal Cell Carcinomas (ccRCC); however, additional mechanisms are proposed to regulate VHL expression, including suppression by microRNAs (miRNAs). miRNAs are a class of naturally occurring, small non-coding RNA molecules that downregulate gene expression of target mRNAs. We demonstrate that ccRCC-dysregulated miRNAs can target multiple members of the ccRCC-related signaling pathways. Methods: miR-17 and miR-224 mimics and inhibitors were transfected into ccRCC cell lines using siPORT (Ambion). PicTar and TargetScan were used for target prediction. Target expression and miRNA expression was analyzed by qRT-PCR (Ambion). Western blot antibodies were purchased from Millipore or Cell Signaling. Cell lines were purchased from ATCC. All methods followed the manufacturer’s protocol. Results: According to our preliminary results, the miRNAs that are dysregulated in ccRCC specimens are predicted to target multiple members of the hypoxia-related pathways. To confirm the in silico analysis, miR-17 and miR-224 were selected for experimental target validation, as they were among the most up-regulated miRNAs in ccRCC. We experimentally validated VHL and HIF1α as likely direct targets of miR-17 and miR-224. Luciferase reporter assay confirmed that miR-17 directly downregulates VHL. Moreover, VHL protein level decreased upon miR-17 and miR-224 transfection. We also established a negative correlation between the expression of miR-17 and two predicted targets VEGF-A, EGLN3 in RCC specimens, and miR-224 and its predicted targets SMAD4 and SMAD5. This suggests that downstream signaling pathways are also modulated by miR-17 and miR-224. These results confirm the most important findings of the bioinformatics analysis: miR-17 targets different molecules along the same signaling pathway and that multiple ccRCC-dysregulated miRNAs can synergistically suppress a single target, which functions in the pathogenesis. Conclusions: Our results indicate that miRNAs possibly regulate hypoxia-related pathways at multiple points. This is of special interest as miRNAs may serve as potential therapeutic targets.
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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".