MicroRNA profiling identifies VHL/HIF-2α dependent miR-2355-5p as a key modulator of clear cell Renal cell carcinoma tumor growth
Bibliographic record
Abstract
Inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene is one of the first truncal events in clear cell Renal Cell Carcinoma (ccRCC) tumorigenesis. The accumulation of Hypoxia Induced Factor (HIFα) resulting from VHL loss can promote ccRCC tumorigenesis by regulating microRNA (miRNA) expression. Here, we performed miRNA profiling and high-throughput analysis to identify a panel of VHL-dependent miRNAs in ccRCC. Validation of these miRNAs revealed the overexpression of miR-2355-5p in ccRCC cell models and primary tumors. Moreover, we showed a significant increase in circulating miR-2355-5p in plasma from patients with ccRCC. Mechanistically, miR-2355-5p overexpression was confirmed to be HIF-2α dependent. Targeting miR-2355-5p with the CRISPR/Cas9 system not only negatively disrupted the ability of ccRCC cells to stimulate angiogenesis but also decreased cell proliferation and drastically reduced tumor growth in mouse xenograft models. Finally, a miR-2355-5p pulldown assay identified five tumor suppressor genes, ACO1, BTG2, CMTM4, SLIT2, and WDFY2, as potential targets. All five genes were significantly downregulated in ccRCC tumors and mouse xenograft tumors. The results from this research demonstrate the oncogenic ability of miR-2355-5p and shed light on the possible mechanism by which this miRNA controls angiogenesis and tumor growth in VHL-deficient ccRCC.
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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".