Dysregulation of kallikrein-related peptidases in renal cell carcinoma: potential targets of miRNAs
Why this work is in the frame
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Bibliographic record
Abstract
Renal cell carcinoma (RCC) accounts for 3% of all adult malignancies and currently no diagnostic marker exists. Kallikrein-related peptidases (KLKs) have been implicated in numerous cancers including ovarian, prostate, and breast carcinoma. KLKs 5, 6, 10, and 11 have decreased expression in RCC when compared to normal kidney tissue. Our bioinformatic analysis indicated that the KLK 1, 6, and 7 genes have decreased expression in RCC. We experimentally verified these results and found that decreased expression of KLKs 1 and 3 were significantly associated with the clear cell RCC subtype (p<0.001). An analysis of miRNAs differentially expressed in RCC showed that 61 of the 117 miRNAs that were reported to be dysregulated in RCC were predicted to target KLKs. We experimentally validated two targets using two independent approaches. Transfection of miR-224 into HEK-293 cells resulted in decreased KLK1 protein levels. A luciferase assay demonstrated that hsa-let-7f can target KLK10 in the RCC cell line ACHN. Our results, showing differential expression of KLKs in RCC, suggest that KLKs could be novel diagnostic markers for RCC and that their dysregulation could be under miRNA control. The observation that KLKs could represent targets for miRNAs suggests a post-transcriptional regulatory mechanism with possible future therapeutic applications.
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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) | 0.001 | 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 it