MicroRNA‐204‐5p: A novel candidate urinary biomarker of Xp11.2 translocation renal cell carcinoma
Bibliographic record
Abstract
Xp11.2 translocation renal cell carcinoma (Xp11 tRCC) is a rare sporadic pediatric kidney cancer caused by constitutively active TFE3 fusion proteins. Tumors in patients with Xp11 tRCC tend to recur and undergo frequent metastasis, in part due to lack of methods available to detect early-stage disease. Here we generated transgenic (Tg) mice overexpressing the human PRCC-TFE3 fusion gene in renal tubular epithelial cells, as an Xp11 tRCC mouse model. At 20 weeks of age, mice showed no histological abnormalities in kidney but by 40 weeks showed Xp11 tRCC development and related morphological and histological changes. MicroRNA (miR)-204-5p levels in urinary exosomes of 40-week-old Tg mice showing tRCC were significantly elevated compared with levels in control mice. MicroRNA-204-5p expression also significantly increased in primary renal cell carcinoma cell lines established both from Tg mouse tumors and from tumor tissue from 2 Xp11 tRCC patients. All of these lines secreted miR-204-5p-containing exosomes. Notably, we also observed increased miR-204-5p levels in urinary exosomes in 20-week-old renal PRCC-TFE3 Tg mice prior to tRCC development, and those levels were equivalent to those in 40-week-old Tg mice, suggesting that miR-204-5p increases follow expression of constitutively active TFE3 fusion proteins in renal tubular epithelial cells prior to overt tRCC development. Finally, we confirmed that miR-204-5p expression significantly increases in noncancerous human kidney cells after overexpression of a PRCC-TFE3 fusion gene. These findings suggest that miR-204-5p in urinary exosomes could be a useful biomarker for early diagnosis of patients with Xp11 tRCC.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".