Characterization of a Prostate- and Prostate Cancer-Specific Circular RNA Encoded by the Androgen Receptor Gene
Bibliographic record
Abstract
The linear mRNAs transcribed under alternative RNA splicing and overexpression/amplification of the androgen receptor (AR) gene are poor prognostic biomarkers of castrate-resistant prostate cancer (PCa). Whether the AR gene also transcribes non-coding circular RNAs that are associated with PCa development and tumor progression remains unclear. Here, we identified and characterized an AR circular RNA, called circAR3, that is widely expressed in PCa cell models and prostate tumors. circAR3 can be secreted into culture media of PCa cell lines and is detectable in the serum from mice bearing PCa xenografts. In PCa patient tissues, circAR3 is highly expressed in benign prostate and hormone naive PCa but downregulated when tumors were treated with neoadjuvant hormone therapy and further reduced when tumors progressed to the castrate-resistant stage. However, circAR3 levels in plasma are extremely low in patients with benign prostate, are upregulated in PCa patients with high Gleason scores and lymph node metastasis, and become undetectable in men after radical prostatectomy. circAR3 does not affect AR signaling, PCa cell proliferation, and invasion rates. Our results demonstrated that the origin of the detectable plasma circAR3 is from the prostate/PCa. Plasma circAR3 may be developed to be a PCa biomarker to monitor PCa development and tumor progression.
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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".