miR-100-5p inhibition induces apoptosis in dormant prostate cancer cells and prevents the emergence of castration-resistant prostate cancer
Bibliographic record
Abstract
Carcinoma of the prostate is the most common cancer in men. Treatment of aggressive prostate cancer involves a regiment of radical prostectomy, radiation therapy, chemotherapy and hormonal therapy. Despite significant improvements in the last decade, the treatment of prostate cancer remains unsatisfactory, because a significant fraction of prostate cancers develop resistance to multiple treatments and become incurable. This prompts an urgent need to investigate the molecular mechanisms underlying the evolution of therapy-induced resistance of prostate cancer either in the form of castration-resistant prostate cancer (CRPC) or transdifferentiated neuroendocrine prostate cancer (NEPC). By analyzing micro-RNA expression profiles in a set of patient-derived prostate cancer xenograft tumor lines, we identified miR-100-5p as one of the key molecular components in the initiation and evolution of androgen ablation therapy resistance in prostate cancer. In vitro results showed that miR-100-5p is required for hormone-independent survival and proliferation of prostate cancer cells post androgen ablation. In Silico target predictions revealed that miR-100-5p target genes are involved in key aspects of cancer progression, and are associated with clinical outcome. Our results suggest that mir-100-5p is a possible therapeutic target involved in prostate cancer progression and relapse post androgen ablation therapy.
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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 | 0.001 | 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".