miR-409-3p/-5p Promotes Tumorigenesis, Epithelial-to-Mesenchymal Transition, and Bone Metastasis of Human Prostate Cancer
Bibliographic record
Abstract
PURPOSE: miR-409-3p/-5p is a miRNA expressed by embryonic stem cells, and its role in cancer biology and metastasis is unknown. Our pilot studies demonstrated elevated miR-409-3p/-5p expression in human prostate cancer bone metastatic cell lines; therefore, we defined the biologic impact of manipulation of miR-409-3p/-5p on prostate cancer progression and correlated the levels of its expression with clinical human prostate cancer bone metastatic specimens. EXPERIMENTAL DESIGN: miRNA profiling of a prostate cancer bone metastatic epithelial-to-mesenchymal transition (EMT) cell line model was performed. A Gleason score human tissue array was probed for validation of specific miRNAs. In addition, genetic manipulation of miR-409-3p/-5p was performed to determine its role in tumor growth, EMT, and bone metastasis in mouse models. RESULTS: Elevated expression of miR-409-3p/-5p was observed in bone metastatic prostate cancer cell lines and human prostate cancer tissues with higher Gleason scores. Elevated miR-409-3p expression levels correlated with progression-free survival of patients with prostate cancer. Orthotopic delivery of miR-409-3p/-5p in the murine prostate gland induced tumors where the tumors expressed EMT and stemness markers. Intracardiac inoculation (to mimic systemic dissemination) of miR-409-5p inhibitor-treated bone metastatic ARCaPM prostate cancer cells in mice led to decreased bone metastasis and increased survival compared with control vehicle-treated cells. CONCLUSION: miR-409-3p/-5p plays an important role in prostate cancer biology by facilitating tumor growth, EMT, and bone metastasis. This finding bears particular translational importance as miR-409-3p/-5p appears to be an attractive biomarker and/or possibly a therapeutic target to treat bone metastatic prostate cancer.
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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 | 0.001 |
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".