MicroRNA-652 induces NED in LNCaP and EMT in PC3 prostate cancer cells
Bibliographic record
Abstract
// Robert K. Nam 1, * , Tania Benatar 2, * , Yutaka Amemiya 3 , Christopher J.D. Wallis 1 , Joan Miguel Romero 2 , Melina Tsagaris 2 , Christopher Sherman 4, 5 , Linda Sugar 4, 5 and Arun Seth 2, 3, 4, 5 1 Division of Urology, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada 2 Platform Biological Sciences, Sunnybrook Research Institute, Toronto, ON, Canada 3 Genomics Facility, Sunnybrook Research Institute, Toronto, ON, Canada 4 Department of Anatomic Pathology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada 5 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada * These authors contributed equally to the work Correspondence to: Tania Benatar, email: tbenatar@rogers.com Arun Seth, email: arun.seth@utoronto.ca Keywords: miR-652-3p; miRNA; prostate cancer; NED; EMT Received: June 15, 2017 Accepted: March 06, 2018 Published: April 10, 2018 ABSTRACT MicroRNAs (miRNAs) are small noncoding RNA molecules that post-transcriptionally regulate gene expression. Dysregulation of miRNAs is frequently associated with disease and, in particular, is involved in prostate cancer progression. Next generation miRNA sequencing identified a panel of five miRNAs associated with prostate cancer recurrence and metastasis. High expression of one of these five miRNAs, miR-652, correlated significantly with an increased rate of prostate cancer biochemical recurrence. Overexpression of miR-652 in prostate cancer cells, PC3 and LNCaP, resulted in increased growth, migration and invasion. Prostate cancer cell xenografts overexpressing miR-652 showed increased tumorigenicity and metastases. We found that miR-652 directly targets the B” regulatory subunit, PPP2R3A, of the tumor suppressor PP2A, inducing epithelial-mesenchymal transition (EMT) in PC3 cells and neuroendocrine-like differentiation (NED) in LNCaP cells. The mesenchymal marker N-cadherin increased and epithelial marker E-cadherin decreased in PC3 cells overexpressing miR-652. In LNCaP cells and xenografted tumors, overexpression of miR-652 increased markers of NED, including chromogranin A, neuron specific enolase, and synaptophysin. MiR-652 may contribute to prostate tumor progression by promoting NED through decreased PP2A function. MiR-652 expression could serve as a biomarker for aggressive prostate cancer, as well as provide an opportunity for novel therapy in prostate cancer.
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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 | 0.000 | 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) | 0.000 | 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".