<scp>miRNAs</scp> dysregulated in association with Gleason grade regulate extracellular matrix, cytoskeleton and androgen receptor pathways
Bibliographic record
Abstract
The Gleason grading system is an important determinant of treatment decisions and prognosis in prostate cancer. It has a number of limitations, including significant inter-observer variability, creating a need for biological parameters to accurately assess the Gleason grade. The objective of this study was to determine the molecular correlates of the different Gleason grades. Global miRNA expression was analysed in pure regions of each Gleason grade. Bioinformatics analysis was performed to predict miRNA-mediated signalling. We experimentally validated the effect of miRNAs on target gene expression and cellular functions using cell line models. We also examined the correlation of miRNAs with biochemical failure, metastasis and prognosis. We identified miRNAs that are differentially expressed between grades 3 and 5, and the top biological processes associated with Gleason grade transition were extracellular matrix (ECM)-mediated signalling, focal adhesion kinase- and mitogen-activated kinase pathways. Transfection with miR-29c, miR-34a and miR-141 repressed genes involved in ECM-mediated pathways, such as SRC, PRKCA, COL1A1, ITGB1 and MAPK13, and decreased cell proliferation and migration. Furthermore, miR-29c and miR-34a influenced downstream pathways that affect actin cytoskeleton organization and androgen receptor localization. Finally, miR-29c, miR-34a, miR-141 and miR-148a showed inverse correlations with biochemical recurrence, but were independent of other clinical parameters. Our results demonstrate the potential role of miRNAs as independent prognostic markers and pave the road for a biological-based reclassification of the Gleason grading system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".