Targeted Inhibition of the KLF6 Splice Variant, KLF6 SV1, Suppresses Prostate Cancer Cell Growth and Spread
Bibliographic record
Abstract
Prostate cancer is a leading cause of cancer death in men. Risk prognostication, treatment stratification, and the development of rational therapeutic strategies lag because the molecular mechanisms underlying the initiation and progression from primary to metastatic disease are unknown. Multiple lines of evidence now suggest that KLF6 is a key prostate cancer tumor suppressor gene including loss and/or mutation in prostate cancer tumors and cell lines and decreased KLF6 expression levels in recurrent prostate cancer samples. Most recently, we identified a common KLF6 germ line single nucleotide polymorphism that is associated with an increased relative risk of prostate cancer and the increased production of three alternatively spliced, dominant-negative KLF6 isoforms. Here we show that although wild-type KLF6 (wtKLF6) acts as a classic tumor suppressor, the single nucleotide polymorphism-increased splice isoform, KLF6 SV1, displays a markedly opposite effect on cell proliferation, colony formation, and invasion. In addition, whereas wtKLF6 knockdown increases tumor growth in nude mice >2-fold, short interfering RNA-mediated KLF6 SV1 inhibition reduces growth by approximately 50% and decreases the expression of a number of growth- and angiogenesis-related proteins. Together, these findings begin to highlight a dynamic and functional antagonism between wtKLF6 and its splice variant KLF6 SV1 in tumor growth and dissemination.
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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 | 0.001 |
| 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".