Ligand-dependent Corepressor (LCoR) Recruitment by Krüppel-like Factor 6 (KLF6) Regulates Expression of the Cyclin-dependent Kinase Inhibitor CDKN1A Gene
Bibliographic record
Abstract
The widely expressed transcriptional coregulator, ligand-dependent corepressor (LCoR), initially characterized as a regulator of nuclear receptor-mediated transactivation, functions through recruitment of C-terminal binding proteins (CtBPs) and histone deacetylases (HDACs) to its N-terminal and central domains, respectively. We performed a yeast two-hybrid screen for novel cofactors, and identified an interaction between the C-terminal domain of LCoR and the transcription factor Krüppel-like factor 6 (KLF6), a putative tumor suppressor in prostate cancer. Subsequent experiments revealed LCoR regulation of several KLF6 target genes notably p21(WAF1/CIP1) (CDKN1A) and to a lesser extent E-cadherin (CDH1), indicating that LCoR regulates gene transcription through multiple classes of transcription factors. In multiple cancer cells, LCoR and KLF6 bind together on the promoters of the genes encoding CDKN1A and CDH1. LCoR contributes to KLF6-mediated transcriptional repression in a promoter- and cell type-dependent manner. Its inhibition of reporter constructs driven by the CDKN1A and CDH1 promoters in PC-3 prostate carcinoma cells is sensitive to treatment with the HDAC inhibitor trichostatin A. Additionally, the LCoR cofactor CtBP1 bound the same promoters and augmented the LCoR-dependent repression in PC-3 cells. Consistent with their inferred roles in transcriptional repression, siRNA-mediated knockdown of KLF6, LCoR, or CtBP1 in PC-3 cells induced expression of CDKN1A and CDH1 and additional KLF6 target genes. We propose a novel model of LCoR function in which promoter-bound KLF6 inhibits transcription of the CDKN1A gene and other genes as well by tethering a transcriptional corepressor complex containing LCoR, with specific contributions by CtBP1 and HDACs.
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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".