DNA-Methyltransferase 1 Induces Dedifferentiation of Pancreatic Cancer Cells through Silencing of Krüppel-Like Factor 4 Expression
Bibliographic record
Abstract
Abstract Purpose: The dismal prognosis of pancreatic cancer has been linked to poor tumor differentiation. However, molecular basis of pancreatic cancer differentiation and potential therapeutic value of the underlying molecules remain unknown. We investigated the mechanistic underexpression of Krüppel-like factor 4 (KLF4) in pancreatic cancer and defined a novel epigenetic pathway of its activation for pancreatic cancer differentiation and treatment. Experimental Design: Expressions of KLF4 and DNMT1 in pancreatic cancer tissues were determined by IHC and the genetic and epigenetic alterations of KLF4 in and KLF4′s impact on differentiation of pancreatic cancer were examined using molecular biology techniques. The function of dietary 3,3′-diindolylmethane (DIM) on miR-152/DNMT1/KLF4 signaling in pancreatic cancer was evaluated using both cell culture and animal models. Results: Overexpression of DNMT1 and promoter hypermethylation contributed to decreased KLF4 expression in and associated with poor differentiation of pancreatic cancer. Manipulation of KLF4 expression significantly affected differentiation marker expressions in pancreatic cancer cells. DIM treatment significantly induced miR-152 expression, which blocked DNMT1 protein expression and its binding to KLF4 promoter region, and consequently reduced promoter DNA methylation and activated KLF4 expression in pancreatic cancer cells. In addition, DIM treatment caused significant inhibition of cell growth in vitro and tumorigenesis in animal models of pancreatic cancer. Conclusions: This is the first demonstration that dysregulated KLF4 expression associates with poor differentiation of pancreatic cancer. Epigenetic activation of miR-152/DNMT1/KLF4 signaling pathway by dietary DIM causes differentiation and significant growth inhibition of pancreatic cancer cells, highlighting its translational implications for pancreatic and other cancers. Clin Cancer Res; 23(18); 5585–97. ©2017 AACR.
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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) | 0.002 | 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".