Transcription onset of genes critical in liver carcinogenesis is epigenetically regulated by methylated DNA-binding protein MBD2
Bibliographic record
Abstract
We previously delineated genes whose promoters are hypomethylated and induced in hepatocellular carcinoma (HCC) patients. The purpose of this study was to establish the players that regulate these genes in liver cancer cells. We performed chromatin immunoprecipitation with methyl-CpG-binding domain protein 2 (MBD2), RNA polymerase II (RNA pol II), CCAAT/enhancer-binding protein alpha (CEBPA) antibodies and methylated DNA immunoprecipitation in HepG2 liver cancer cells treated with scrambled small interfering RNA (siRNA) and siRNA to MBD2 or CEBPA. We then hybridized DNA to microarrays spanning the entire coding sequences, introns and regulatory regions of several hundred HCC-hypomethylated genes. These analyses reveal that MBD2 binds a significant fraction of the hypomethylated genes, determines RNA pol II binding and DNA methylation state. MBD2 binding can result in promoter activation and hypomethylation or in repression. In activated target genes, MBD2 colocalizes with the transcription factor CEBPA, and MBD2 binding at these positions is reduced upon CEBPA depletion. Significant fraction of MBD2 effects on DNA methylation and transcription appears to be indirect since changes occur upon MBD2 depletion in genes where no MBD2 binding was detected. Our study delineates the rules governing the interaction of MBD2 with its targets and the consequences to RNA pol II binding and DNA methylation states. This has important implications for understanding the role of DNA methylation in cancer and targeting DNA methylation proteins in cancer therapy.
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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 | 0.001 | 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".