Ischemia dysregulates DNA methyltransferases and<i>p16INK4a</i>methylation in human colorectal cancer cells
Why this work is in the frame
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Bibliographic record
Abstract
Epigenetic modifications are involved in the initiation and progression of cancer. Expression patterns and activity of DNA methyltransferases (DNMTs) are strictly controlled in normal cells, however, regulation of these enzymes is lost in cancer cells due to unknown reasons. Cancer therapies which target DNMTs are promising treatments of hematologic cancers, but they lack effectiveness in solid tumors. Solid tumors exhibit areas of hypoxia and hypoglycaemia due to their irregular and dysfunctional vasculature, and we previously showed that hypoxia reduces global DNA methylation. Colorectal carcinoma (CRC) cells (HCT116 and 379.2; p53+/+ and p53-/-, respectively) were subjected to ischemia (hypoxia and hypoglycaemia) in vitro, and levels of DNMTs were assessed. We found a significant decrease in mRNA for DNMT1, DNMT3a and DNMT3b, and similar reductions in DNMT1 and DNMT3a protein levels were detected by western blotting. In addition, total activity levels of DNMTs (as measured by an ELISA-based DNMT activity assay) were reduced in cells exposed to hypoxic and hypoglycaemic conditions. Immunofluorescence of HCT116 tumor xenografts demonstrated an inverse relationship between ischemia (as revealed by carbonic anhydrase IX staining) and DNMT1 protein. Bisulfite sequencing of the proximal promoter region of p16INK4a showed a decrease in 5-methylcytosine following in vitro exposure to ischemia. These studies provide evidence for the down-regulation of DNMTs and modulation of methylation patterns by hypoxia and hypoglycaemia in human CRC cells, both in vitro and in vivo. Our findings suggest that ischemia, either intrinsic or induced through the use of anti-angiogenic drugs, may influence epigenetic patterning and hence tumor progression.
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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 | 0.000 | 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 it