Chemically induced DNA hypomethylation in breast carcinoma cells detected by the amplification of intermethylated sites
Bibliographic record
Abstract
INTRODUCTION: Compromised patterns of gene expression result in genomic instability, altered patterns of gene expression and tumour formation. Specifically, aberrant DNA hypermethylation in gene promoter regions leads to gene silencing, whereas global hypomethylation events can result in chromosomal instability and oncogene activation. Potential links exist between environmental agents and DNA methylation, but the destabilizing effects of environmental exposures on the DNA methylation machinery are not understood within the context of breast cancer aetiology. METHODS: We assessed genome-wide changes in methylation patterns using a unique methylation profiling technique called amplification of intermethylated sites (AIMS). This method generates easily readable fingerprints that represent the investigated cell line's methylation profile, based on the differential cleavage of DNA with methylation-specific isoschisomeric restriction endonucleases. RESULTS: We validated this approach by demonstrating both unique and reoccurring sites of genomic hypomethylation in four breast carcinoma cell lines treated with the cytosine analogue 5-azacytidine. Comparison of treated with control samples revealed individual bands that exhibited methylation changes, and these bands were excized and cloned, and the precise genomic location individually identified. In most cases, these regions of hypomethylation coincided with susceptible target regions previously associated with chromosome breakage, rearrangement and gene amplification. Similarly, we observed that acute benzopyrene exposure is associated with altered methylation patterns in these cell lines. CONCLUSION: These results reinforce the link between environmental exposures, DNA methylation and breast cancer, and support a role for AIMS as a rapid, affordable screening method to identify environmentally induced DNA methylation changes that occur in tumourigenesis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".