Estrogen-Induced Rat Breast Carcinogenesis is Characterized by Alterations in DNA Methylation, Histone Modifications, and Aberrant microRNA Expression
Bibliographic record
Abstract
Breast cancer is the most common malignancy in women continuing to rise worldwide. Breast cancer emerges through a multi-step process, encompassing progressive changes from a normal cell to hyperplasia (with and without atypia), carcinoma in situ, invasive carcinoma, and metastasis. In the current study, we analyzed the morphological changes and alterations of DNA methylation, histone methylation and microRNA expression during estradiol-17beta (E(2))-induced mammary carcinogenesis in female August Copenhagen Irish (ACI) rats. E(2)-induced breast carcinogenesis in ACI rats provides a physiologically relevant and genetically defined animal model for studying human sporadic breast cancer. The pattern of morphological changes in mammary glands during E(2)-induced carcinogenesis was characterized by transition from normal appearing alveolar and ductular hyperplasia to focal hyperplastic areas of atypical glands and ducts accompanied by a rapid and sustained loss of global DNA methylation, LINE-1 hypomethylation, loss of histone H3 lysine 9 and histone H4 lysine 20 trimethylation, and altered microRNAs expression. More importantly, these alterations in the mammary tissue occurred after six weeks of E(2)-treatment, whereas the atypical hyperplasia, which represents a putative precursor lesion to mammary carcinoma in this model, was detected only after twelve weeks of exposure, demonstrating clearly that these events are directly associated with the effects of E(2) and are not a consequence of the preexisting preneoplastic lesions. The results of this study show that deregulation of cellular epigenetic processes plays a crucial role in the mechanism of E(2)-induced mammary carcinogenesis in ACI rats, especially in the tumor initiation process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
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".