Alteration of the Methylation Status of Tumor-Promoting Genes Decreases Prostate Cancer Cell Invasiveness and Tumorigenesis <i>In vitro</i> and <i>In vivo</i>
Bibliographic record
Abstract
We tested the hypothesis that cell invasiveness and tumorigenesis are driven by hypomethylation of genes involved in tumor progression. Highly invasive human prostate cancer cells PC-3 were treated with either the methyl donor S-adenosylmethionine (SAM) or methyl DNA-binding domain protein 2 antisense oligonucleotide (MBD2-AS). Both treatments resulted in a dose- and time-dependent inhibition of key genes, such as urokinase-type plasminogen activator (uPA), matrix metalloproteinase-2 (MMP-2), and vascular endothelial growth factor expression to decrease tumor cell invasion in vitro. No change in the levels of expression of genes already known to be methylated in late-stage prostate cancer cells, such as glutathione S-transferase P1 and androgen receptor, was seen. Inoculation of PC-3 cells pretreated with SAM and MBD2-AS into the flank of male BALB/c nu/nu mice resulted in the development of tumors of significantly smaller volume compared with animals inoculated with PC-3 cells treated with vehicle alone or MBD2 scrambled oligonucleotide. Immunohistochemical analysis of tumors showed the ability of SAM and MBD2-AS to significantly decrease tumoral uPA and MMP-2 expression along with levels of angiogenesis and survival pathway signaling molecules. Bisulfite sequencing analysis of tumoral genomic DNA showed that inhibition of both uPA and MMP-2 expression was due to methylation of their 5' regulatory region. These studies support the hypothesis that DNA hypomethylation controls the activation of multiple tumor-promoting genes and provide valuable insight into developing novel therapeutic strategies against this common disease, which target the demethylation machinery.
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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 | 0.000 |
| 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 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".