Methylated DNA-binding protein 2 antisense inhibitors suppress tumourigenesis of human cancer cell lines in vitro and in vivo
Bibliographic record
Abstract
Methylated DNA-binding protein 2 (MBD2) has been proposed to function both as a silencer of methylated genes and as a DNA demethylase. Our previous data indicated that knockdown of MBD2 inhibited tumourigenesis of human cancer lines and MBD2-deficient mice were recently shown to be resistant to intestinal tumourigenesis. MBD2 is an attractive anticancer target since MBD2-deficient mice were previously shown to be viable and fertile and knockdown of MBD2 was reported to have no effect on cellular growth parameters of non-transformed cells. In this paper we test the hypothesis that pharmacological inhibition of MBD2 inhibits cancer growth in vivo using human tumour lines implanted in mice as a model. We develop sequence-specific antisense inhibitors of MBD2 and we show that these agents inhibit anchorage-independent growth of human lung (A549) and colorectal (HCT116) cancer cell lines in vitro and tumourigenic growth of human cancer cell xenografts in vivo. MBD2 antisense oligonucleotide does not inhibit the growth of normal and transformed cell lines and does not alter cell cycle parameters in vitro and does not exhibit overt toxicity in vivo in comparison with a scrambled control oligonucleotide, as determined by measuring body mass, blood cell parameters and liver and kidney enzymes. Our data provide a proof of principle that MBD2 is a new anticancer target and that pharmacological inhibition of MBD2 by agents such as the antisense inhibitors described in this paper is a potential new anticancer therapy, which in contrast to the vast majority of current approaches does not target normal progression of the cell cycle.
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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 | 0.000 | 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) | 0.001 | 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 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".