Methyl-CpG binding domain protein 2 plays a causal role in breast cancer growth and metastasis
Bibliographic record
Abstract
Abstract Methyl-CpG-binding domain protein 2 (Mbd2), a reader of DNA-methylation, has been implicated in the progression of several types of malignancies, including breast cancer. To test whether Mbd2, which is overexpressed in human breast cancer samples and in MMTV-PyMT mammary pads, plays a causal role in mammary tumor growth and metastasis we depleted Mbd2 in transgenic MMTV-PyMT model of breast cancer by cross-breeding with Mbd2 knockout mice to generate heterozygous (PyMT; Mbd2 +/- ) and homozygous (PyMT; Mbd2 -/- ) animals. We found that Mbd2 depletion caused a gene dose-dependent delay in mammary tumor formation, reduced primary tumor burden, and lung metastasis at the experimental endpoint. In addition, animals from the PyMT; Mbd2 -/- group survived significantly longer compared to the wildtype (PyMT; Mbd2 +/+ ) and PyMT; Mbd2 +/- arms. Transcriptomic and proteomic analyses of the primary tumors obtained from PyMT; Mbd2 +/+ and PyMT; Mbd2 +/- groups revealed that Mbd2 depletion alters several key determinants of the molecular signaling networks related to tumorigenesis and metastasis, which thereby demonstrate that Mbd2 is regulating transcriptional programs critical for breast cancer. To our knowledge, this is the first study demonstrating a causal role for a DNA-methylation reader in breast cancer. Results from this study will provide the rationale for further development of first-in-class targeted epigenetic therapies against Mbd2 to inhibit the progression of breast and other common cancers.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".