Metastasis-associated protein 1 (MTA1) is an essential downstream effector of the c-MYC oncoprotein
Bibliographic record
Abstract
The c-myc oncogene is among the most commonly overexpressed genes in human cancer. c-myc encodes a basic helix-loop-helix/leucine zipper (bHLH/LZ) transcription factor (c-MYC) that activates a cascade of downstream targets that ultimately mediate cellular transformation. Although a large number of genes are regulated by c-MYC, only a few have been functionally linked to c-MYC-mediated transformation. By expression profiling, the metastasis-associated protein 1 (MTA1) gene was identified here as a target of the c-MYC oncoprotein in primary human cells, a result confirmed in human cancer cells. MTA1 itself has been previously implicated in cellular transformation, in part through its ability to regulate the epithelial-to-mesenchymal transition and metastasis. MTA1 is a component of the Mi-2/nucleosome remodeling and deacetylating (NURD) complex that contains both histone deacetylase and nucleosome remodeling activity. The data reported here demonstrate that endogenous c-MYC binds to the genomic MTA1 locus and recruits transcriptional coactivators. Most importantly, short hairpin RNA (shRNA)-mediated knockdown of MTA1 blocks the ability of c-MYC to transform mammalian cells. These data implicate MTA1 and the Mi-2/NURD complex as one of the first downstream targets of c-MYC function that are essential for the transformation potential of c-MYC.
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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) | 0.002 | 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".