MYC interaction with the tumor suppressive SWI/SNF complex member INI1 regulates transcription and cellular transformation
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Bibliographic record
Abstract
MYC is a key driver of cellular transformation and is deregulated in most human cancers. Studies of MYC and its interactors have provided mechanistic insight into its role as a regulator of gene transcription. MYC has been previously linked to chromatin regulation through its interaction with INI1 (SMARCB1/hSNF5/BAF47), a core member of the SWI/SNF chromatin remodeling complex. INI1 is a potent tumor suppressor that is inactivated in several types of cancers, most prominently as the hallmark alteration in pediatric malignant rhabdoid tumors. However, the molecular and functional interaction of MYC and INI1 remains unclear. Here, we characterize the MYC-INI1 interaction in mammalian cells, mapping their minimal binding domains to functionally significant regions of MYC (leucine zipper) and INI1 (repeat motifs), and demonstrating that the interaction does not interfere with MYC-MAX interaction. Protein-protein interaction network analysis expands the MYC-INI1 interaction to the SWI/SNF complex and a larger network of chromatin regulatory complexes. Genome-wide analysis reveals that the DNA-binding regions and target genes of INI1 significantly overlap with those of MYC. In an INI1-deficient rhabdoid tumor system, we observe that with re-expression of INI1, MYC and INI1 bind to common target genes and have opposing effects on gene expression. Functionally, INI1 re-expression suppresses cell proliferation and MYC-potentiated transformation. Our findings thus establish the antagonistic roles of the INI1 and MYC transcriptional regulators in mediating cellular and oncogenic functions.
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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 | 0.000 | 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) | 0.000 | 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 it