The SWI/SNF Complex Protein Snr1 Is a Tumor Suppressor in <i>Drosophila</i> Imaginal Tissues
Bibliographic record
Abstract
Abstract Components of the SWI/SNF chromatin-remodeling complex are among the most frequently mutated genes in various human cancers, yet only SMARCB1/hSNF5, a core member of the SWI/SNF complex, is mutated in malignant rhabdoid tumors (MRT). How SMARCB1/hSNF5 functions differently from other members of the SWI/SNF complex remains unclear. Here, we use Drosophila imaginal epithelial tissues to demonstrate that Snr1, the conserved homolog of human SMARCB1/hSNF5, prevents tumorigenesis by maintaining normal endosomal trafficking-mediated signaling cascades. Removal of Snr1 resulted in neoplastic tumorigenic overgrowth in imaginal epithelial tissues, whereas depletion of any other members of the SWI/SNF complex did not induce similar phenotypes. Unlike other components of the SWI/SNF complex that were detected only in the nucleus, Snr1 was observed in both the nucleus and the cytoplasm. Aberrant regulation of multiple signaling pathways, including Notch, JNK, and JAK/STAT, was responsible for tumor progression upon snr1-depletion. Our results suggest that the cytoplasmic Snr1 may play a tumor suppressive role in Drosophila imaginal tissues, offering a foundation for understanding the pivotal role of SMARCB1/hSNF5 in suppressing MRT during early childhood. Cancer Res; 77(4); 862–73. ©2017 AACR.
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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 | 0.001 |
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".