TRIM16 inhibits neuroblastoma cell proliferation through cell cycle regulation and dynamic nuclear localization
Bibliographic record
Abstract
Neuroblastoma is the most common solid tumor in childhood and represents 15% of all children's cancer deaths. We have previously demonstrated that tripartite motif 16 (TRIM16), a member of the RING B-box coiled-coil (RBCC)/tripartite totif (TRIM) protein family, has significant effects on neuroblastoma proliferation and migration in vitro and tumorigenicity in vivo. However, the mechanism by which this putative tumor suppressor influences cell proliferation and tumorigenicity was undetermined. Here we show, for the first time, TRIM16's striking pattern of expression and dynamic localization during cell cycle progression and neuroblastoma tumor development. In a tyrosine hydroxylase MYCN (TH-MYCN) neuroblastoma mouse model, immunohistochemical staining revealed strong nuclear TRIM16 expression in differentiating ganglia cells but not in the tumor-initiating cells. Furthermore in vitro studies clearly demonstrated that during G 1 cell cycle phase, TRIM16 protein expression is upregulated and shifts to the nucleus of cells. TRIM16 also plays a role in cell cycle progression through changes in Cyclin D1 and p27 expression. Importantly, using TRIM16 deletion mutants, an uncharacterized protein domain of TRIM16 was found to be required for both TRIM16's growth inhibitory effects and its nuclear localization. Taken together, our data suggest that TRIM16 acts as a novel regulator of both neuroblastoma G 1/S progression and cell differentiation.
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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".