USP22 overexpression fails to augment tumor formation in MMTV-ERBB2 mice but loss of function impacts MMTV promoter activity
Bibliographic record
Abstract
Abstract The Ubiquitin Specific Peptidase 22 (USP22), a component of the Spt-Ada-Gcn5 Acetyltransferase (SAGA) histone modifying complex, is overexpressed in multiple human cancers, but how USP22 impacts tumorigenesis is not clear. We reported previously that Usp22 loss in mice impacts execution of several signaling pathways driven by growth factor receptors such as erythroblastic oncogene B b2 (ERBB2). To determine whether changes in USP22 expression affects ERBB2-driven tumorigenesis, we introduced conditional overexpression or deletion alleles of Usp22 into mice bearing the Mouse mammary tumor virus-Neu-Ires-Cre (MMTV-NIC) transgene, which drives both rat ERBB2/NEU expression and Cre recombinase activity from the MMTV promoter resulting in mammary tumor formation. We found that USP22 overexpression in mammary glands did not further enhance primary tumorigenesis in MMTV-NIC female mice, but increased lung metastases were observed. However, deletion of Usp22 significantly decreased tumor burden and increased survival of MMTV-NIC mice. These effects were associated with markedly decreased levels of both Erbb2 mRNA and protein, indicating Usp22 loss impacts MMTV promoter activity. Usp22 loss had no impact on ERBB2 expression in other settings, including MCF10A cells bearing a Cytomegalovirus (CMV) - driven ERBB2 transgene or in human epidermal growth factor receptor 2 (HER2)+ human SKBR3 and HCC1953 cells. Decreased activity of the MMTV promoter in MMTV-NIC mice correlated with decreased expression of known regulatory factors, including the glucocorticoid receptor (GR), the progesterone receptor (PR), and the chromatin remodeling factor Brahma-related gene-1 (BRG1). Together our findings indicate that increased expression of USP22 does not augment the activity of an activated ERBB2/NEU transgene but impacts of Usp22 loss on tumorigenesis cannot be assessed in this model due to unexpected effects on MMTV-driven Erbb2/Neu expression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".