The role of ICT1 during MYC-deregulated fast-onset mouse plasmacytomagenesis
Bibliographic record
Abstract
Murine plasmacytoma models human cancers that involve deregulation of MYC. Overexpression and duplication of the immature colon carcinoma transcript 1 gene, Ict1, along with MYC deregulation may contribute to the aggressive mechanism for disease development in fast-onset mouse plasmacytomas. This study looks at Ict1 and c-MYC overexpression in mouse PreBmycER cells that serve as a cell culture model for MYC-dependent plasmacytomagenesis. An Ict1 inducible vector was transfected into the mouse PreBmycER cell line that contains inducible c-MYC. This allowed us to examine the effect of overexpression of ICT1 and c-MYC proteins simultaneously or each separately, on selected hallmark cancer cell traits such as increased proliferation, evasion of apoptosis and increased genomic instability. An increase in the number of cells in the S-phase was observed by 15 % and up to 20 % at 24 and 36 hours respectively, and cell doubling time shortened by almost 2 hours at 24 hours during peak ICT1 and c-MYC overexpression. Although, no noticeable change in apoptosis levels, or large scale genomic alterations were detected up to 96 hours post-ICT1 and c-MYC peak-overexpression, genomic instability was observed when MYC protein was overexpressed with or without ICT1 protein overexpression. Extrachromosomal elements increased in number and size during conditional MYC deregulation, and most of these elements (25 %) classified as Chromosome 11. These findings support Ict1 as a candidate gene that is selected for by MYC-deregulation during plasmacytomagenesis, and show promise that the experimental model of induced MYC and ICT1 overexpression in mouse PreB cells, deserves further investigation, specifically with in vivo studies.
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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".