Loss of EMI1 compromises chromosome stability and is associated with cellular transformation in colonic epithelial cell contexts
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) is still a leading cause of cancer deaths worldwide. Thus, identifying the aberrant genes and proteins underlying disease pathogenesis is critical to improve early detection methods and develop novel therapeutic strategies. Chromosome instability (CIN), or ongoing changes in chromosome complements, is a predominant form of genome instability. It is a driver of genetic heterogeneity found in ~85% of CRCs. Although CIN contributes to CRC pathogenesis, the molecular determinants underlying CIN remain poorly understood. Recently, EMI1, an F-box protein, was identified as a candidate CIN gene. In this study, we sought to determine the impact reduced EMI1 expression has on CIN and cellular transformation. METHODS: Coupling siRNA-based silencing and CRISPR/Cas9 knockout clones with quantitative imaging microscopy we evaluated the impact reduced EMI1 expression has on CIN and cellular transformation in four colonic epithelial cell contexts. RESULTS: Quantitative imaging microscopy data revealed that reduced EMI1 expression induces increases in CIN phenotypes in both transient (siRNA) and constitutive (CRISPR/Cas9) cell models that are associated with increases in DNA damage and cellular transformation phenotypes in long-term studies. CONCLUSIONS: This study determined that reduced EMI1 expression induces CIN and promotes cellular transformation, which is consistent with a role in early CRC development.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".