Functional impact of colorectal cancer-associated mutations in the transcription factor E2F4
Bibliographic record
Abstract
The transcription factor E2F4 plays a critical role in cell cycle progression of normal and cancerous intestinal epithelial cells. Contrary to other E2Fs, the coding region of the E2F4 gene contains a longer spacer segment of a CAG trinucleotide repeat sequence encoding 13 consecutive serine residues, which is highly vulnerable to frameshift mutations in situations of genetic instability. Mutations in this region of the E2F4 gene have been observed in colorectal tumors with microsatellite instability. However, the effect of these changes on its function in colorectal cancer cells is currently unknown. We generated E2F4(CAG)₁₂ and E2F4(CAG)₁₄ mutants and compared their activity to the E2F4 wild-type, E2F4(CAG)₁₃. Luciferase assays with the thymidine kinase-luc reporter gene revealed that the mutants were more transcriptionally active than wild-type E2F4. The mechanism of increased activity of E2F4 was primarily related to protein stability, due to a significantly enhanced half-life of E2F4 mutants comparatively to that of wild-type E2F4. However, the association with the pocket protein p130/RBL2 did not account for this increased protein stability. Sequencing analysis of the endogenous E2F4 gene in a series of colorectal cancer cell lines showed that the microsatellite-unstable cell line SW48 exhibited a serine deletion in this gene. Accordingly, E2F4 half-life was much more elevated in SW48 cells in comparison to Caco-2/15, a microsatellite-stable cell line. Notably, in soft-agar assays, both mutants more potently increased anchorage-independent growth in comparison to wild-type E2F4. In conclusion, our data demonstrate that cancer-associated E2F4 mutations enhance the capacity of colorectal cancer cells to grow without anchorage, thereby contributing to tumor progression.
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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".