Breast cancer cell mesenchymal transition and metastasis directed by DAP5/eIF3d-mediated selective mRNA translation
Bibliographic record
Abstract
Cancer cell plasticity enables cell survival in harsh physiological environments and fate transitions such as the epithelial-to-mesenchymal transition (EMT) that underlies invasion and metastasis. Using genome-wide transcriptomic and translatomic studies, an alternate mechanism of cap-dependent mRNA translation by the DAP5/eIF3d complex is shown to be essential for metastasis, EMT, and tumor directed angiogenesis. DAP5/eIF3d carries out selective translation of mRNAs encoding EMT transcription factors and regulators, cell migration integrins, metalloproteinases, and cell survival and angiogenesis factors. DAP5 is overexpressed in metastatic human breast cancers associated with poor metastasis-free survival. In human and murine breast cancer animal models, DAP5 is not required for primary tumor growth but is essential for EMT, cell migration, invasion, metastasis, angiogenesis, and resistance to anoikis. Thus, cancer cell mRNA translation involves two cap-dependent mRNA translation mechanisms, eIF4E/mTORC1 and DAP5/eIF3d. These findings highlight a surprising level of plasticity in mRNA translation during cancer progression and metastasis.
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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".