An Identity Crisis for <i>fps/fes</i>: Oncogene or Tumor Suppressor?
Bibliographic record
Abstract
Fps/Fes proteins were among the first members of the protein tyrosine kinase family to be characterized as dominant-acting oncoproteins. Addition of retroviral GAG sequences or other experimentally induced mutations activated the latent transforming potential of Fps/Fes. However, activating mutations in fps/fes had not been found in human tumors until recently, when mutational analysis of a panel of colorectal cancers identified four somatic mutations in sequences encoding the Fps/Fes kinase domain. Here, we report biochemical and theoretical structural analysis demonstrating that three of these mutations result in inactivation, not activation, of Fps/Fes, whereas the fourth mutation compromised in vivo activity. These results did not concur with a classic dominant-acting oncogenic role for fps/fes involving activating somatic mutations but instead raised the possibility that inactivating fps/fes mutations might promote tumor progression in vivo. Consistent with this, we observed that tumor onset in a mouse model of breast epithelial cancer occurred earlier in mice targeted with either null or kinase-inactivating fps/fes mutations. Furthermore, a fps/fes transgene restored normal tumor onset kinetics in targeted fps/fes null mice. These data suggest a novel and unexpected tumor suppressor role for Fps/Fes in epithelial cells.
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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 | 0.001 |
| 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 | 0.001 |
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".