Molecular characterization of human homologs of yeast MOB1
Bibliographic record
Abstract
MOB (Mps one binder) was originally identified in yeast as a regulator of mitotic exit and cytokinesis, and was later identified as a tumor suppressor and a component of an emerging Hippo-LATS tumor suppressor pathway in Drosophila (D). So far, 7 human homologs of yeast MOB (hMOB1A, 1B, 2A, 2B, 2C, 3, 4) have been identified. Although hMOB1A/B has been extensively studied, the biological features of other hMOBs are largely unknown. In addition, while hMOB1 has been reported to interact with and activate LATS (Large tumor suppressor)/Warts tumor suppressor, the functional significance of this is unknown. In this study, we have characterized, for the first time, the cellular and biochemical function of all human MOBs. By examining hMOB mRNAs expression in various human tissues, we found that hMOBs demonstrated different expression patterns. Further biochemical characterization of hMOBs showed that only hMOB1A and hMOB1B interact with both LATS1 and LATS2 in vitro and in vivo. Significantly, we have discovered that overexpression of hMOB1 in human cancer cells activated LATS activity and inhibited cell proliferation or caused apoptosis while hMOB1, targeting the plasma membrane, led to a more significant phenotype. Reciprocally, short-hairpin (sh) RNA-mediated suppression of hMOB1 causes increased cell proliferation. Our findings provided evidence that hMOB1A and hMOB1B are 2 LATS-binding proteins that may function as tumor suppressors in human cancer 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".