Proteomic and Phosphoproteomic Reprogramming in Epithelial Ovarian Cancer Metastasis
Bibliographic record
Abstract
Epithelial ovarian cancer (EOC) is a high-risk cancer presenting with heterogeneous tumors. The high incidence of EOC metastasis from primary tumors to nearby tissues and organs is a major driver of EOC lethality. We used cellular models of spheroid formation and readherence to investigate cellular signaling dynamics in each step toward EOC metastasis. In our system, adherent cells model primary tumors, spheroid formation represents the initiation of metastatic spread, and readherent spheroid cells represent secondary tumors. Proteomic and phosphoproteomic analyses show that spheroid cells are hypoxic and show markers for cell cycle arrest. Aurora kinase B abundance and downstream substrate phosphorylation are significantly reduced in spheroids and readherent cells, explaining their cell cycle arrest phenotype. The proteome of readherent cells is most similar to spheroids, yet greater changes in the phosphoproteome show that spheroid cells stimulate Rho-associated kinase 1 (ROCK1)-mediated signaling, which controls cytoskeletal organization. In spheroids, we found significant phosphorylation of ROCK1 substrates that were reduced in both adherent and readherent cells. Application of the ROCK1-specific inhibitor Y-27632 to spheroids increased the rate of readherence and altered spheroid density. The data suggest ROCK1 inhibition increases EOC metastatic potential. We identified novel pathways controlled by Aurora kinase B and ROCK1 as major drivers of metastatic behavior in EOC cells. Our data show that phosphoproteomic reprogramming precedes proteomic changes that characterize spheroid readherence in EOC metastasis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".