Proteomic Landscapes of 3D and 2D Models of High-Grade Serous Ovarian Carcinoma: Implications for Carboplatin Response
Bibliographic record
Abstract
High-grade serous ovarian carcinoma (HGSOC) is the most common form of ovarian cancer, and finding new treatments remains an unmet need. While drug discovery is typically performed in two-dimensional (2D) monolayers, three-dimensional (3D) culture systems better mimic the in vivo conditions. However, a comprehensive comparison of 3D versus 2D ovarian cancer models is lacking. Here, we quantitatively compared the whole cell proteomic signatures of four ovarian cell lines─PEO1, PEO4, UWB1.289, and UWB1.289+BRCA1─with different status of BRCA genes grown in 2D and 3D. Using isobaric labeling proteomics, we quantified 6404 proteins and identified 371 significantly and commonly altered proteins between 2D and 3D. Proteins upregulated in 3D were enriched for transmembrane transport and NADH:ubiquinone oxidoreductase complex I, while energy metabolism and cell growth pathways also showed dimensionality-dependent changes. Notably, membrane-associated proteins were downregulated in spheroids, particularly EGFR in PEO1. Furthermore, the 3D culture modulated the response to carboplatin, with an increased expression of drug resistance-associated proteins, including NDUF family members in all spheroid models. These findings underscore how culture dimensionality influences both the molecular landscape and the chemotherapeutic response of HGSOC cells and highlights candidate targets for overcoming carboplatin resistance.
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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 | 0.002 | 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 | 0.001 |
| 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".