Effects of Long-term Serial Passaging on the Characteristics and Properties of Cell Lines Derived From Uveal Melanoma Primary Tumors
Bibliographic record
Abstract
PURPOSE: Development of liver metastasis remains the most common cause of mortality in uveal melanoma (UM). A few cell lines cultured from primary UM tumors have been used widely to investigate the pathobiology of UM. However, the translation of basic knowledge to the clinic for the treatment of the metastatic disease has remained incremental at best. In this study, we examined whether the properties of UM cell lines at various passages were similar to their corresponding primary tumors. METHODS: Gene expression profiling by microarray was performed on UM primary tumors and derived cell lines cultured at varying passages. Expression of UM protein markers was monitored by immunohistochemical analyses and Western blotting. The in vivo tumorigenic properties of UM cultures were evaluated using athymic nude mice. RESULTS: Cell passaging severely reduced the expression of genes encoding markers typical of UM, including those of the prognostic gene signature. Marked differences between gene expression profiles of primary tumors and cell lines could be linked to the infiltrating immune and stromal cells in situ. In addition, the tumorigenic properties of UM cell lines also increased with cell passaging in culture as evaluated by their subcutaneous injection into athymic mice. CONCLUSIONS: Together, these findings demonstrate that the short-term UM primary cultures exhibit molecular features that resemble the respective surgical material and, thus, represent the best model for in vitro-assessed cancer treatments.
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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 | 0.001 |
| 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".