Epigenetic transfer of metastatic activity by uptake of highly metastatic B16 melanoma cell-released exosomes.
Bibliographic record
Abstract
AIM: To investigate potential role of highly metastatic BL6-10 tumor cell-released exosomes (EXO) in transfer of metastatic activity into poorly metastatic tumor cell line F1. METHODS: The highly metastatic B16 melanoma cell line (BL6-10) was generated in our laboratory. EXO from this cell line were isolated and amount of exosomal recovered proteins was measured using Bradford assay. For phenotypic analysis BL6-10 and F1 melanoma cells were stained with FITC-conjugated anti-MHC I (H-2K(b)), MHC II (Ia(b)) and Met 72 antibodies and analyzed by flow cytometry. C57BL/6 mice (8 per group) were injected (i. v.) with 0.5 x 10(6) F1, BL6-10 and F1(EXO) melanoma cells. Lungs were removed 4 weeks after tumor cell injection, fixed in 10% neutral buffered formaldehyde and embedded in paraffin for histological analysis. RESULTS: Data revealed that BL6-10 cells expressed metastasis marker (Met 72 tumor antigen), while F1 cells did not display this cell surface marker. All mice inoculated with BL6-10 melanoma cells had numerous lung tumor colonies, while mice injected with F1 tumor cells were free of lung metastatic colonies. BL6-10 tumor cells-released EXO also expressed Met 72 tumor antigen as BL6-10 tumor cells, but in less amount. F1 tumor cells can uptake EXO from BL6-10 tumor cells and express acquired exosomal Met 72 tumor antigen. CONCLUSION: The metastatic activity of highly metastatic BL6-10 tumor cells can be transferred to poorly metastatic F1 tumor cells by uptake of highly metastatic BL6-10 tumor-released EXO.
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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".