Abstract 6455: Characterization of extracellular vesicles derived from uveal melanoma cell lines
Bibliographic record
Abstract
Abstract Purpose: Extracellular vesicles (EVs) are small (50nm-800nm) membrane-enclosed structures with highly heterogeneous content. Recently, the importance of EVs in tumor progression as well as biomarkers has become apparent in many malignancies. However, there has been very limited research done to investigate EVs derived from uveal melanoma (UM). UM is the most common primary intraocular tumor in adults, and it displays a high frequency of metastases to the liver. The aim of this study was (i) to characterize the protein signatures of UM cell line-derived EVs to determine potential biomarkers, (ii) to determine EV uptake by recipient cell lines, (iii) to analyze the activation of the MAPK pathway in the recipient cells, and to examine the potential of UM EV-educated BRCA1 deficient fibroblasts (Fibro-BKO) to develop tumors in NOD-SCID mice. Methods: EVs were isolated from the conditioned media of UM cell lines (MP41, MP46, 92.1, MEL285, MEL270, OMM2.5) and normal choroidal melanocytes cells using an ultracentrifugation method. Western blots and immunogold-labelling Transmission Electron Microscopy were employed to validate various EV markers (CD63, CD81 and TSG101). Proteomic analysis by mass spectrometry was performed to determine the UM-derived EV proteome signature that could elucidate potential key players in UM metastasis. After exposure to EVs, recipient cells were analysed for the activation of downstream signaling pathways, and were inoculated in NOD-SCID mice to analyze their behaviour. Results: We observed 2069 proteins in EVs using Scaffold Viewer. FUNRich analysis revealed that 95% of these EV proteins were found in the Vesiclepedia database. Gene Ontology analysis confirmed the presence of exosomal markers (CD81, TSG101and Syntenin) as well as cell-cell adhesion-related proteins. The DAVID Functional Annotation chart revealed proteins related to endocytosis, PI3K-Akt signaling pathway and focal adhesion. In addition, we observed high hits in HSP90 and HSP70, well-known biomarkers in UM. Integrin alpha V, which are known for preparing premetastatic niches in the liver environment, were also present. Western blot results confirmed the increase in MAPK pathway in the recipient cells. Furthermore, UM EVs-educated Fibro-BKO transformed and gave rise to tumors in vivo. Conclusion: In conclusion, our study reports an essential step towards understanding protein emission through EVs from UM cells. Our analyses revealed UM EVs cargo candidates that may play a role in pre-metastatic niche formation and metastasis in specific organs, such as the liver. The in vivo study model confirmed that EVs derived from UM are capable of inducing tumorigenesis. We believe that our data pave the way to the application of liquid biopsy to the monitoring of UM-affected patients. Citation Format: Thupten Tsering, Alexander Laskaris, Mohamed Abdouh, Prisca Bustamante Alvarez, Goffredo Arena, Julia Valdemarin Burnier. Characterization of extracellular vesicles derived from uveal melanoma cell lines [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6455.
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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) | 0.001 | 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".