Abstract 3555: Proteomic characterization of rhabdomyosarcoma-derived extracellular vesicles reveals a fusion-positive protein signature
Bibliographic record
Abstract
Abstract Rhabdomyosarcoma is the most common pediatric soft tissue sarcoma. Current diagnostic methods involve imaging and tissue biopsy for staging, histology and fusion status assessment. There are presently no serum biomarkers for rhabdomyosarcoma diagnosis or surveillance. Novel approaches and identification of biomarkers are warranted for minimally invasive diagnostic/surveillance techniques. Extracellular vesicles (EVs) are recognized as critical mediators of intercellular communication and the pathophysiology of carcinogenesis and metastasis. This study aimed to characterize the proteome of rhabdomyosarcoma-derived EVs and identify proteomic signatures that correlate with clinical characteristics such as histological subtype, cancer stage, age and metastasis, using patient-derived cell lines. EVs were isolated from cell culture conditioned media by differential ultracentrifugation from four rhabdomyosarcoma cell lines (RH4, RH18, RH30, RD), each in triplicate. Liquid chromatography-tandem mass spectrometry identified EV protein cargo. Proteins identified in our samples were compared to all available EV data in the Vesiclepedia database, using the FunRich software. We identified 1,527 total proteins in our rhabdomyosarcoma-derived EVs. When comparing to Vesiclepedia, 96 unique proteins were identified from our EVs that were not previously annotated in EVs within the database. Expression of these 96 proteins was further evaluated based on clinical characteristics of the tumors the cell lines were derived from. We found a four-protein signature in the EV secretome of rhabdomyosarcoma cell lines correlated with FOXO1 fusion-positive status. This signature includes proteins involved in regulating extracellular matrix organization, regulating gene expression, protein biosynthesis and translation. Rhabdomyosarcoma cells secrete EVs with unique protein cargo based on clinical characteristics of the parent tumor such as histological subtype and FOXO1 fusion status. Further validation of these secreted EV proteins in biological fluids could prove an effective liquid biopsy technique for novel diagnostic approaches or surveillance in pediatric rhabdomyosarcoma. Citation Format: Paula R. Quaglietta, Ashby Kissoondoyal, Ethan Malkin, David Malkin, Reto M. Baertschiger. Proteomic characterization of rhabdomyosarcoma-derived extracellular vesicles reveals a fusion-positive protein signature. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3555.
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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".