Abstract P2179: Endothelial-derived Extracellular Vesicles Communicate With Cardiomyocytes To Elicit Cancer Therapy-related Cardiac Dysfunction
Bibliographic record
Abstract
Background: Treatment with the anthracycline, epirubicin, can result in cancer-therapy related cardiac dysfunction (CTRCD), a leading cause of non-malignant mortality in cancer survivors. Endothelial cells (ECs) lining the blood vessels are the first point of contact of epirubicin and secrete factors that are pivotal in regulating cardiac function. Of these factors, extracellular vesicles (EVs) are known to mediate intercellular communication. It remains unknown whether and how EC-EVs affect cardiomyocyte function in the context of CTRCD. Hypothesis: We hypothesize that epirubicin exposure leads to altered EC-EV cargo which mediates cardiomyocyte dysfunction. Methods: Human umbilical vein endothelial cells (HUVEC) were exposed to the peak and trough concentrations of epirubicin and endothelial function was assessed. EC-EVs were isolated via ultracentrifugation and EV size and concentration were measured through nanoparticle tracking analysis. The protein content of EC-EVs was determined using liquid chromatography with tandem mass spectrometry. Pluripotent stem cell-derived cardiomyocytes (iPSC-CM) were exposed to physiological concentrations of EVs (1x1010 particles/mL) and contractility was assessed in real-time. Results: Epirubicin exposure increased endothelial leak, apoptosis, and adhesion molecule expression. We observed an increase in size and concentration of EC-EVs and proteomic analysis revealed altered EV cargo including reduced cardiomyocyte protective factors, CNP and eNOS in EVs from epirubicin treated HUVEC in comparison to control. Treatment of iPSC-cardiomyocytes with EVs from epirubicin treated HUVECs resulted in reduced contractility compared to EVs from healthy ECs. Cleavage of EC-EV surface proteins via proteinase K abrogated the effects of EC-EVs on iPSC-cardiomyocytes. Cardiomyocyte-specific pathways targeted by EC-EVs from epirubicin- compared to control-treated cells are currently on-going. Conclusion: We demonstrate that epirubicin treatment leads to endothelial dysfunction and altered release of EVs capable of mediating cardiomyocyte dysfunction. Our results show the potential role of EC-EVs in CTRCD pathogenesis and highlight their influence on cardiomyocyte function.
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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) | 0.002 | 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".