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Updated: Jul 12, 2025
Setting a Successful Sorting for Extracellular Vesicle Isolation
Published on: October 11, 2024
Statistical modeling of extracellular vesicle cargo to predict clinical trial outcomes for hypoplastic left heart
Jessica R Hoffman1,2, Hyun-Ji Park1, Sruti Bheri1
1Wallace H. Coulter Department of Biomedical Engineering, Emory University School of Medicine & Georgia Institute of Technology, Atlanta, GA 30322, USA.
Insights
Cardiac progenitor cell-derived extracellular vesicles (CPCEVs) show promise for hypoplastic left heart syndrome (HLHS) treatment. Their angiogenic potential correlates with improved right ventricle function in patients, suggesting a viable cell therapy approach.
Area of Science:
- Cardiovascular Research
- Regenerative Medicine
- Biotechnology
Background:
- Hypoplastic left heart syndrome (HLHS) is a severe congenital heart defect.
- Cardiac progenitor cells (CPCs) and their extracellular vesicles (EVs) are being investigated for HLHS treatment.
- Understanding variability in CPC-derived EVs (CPC-EVs) is crucial for therapeutic development.
Purpose of the Study:
- To develop a predictive model for CPC-EV therapeutic efficacy using machine learning.
- To analyze the RNA content of CPC-EVs and their functional responses.
- To correlate CPC-EV characteristics with clinical outcomes in HLHS patients.
Main Methods:
- Isolation of CPCs from patient cardiac biopsies (n=34).
- Bulk RNA sequencing of CPC-EVs.
- In vitro assessment of EV inflammatory, fibrotic, angiogenic, and migratory responses.
- Machine learning model development to predict in vitro outcomes.
Main Results:
- CPC-EV RNAs are associated with cardiac development and signaling pathways.
- A predictive model successfully forecasted in vitro outcomes for clinical samples.
- Angiogenic performance of CPC-EVs correlated with improved right ventricle function in patients.
Conclusions:
- CPC-EVs possess pro-reparative properties relevant to cardiac development.
- Machine learning can predict CPC-EV functional performance.
- CPC-EV angiogenic capacity is a potential biomarker for clinical improvement in HLHS.
Abstract:
Cardiac-derived c-kit+ progenitor cells (CPCs) are under investigation in the CHILD phase I clinical trial (NCT03406884) for the treatment of hypoplastic left heart syndrome (HLHS). The therapeutic efficacy of CPCs can be attributed to the release of extracellular vesicles (EVs). To understand sources of cell therapy variability we took a machine learning approach: combining bulk CPC-derived EV (CPC-EV) RNA sequencing and cardiac-relevant in vitro experiments to build a predictive model. We isolated CPCs from cardiac biopsies of patients with congenital heart disease (n = 29) and the lead-in patients with HLHS in the CHILD trial (n = 5). We sequenced CPC-EVs, and measured EV inflammatory, fibrotic, angiogeneic, and migratory responses. Overall, CPC-EV RNAs involved in pro-reparative outcomes had a significant fit to cardiac development and signaling pathways. Using a model trained on previously collected CPC-EVs, we predicted in vitro outcomes for the CHILD clinical samples. Finally, CPC-EV angiogenic performance correlated to clinical improvements in right ventricle performance.
