Statistical modeling of extracellular vesicle cargo to predict clinical trial outcomes for hypoplastic left heart syndrome

Jessica R Hoffman; Hyun-Ji Park; Sruti Bheri; Manu O Platt; Joshua M Hare; Sunjay Kaushal; Judith L Bettencourt; Dejian Lai; Timothy C Slesnick; William T Mahle; Michael E Davis

doi:10.1016/j.isci.2023.107980

Statistical modeling of extracellular vesicle cargo to predict clinical trial outcomes for hypoplastic left heart syndrome

iScience. 2023 Sep 21;26(10):107980. doi: 10.1016/j.isci.2023.107980. eCollection 2023 Oct 20.

Authors

Jessica R Hoffman^{1

2}, Hyun-Ji Park¹, Sruti Bheri¹, Manu O Platt¹, Joshua M Hare³, Sunjay Kaushal⁴, Judith L Bettencourt⁵, Dejian Lai⁵, Timothy C Slesnick^{6

7}, William T Mahle^{6

7}, Michael E Davis^{1

2

7}

Affiliations

¹ Wallace H. Coulter Department of Biomedical Engineering, Emory University School of Medicine & Georgia Institute of Technology, Atlanta, GA 30322, USA.
² Molecular & Systems Pharmacology Graduate Training Program, Laney Graduate School, Emory University, Atlanta, GA 30322, USA.
³ Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
⁴ Departments of Surgery and Pediatrics, Ann and Robert H. Lurie Children's Hospital of Chicago, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
⁵ Coordinating Center for Clinical Trials, Department of Biostatistics and Data Science, University of Texas Health Science Center School of Public Health, Houston, TX 77030, USA.
⁶ Division of Pediatric Cardiology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, USA.
⁷ Children's Heart Research & Outcomes (HeRO) Center, Children's Healthcare of Atlanta & Emory University, Atlanta, GA 30322, USA.

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.

Keywords: Drug delivery system; Medicine; Statistical physics.

Abstract

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