Abstract 10204: Single Cell Transcriptomics of Multiple Organ Sources to Develop Better Cell Grafts for Therapeutic Angiogenesis

Abstract

Introduction: To develop better cell therapy to combat cardiovascular disease (CVD), a greater number of cell markers or populations should be tested for their regenerative potentials. We applied single cell RNA-sequencing (scRNA-seq) analysis of multiple organs to identify attractive cell subsets for therapeutic angiogenesis. Methods: We revisited scRNA-seq datasets of various human organs. Transcriptomic data were normalized and analyzed for dimension reduction, cell clustering, and gene ontology. The screened cell population was sorted, cultured, and transplanted into a nude mice model of limb ischemia. Furthermore, AT of CVD patients ( n =40) was evaluated for the cell subset by flowcytometry. Results: We analyzed three well-known sources of cell therapy including bone marrow, adipose tissue (AT), and umbilical-cord blood. After clustering, lineage negative mesenchymal cell clusters were compared their expression of pro/anti-angiogenic factors. Interestingly, AT showed the most prominent expression of both pro- and anti-angiogenic factors ( Fig.A ). Then, we divided AT stromal cells into pro- and anti-angiogenic clusters. From this clustering, 17 markers were screened as specific for pro-angiogenic cluster ( Fig.B ). Subsequently, we identified a receptor CD271 as top candidate for angiogenic cell isolation. CD271 + cells showed enhanced angiogenic capacity in cell therapy experiments when compared to CD271 - cells. Furthermore, we detected long-term engraftment (PKH26) and increased number of proliferating host tissue cells using EdU labeling ( Fig.C ). Finally, we found CD271 + cells were significantly reduced and deteriorated in CVD patients with insulin resistance or higher Lp(a) ( Fig.D ). Conclusions: CD271 + cells from AT of metabolically healthy donors appears as an attractive for therapeutic angiogenesis. ScRNA-seq analysis is a potent tool to accelerate cell therapy field to find better cell populations and appropriate resources.