Label-free impedance analysis of induced pluripotent stem cell-derived spinal cord progenitor cells for rapid safety and efficacy profiling

Regenerative therapies, including the transplantation of spinal cord progenitor cells (SCPCs) derived from induced pluripotent stem cells (iPSCs), are promising treatment strategies for spinal cord injuries. However, the risk of tumorigenicity from residual iPSCs advocates an unmet need for rapid SC...

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Bibliographic Details
Main Authors: He, Linwei, Tan, Jerome, Ng, Shi-Yan, Li, Holden King Ho, Han, Jongyoon, Chew, Sing Yian, Hou, Han Wei
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/180370
Description
Summary:Regenerative therapies, including the transplantation of spinal cord progenitor cells (SCPCs) derived from induced pluripotent stem cells (iPSCs), are promising treatment strategies for spinal cord injuries. However, the risk of tumorigenicity from residual iPSCs advocates an unmet need for rapid SCPCs safety profiling. Herein, we report a rapid (~3000 cells/min) electrical-based microfluidic biophysical cytometer to detect low-abundance iPSCs from SCPCs at single-cell resolution. Based on multi-frequency impedance measurements (0.3 to 12 MHz), biophysical features including cell size, deformability, membrane and nucleus dielectric properties are simultaneously quantified as a cell is hydrodynamically stretched at a cross junction under continuous flow. We further develop a supervised Uniform Manifold Approximation and Projection (UMAP) model for impedance-based quantification of undifferentiated iPSCs with high sensitivity (~ 1% spiked iPSCs) and showed good correlations with SCPCs differentiation outcomes using two iPSC lines. We also identified cell membrane opacity (day 1) as a novel early intrinsic predictive biomarker that exhibited a strong correlation with SCPC differentiation efficiency (day 10). Overall, we envision this label-free and optic-free platform technology can be further developed as a versatile cost-effective process analytical tool to monitor or assess stem cell quality and safety in regenerative medicine.