Electrostatic polarization fields trigger glioblastoma stem cell differentiation.
Tamara Fernandez CabadaMassimo RubenAmira El MerhieRemo Proietti ZaccariaAlessandro AlabastriEnrica Maria PetriniAndrea BarberisMarco SalernoMarco CrepaldiAlexander DavisLuca CeseracciuTiziano CatelaniAthanassia AthanassiouTeresa PellegrinoRoberto CingolaniEvie L PapadopoulouPublished in: Nanoscale horizons (2022)
Over the last few years it has been understood that the interface between living cells and the underlying materials can be a powerful tool to manipulate cell functions. In this study, we explore the hypothesis that the electrical cell/material interface can regulate the differentiation of cancer stem-like cells (CSCs). Electrospun polymer fibres, either polyamide 66 or poly(lactic acid), with embedded graphene nanoplatelets (GnPs), have been fabricated as CSC scaffolds, providing both the 3D microenvironment and a suitable electrical environment favorable for CSCs adhesion, growth and differentiation. We have investigated the impact of these scaffolds on the morphological, immunostaining and electrophysiological properties of CSCs extracted from human glioblastoma multiform (GBM) tumor cell line. Our data provide evidence in favor of the ability of GnP-incorporating scaffolds to promote CSC differentiation to the glial phenotype. Numerical simulations support the hypothesis that the electrical interface promotes the hyperpolarization of the cell membrane potential, thus triggering the CSC differentiation. We propose that the electrical cell/material interface can regulate endogenous bioelectrical cues, through the membrane potential manipulation, resulting in the differentiation of CSCs. Material-induced differentiation of stem cells and particularly of CSCs, can open new horizons in tissue engineering and new approaches to cancer treatment, especially GBM.
Keyphrases
- stem cells
- tissue engineering
- cell therapy
- living cells
- single cell
- cancer stem cells
- endothelial cells
- magnetic resonance imaging
- escherichia coli
- computed tomography
- machine learning
- spinal cord
- electronic health record
- staphylococcus aureus
- spinal cord injury
- squamous cell carcinoma
- papillary thyroid
- big data
- pseudomonas aeruginosa
- molecular dynamics
- mass spectrometry
- climate change
- high glucose
- molecular dynamics simulations