Real-Time Evaluation of Adhesion Processes and Glucose Response of Cancer Cells onto Phenylboronic Acid-Functionalized Films Monitored by Quartz Crystal Microbalance with Dissipation.
Bo WangYingjuan SunZhaohui SuYuan LinYongdong JinPublished in: Analytical chemistry (2023)
Understanding the interactions between cancer cells and smart substrates is of great benefit to physiology and pathology. Herein, we successfully fabricated two phenylboronic acid (PBA)-functionalized films with different surface topographies using a PBA homopolymer (PBAH) and self-assembled nanoparticles (PBAS) via a layer-by-layer assembly technique. We used a quartz crystal microbalance with dissipation (QCM-D) to monitor the entire cell adhesion process and figured out the adhesion kinetics of HepG2 cells on the two PBA-functionalized films. As seen from the QCM-D data, the HepG2 cells displayed distinctly different adhesion behaviors on the two PBA-functionalized films (PBAS and PBAH films). The results showed that the PBAS film promoted cell adhesion and cell spreading owing to its specific physicochemical properties. Likewise, the slope changes in the D-f plots clearly revealed the evolution of the cell adhesion process, which could be classified into three stages during cell adhesion on the PBA-functionalized films. In addition, compared with the PBAH film, the PBAS film could also control cell detachment behavior in the presence of glucose based on the molecular recognition between the PBA group and the cell membrane. Such a glucose-responsive PBAS film is promising for biological applications, including cell-based diagnostics and tissue engineering. In addition, the QCM-D proved to be a useful tool for in situ and real-time monitoring and analysis of interactions between cells and surfaces of supporting substrates.
Keyphrases
- cell adhesion
- room temperature
- single cell
- quantum dots
- cell therapy
- ionic liquid
- tissue engineering
- molecularly imprinted
- blood glucose
- carbon nanotubes
- induced apoptosis
- escherichia coli
- adipose tissue
- machine learning
- blood pressure
- type diabetes
- big data
- electronic health record
- endoplasmic reticulum stress
- mass spectrometry
- cystic fibrosis
- bone marrow
- staphylococcus aureus
- solid state
- candida albicans