Plasmonic Functional Assay Platform Determines the Therapeutic Profile of Cancer Cells

Area of Science:

• Biophysics
• Cell Biology
• Cancer Research

Background:

• Traditional functional assays require large samples and long culture times, limiting their use for rapid drug susceptibility testing.
• Single-cell analysis offers potential to overcome bulk measurement limitations and identify cellular subpopulations.
• Existing methods struggle to provide rapid, detailed insights into individual cell responses to therapies.

Purpose of the Study:

• To develop a high-throughput plasmonic functional assay platform for real-time, single-cell analysis of cellular growth and therapeutic responses.
• To rapidly determine drug susceptibility, identify therapeutic heterogeneity, and assess drug combination effects.
• To enable personalized cancer therapy by quickly profiling individual cell responses to various treatments.

Main Methods:

• Developed a high-throughput plasmonic functional assay utilizing real-time spectral variations and plasmonic diffraction field intensity imaging.
• Monitored individual cell mass and growth rates at a scanning rate of >500 cells/h.
• Applied the platform to study MCF-7 cells' response to DFMO, 5-FU, PTX, and Dox, including drug combinations.

Main Results:

• The platform determined population growth profiles and individual cell mass changes in real time.
• Therapeutic profiles were assessed within hours, significantly faster than traditional methods requiring days.
• Identified drug-resistant subpopulations within MCF-7 cells and precisely determined synergistic/antagonistic effects of drug combinations.

Conclusions:

• The developed plasmonic functional assay platform enables rapid, high-throughput, single-cell analysis of cellular growth and drug response.
• This technology reveals cellular heterogeneity and identifies resistant subpopulations, crucial for effective cancer treatment.
• The platform facilitates personalized drug therapy by providing rapid insights into individual patient cell responses and optimal drug combinations.