Quantitative LA-ICP-MS Imaging of Elemental Distributions with Protein Correlation in 3D Tumor Models

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Materials Science

Background:

• Accurate mapping of elemental and drug distributions in 3D biological systems is vital for therapeutic efficacy.
• Current methods using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) face challenges in quantitative analysis of heterogeneous models due to preparation artifacts and calibration issues.

Purpose of the Study:

• To develop and validate a workflow for quantitative LA-ICP-MS imaging in tumor spheroids.
• To enable spatial correlation of elemental distributions with biological markers like immunohistochemistry.

Main Methods:

• Optimized cryo-embedding in carboxymethyl cellulose and freeze-drying to minimize analyte redistribution.
• Matrix-matched calibration with endogenous 31P normalization for pixel-level quantification.
• Consecutive section analysis for correlating elemental data with protein expression via immunohistochemistry.

Main Results:

• Optimized preparation reduced boron leaching by up to 84% compared to conventional methods.
• Achieved reproducible pixel-level quantification with high accuracy (r2 > 0.99) and validated against bulk ICP-MS.
• Demonstrated strong correlations between elemental and protein distributions across different cell lines, with 10 μm spatial resolution and low detection limits for boron.

Conclusions:

• The validated workflow provides a reproducible platform for quantitative elemental imaging in 3D biological systems.
• Enables cross-modal spatial analysis, correlating elemental and protein distributions for a deeper understanding of therapeutic efficacy.