Objective:

To develop a method for mapping local pH changes in 3D breast cancer models after different forms of cellular stress.

Approach:

• Sensor and model: Researchers led by Gail A. Vinnacombe-Willson loaded breast cancer cells with pH-responsive SERS nanotags and placed them on a 3D-printed hydrogel scaffold. The tags used polymer-coated gold nanostars functionalized with the Raman reporter 4-mercaptobenzoic ac…
• Treatments and analysis: Models were exposed to a chemotherapeutic agent, a cytotoxic surfactant, or light-induced plasmonic heating. SERS maps were collected across millimeter-scale 3D regions, and machine learning was used to identify and track pH-related spectral changes.

Key Findings:

• The nanotags detected pH increases after all three treatments, with response timing ranging from minutes to days depending on the stimulus.
• Independent cytotoxicity testing linked the pH increases to cell-membrane damage.
• SERS mapping provided subcellular spatial information across three-dimensional regions.

Interpretation:

The study demonstrates integration of responsive SERS tags into engineered tissue models to monitor spatial and time-dependent chemical changes associated with cell damage.

Limitations:

• Further work is needed to assess calibration stability and variation between sensors.
• The biological effects of the nanotags and their performance in models with additional cell types and extracellular components remain to be evaluated.